Sexual mixing in bisexual activity in male–male partnerships in Melbourne, Australia
Hayden A. Griffiths
A B , Christopher K. Fairley A B , Jason J. Ong A B , Eric P. F. Chow A B C # * and Tiffany R. Phillips A B #
A
B
C
Handling Editor: Kevan Wylie
Abstract
The patterns of sexually transmitted infections (STIs) in populations may be influenced by the sexual mixing within the population. We aimed to investigate the assortative sexual mixing pattern by bisexuality in male–male partnerships.
This was a retrospective repeated cross-sectional study of men with mostly regular male partners attending the Melbourne Sexual Health Centre between 2011 and 2019. Data on sexual practices, including their sexual practices, presence of other male/female sex partners and the gender of sexual partners in the previous 3 and 12 months, were collected using computer-assisted self-interview. We calculated the proportion of male partnerships where at least one man in the partnership reported a female sex partner.
A total of 2056 male–male partnerships (i.e. 4112 individuals) with a median age of 29 years (IQR 25 to 35) were included. Overall, in 94.4% (1941/2056) of male–male partnerships both men had male partners only; however, in 5.5% (113/2056) of partnerships, one man had both male and female partners, and in 0.1% (2/2056) partnerships, both men had both male and female partners. No assortative relationship was found on the sexual mixing by bisexuality in male–male partnerships due to the low assortativity coefficient (r = 0.006, 95% CI: −0.004 to 0.016).
One in 20 male–male partnerships had at least one man who had both male and female partners within the preceding year. Individuals were not selective by bisexuality, suggesting that partnerships of bisexual individuals are mixed proportionately to the distribution of their characteristics. Still, these sexual mixing practices may affect STI transmission dynamics.
Keywords: assortativity, bisexual, heterosexual, mixing, opposite-sex, same-sex, sexual mixing, sexual networks, sexual partners, sexual practice.
Introduction
Sexually transmitted infections (STIs) continue to rise worldwide, affecting all populations, including in Australia.1,2 STIs disproportionately affect gay, bisexual and other men who have sex with men (GBMSM) in Australia;2 however, STIs have become more generalised with increasing cases in heterosexuals.3,4 For example, the notification rate of infectious syphilis in the female population has increased from 149 cases in 2013 to 1063 cases in 2022, a 613% increase in 10 years.5 The rise in syphilis in women has led to the re-emergence of congenital syphilis, which has become a major public health concern.6 The rise in STIs in different populations is complex and due to multiple factors. Past epidemiological and genomic studies have indicated that HIV/STI transmission may occur across different populations due to sexual mixing.7,8
Sexual mixing represents the tendency of individuals with comparable qualities to mix together.9 Individuals may prefer sexual partners with similar age, country of birth, HIV status, PrEP use, and number of sexual partners.9–13 Some mixing patterns can facilitate STI transmission more than would occur if partners mixed randomly. Individuals who have sex with more than one gender may acquire or transmit the infections across different populations. A Melbourne-based study has shown that about 13% of GBMSM clinic attendees have both male and female sexual partners.14 Another study from Melbourne of 2112 male–female partnerships (regular and casual) reported that having both male and female partners occurred more commonly than would be expected by chance (assortative mixing pattern), with one in 10 partnerships having at least one individual who has a same-sex partner.15 However, there are limited data on bisexuality mixing patterns in GBMSM. This study aimed to examine sexual mixing patterns by bisexuality for male–male partnerships attending a sexual health clinic in Melbourne, Australia.
Materials and methods
Study design and population
This was a retrospective repeated cross-sectional study of male–male partnerships attending the Melbourne Sexual Health Centre (MSHC), Australia, from 2011 to 2019. The MSHC is a public HIV and STI clinic that provides a wide range of free services, including testing, diagnosis, and treatment.
Data collection
Upon arrival, new and existing clients who had not visited the MSHC in the previous 3 months were asked to complete a questionnaire utilising a computer-assisted self-interview (CASI). This questionnaire is part of the routine clinical care and management at MSHC, which collects data on the client’s demographic characteristics and sexual practices. If the client attends MSHC with their partners, we ask the client to provide their partner’s name on CASI; then we match the two individuals together. For the purpose of this analysis, we defined a male–male partnership if both men attended and were seen by a clinician at MSHC on the same day or within 5 days after the first individual in the partnership attended MSHC. Manual chart reviews were conducted to verify that both men met the definition of ‘partnership’ for this study. Each client was assigned a unique de-identified study number, and partnerships were given a unique partnership number. We only included each partnership once to be consistent with other partnerships, as GBMSM are more likely to visit the clinic more than once during the 12-month duration of the study.16 However, if one of the individuals in the partnerships had changed partners, the new partnership was included in the analysis. We also excluded any individuals who were aged 16 years or under and the corresponding partnership.
Demographic characteristics (i.e. age and country of birth), sexual practices (i.e. type of partners [regular and/or casual], and gender of partners in the previous 12 months) were self-reported by each individual independently. The partners that the survey participants had in the previous 12 months are in addition to the male partners they are defined with as a couple. If both males in a partnership indicated that they had only one male partner in the previous 3 and 12 months it was assumed the partner they attended clinic with was this sexual partner; and thus they were classified for analysis as having no sexual partners outside of the relationship.
Statistical analysis
Descriptive statistics were used to describe the characteristics of the partnerships. Continuous variables (e.g. age) were presented as medians and interquartile ranges (IQR). Categorical variables (e.g. country of birth) were reported as frequency and proportion. We calculated the proportion of partnerships where (1) both had male partners and did not have female partners; (2) one man had both male and female partners; and (3) both had male and female partners. The chi-squared trend test was used to examine the changes in the annual proportion over time.
The expected number of male–male partnerships was calculated by multiplying the marginal distributions of the sexual partners’ characteristics, and the observed/expected ratios (O/E ratio) were calculated based on the observed and expected partnerships under the assumptions of proportionate mixing.
To identify sexual mixing patterns by the individual, we calculated the Newman’s assortativity coefficient (r) using a (k × k) mixing matrix as:
where r is Newman’s assortativity coefficient, eii is the proportion of partnerships with the same recorded sex of sexual partners, and ai and bi are the sum of the rows and columns of the (k × k) matrix, respectively. The Newman’s assortativity coefficient falls between −1 and +1, with +1 means perfect assortativity, 0 means no assortativity, and −1 means perfect disassortativity. The variance from the calculation above was used to calculate the 95% confidence intervals (Cl). All analyses were conducted in Stata (ver. 17, StataCorp, College Station, TX, USA).
Results
We included 2056 male–male partnerships (i.e. 4112 individuals) between 2011 and 2019 who met the inclusion criteria, and all partnerships were verified through manual chart review.
The median age of the 4112 men was 29 years (IQR 25 to 35). More than half (53%, 2181/2056) were born in Australia. Of the 2056 male–male partnerships included in the analysis, 93 (4.5%) partnerships where neither man had a male partner outside the partnership and the majority of the partnerships (89.9%, 1848/2056, 95% CI: 88.5 to 91.2%) were both men who only had male partners outside the partnership in the previous 12 months. A small proportion of the partnerships (5.5%, 113/2056) consisted of one man who had both male and female partners outside the partnership, and there were only two partnerships where both men had both male and female partners (Table 1). Overall, one in 20 male–male partnerships (5.6%, 115/2056) had at least one man who had both male and female partners in the previous 12 months. However, the proportion of male–male partnerships with at least one man who had both male and female partners in the previous 12 months did not change significantly during the study period (ptrend = 0.493).
| Year | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | Total | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Total partnerships, N | 95 | 153 | 174 | 186 | 226 | 303 | 287 | 334 | 298 | 2056 | |
| Neither man had male partners outside the partnership in the previous 12 months, n (%) | 5 (5.3) | 13 (8.5) | 10 (5.7) | 11 (5.9) | 7 (3.1) | 13 (4.3) | 11 (3.8) | 11 (3.3) | 12 (4.0) | 93 (4.5) | |
| Both had only male partners outside the partnership in the previous 12 months, n (%) | 78 (82.1) | 135 (88.2) | 151 (86.8) | 167 (89.8) | 211 (93.4) | 274 (90.4) | 256 (89.2) | 310 (92.8) | 266 (89.3) | 1848 (89.9) | |
| One had male and female partners outside the partnership in the previous 12 months, n (%) | 12 (12.6) | 5 (3.2) | 13 (7.4) | 8 (4.3) | 8 (3.5) | 15 (5.0) | 20 (7.0) | 13 (3.9) | 19 (6.4) | 113 (5.5) | |
| Both had male and female partners outside the partnership in the previous 12 months, n (%) | 0 | 0 | 0 | 0 | 0 | 1 (0.3) | 0 | 0 | 1 (0.3) | 2 (0.1) |
The sexual mixing patterns were calculated based on all sexual partners (including the partner in the defined partnership) among 2056 partnerships. Both men had regular male partners in 57.9% (1190/2056) of partnerships, one man had a regular male partner in 32.1% (660/2056) of partnerships, and neither had regular male partners in 10.0% (206/2056) of partnerships (Supplementary material Table S1). Similarly, both men had casual male partners in 47.5% of partnerships (976/2056), one man had a casual male partner in 37.9% of partnerships (783/2056), and neither had casual male partners in 14.4% of partnerships (297/2056) (Table S2). There were no partnerships where both men had regular female partners, but a small proportion of partnerships existed where one man had a regular female partner (0.08%, 17/2056) (Table S3). Similarly, only a small proportion of partnerships consisted of both men (0.01%, 2/2056) or one man (4.82%, 99/2056) who had casual female partners (Table S4).
The O/E ratios for male partners are close to 1, suggesting that there is little difference between the observed and the expected result for male–male partnerships to have regular and/or casual male partners (Table 2). However, the O/E ratio for male–male partnerships who had casual female sexual partners is 1.54 times higher than expected (Table 2).
| Sexual partnersA | Observed partnerships, n | Expected partnerships, n | Observed/expected partnerships (95% CI) | Newman assortativity coefficient, r (95% CI) | |
|---|---|---|---|---|---|
| Gender of partners | N/A | N/A | N/A | 0.006 (−0.004 to 0.016) | |
| Both had only male partners in the previous 12 months | 1941 | 1940.7 | 1.00 (1.00–1.00) | N/A | |
| Both had male and female partners in the previous 12 months | 2 | 1.7 | 1.18 (0.75–1.60) | N/A | |
| Both had a regular male sexual partner in the previous 12 months | 1190 | 1119.8 | 1.06 (1.01–1.11) | 0.175 (0.149 to 0.202) | |
| Both had a casual male sexual partner in the previous 12 months | 976 | 905.6 | 1.08 (1.03–1.12) | 0.152 (0.124 to 0.180) | |
| Both had a regular female sexual partner in the previous 12 months | 0 | 0 | 0 | 0 | |
| Both had a casual female sexual partner in the previous 12 months | 2 | 1.3 | 1.54 (0.92–2.15) | 0.014 (0.005 to 0.024) |
No assortative relationship was found on the sexual mixing by bisexuality in male–male partnerships due to the low assortativity coefficient (r = 0.006, 95% CI: −0.004 to 0.016), indicating the mixing of individuals in a partnership where both had male and female partners were expected to be proportionate to the characteristics’ distribution (Table 2). Having regular and casual male sexual partners in male–male partnerships was minimally assortative, with assortativity coefficients of 0.175 (95% CI: 0.149 to 0.202) and 0.152 (95% CI: 0.124 to 0.180), respectively (Table 2). There was also no indication of assortativity for having casual female partners in male–male partnerships, as the assortativity coefficient is close to zero (=0.01, 95% CI: 0.01 to 0.02) (Table 2).
Discussion
We included 2056 male–male partnerships attending an urban sexual health clinic in Melbourne over 9 years. The analysis concluded that 5.6% of partnerships comprised at least one individual with male and female partners in the previous 12 months. There is no assortative mixing pattern on the gender of partners in male–male partnerships in our study. However, partners were minimally assortative on having regular or casual male partners.
Past studies have examined the sexual mixing patterns in bisexuality in male–female partnerships. A study conducted in the United Kingdom in 2010 observed highly assortative mixing (r = 0.48; 95% CI: 0.20 to 0.69) in any lifetime same-sex experience among 943 heterosexual couples, and this result is not consistent with our findings.17 Our study only included sexual partners in the previous 12 months instead of all lifetime partners, which may contribute to differing effects between the two studies as sexual attractions may have changed over time. Another study conducted in Melbourne observed weak assortative mixing in having same-sex partners among 2112 male–female partnerships, with one in 10 partnerships including at least one person who also had same-sex partners.15 Individuals who had other same-sex partners were more likely to be in partnership with another individual who also had other same-sex partners than would be predicted by chance.
The Newman’s assortativity coefficient was calculated to examine the assortative sexual mixing by bisexuality in male–male partnerships, where r was 0.01. The low assortativity coefficient indicates that bisexual individuals in male–male partnerships are not significantly skewed towards forming partnerships exclusively with other bisexual individuals or exclusively with individuals of other sexual orientations, suggesting that partnerships of bisexual individuals are mixed proportionately to the distribution of their characteristics. However, the assortativity coefficient can potentially be altered if multiple partners are considered in the calculation. It is important to note that the confidence intervals suggest that the actual assortativity coefficient could range from slightly negative to slightly positive, implying that the sample size of this study is too small, and more data is required to determine the sexual mixing of bisexual individuals in male–male partnerships.
Nonetheless, historical changes in societal acceptability of same-sex sexuality have resulted in increased population prevalence of same-sex sexuality and sexual fluidity.18 Studies had examined heterosexuals’ behaviour towards their willingness to engage in same-sex experiences, but not for GBMSM towards opposite-sex experiences.19 As STIs disproportionately affect GBMSM, sexual mixing can potentially lead to STI transmission linkages between populations from individuals who are at higher risk to those who are at lower risk.
This study has several limitations. First, this study may not be generalisable to the general Australian population and in other settings. This study was conducted in a single urban sexual health clinic and STI clinic attendees may be different to those who do not attend STI clinic (e.g. STI clinic attendees may have a higher likelihood of STI-related symptoms than the overall population). Second, we have only included individuals with male or female partners, but not other genders. A past study has estimated about 1% of male STI clinic attendees reported having sex with a transgender or gender-diverse person.20 Third, individuals may have multiple partners in the previous 12 months. However, we only included one partner in the defined partnership in this analysis. Further studies will be required to explore the sexual mixing within a sexual network with multiple partners. Fourth, we defined bisexual individuals based on their sexual practice but not their sexual identity. Additional research would also be required to explore the individuals’ sexual identities. Fifth, there may be some ethnic and cultural differences in sexual activities.21,22 However, we were unable to explore these factors in bisexual mixing due to a small number of partnerships reporting bisexual activities. Lastly, GBMSM are more likely to attend the clinic more than once, but we only included each partnership once to be consistent with other partnerships.16 Furthermore, the partners that the survey participants had in the previous 12 months are inclusive of the male partner(s) they are defined with as a couple. It is also possible that the individuals within the partnerships might have changed their sexual practices over time.
To conclude, we found that 5.6% of the male–male partnerships have at least one individual who had both male and female partners. However, there was no significant assortative mixing pattern in bisexuality in male–male partnerships attending an STI clinic in Melbourne. Still, these sexual mixing practices may affect STI transmission dynamics; e.g. from high-risk to low-risk populations. Further research, including mathematical modelling, is required to explore the degree of STI transmission by bisexual individuals, the impact this may have on STI epidemiology and potential targets for preventative health measures specifically for bisexual individuals.
Data availability
The data that support this study are available in the article and accompanying online supplementary material.
Conflicts of interest
EPFC and TRP are Associate Editors and JJO is the co-Editor-in Chief of Sexual Health. To mitigate this potential conflict of interest they had no editor-level access to this manuscript during peer review. All other authors declare no conflicts of interest.
Declaration of funding
EPFC and JJO are each supported by the National Health and Medical Research Council (NHMRC) Emerging Leadership Investigator Grant (GNT1172873 and GNT1193955, respectively). CKF is supported by the NHMRC Leadership Investigator Grant (GNT1172900). NHMRC has no direct contribution to the study.
Author contributions
EPFC and TRP conceived and designed the study, and contributed equally to this paper. HAG and EPFC performed data analyses. HAG performed the literature review and wrote the first draft of the manuscript. All authors provided data interpretation, revised the manuscript for intellectual content, and approved the final version of the manuscript. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.
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