AMC, Academic Medical Center; aOR, adjusted odds ratio; CI, confidence interval; CINIMA, Center for Infection and Immunology Amsterdam; DAG, directed acyclic graph; HIV, human immuno deficiency virus; i.e., id est, it is, for example; IQR, interquartile range; MEC, Medical Ethics Committee; MSM, men who have sex with men; OR, odds ratio; RIVM, National Institute of Public Health and the Environment, Centre for Infectious Disease Control; STI, sexually transmitted infection; UAI, unprotected anal intercourse; UMCU, University Medical Center Utrecht
New research should stay up-to-date as it pertains to rapid changing dating approaches and sero-adaptive behaviours (such as viral sorting and pre exposure prophylaxis). With every new way of dating and preventive chances, the rules of battles will change. Our data are 8years old and net-based dating has developed since then. Nevertheless these results are useful, as they demonstrate how internet-based partner acquisition can result in more information on the sex partner, and this may influence on the frequency of UAI.
Relationship online may offer other opportunities for communication on HIV status than dating in physical surroundings. Women Escorts nearest Calamvale Queensland. Women Escorts Near Me Glenroy Queensland. Easing more online HIV status disclosure during partner seeking makes serosorting simpler. Nonetheless, serosorting may increase the burden of other STI and will not prevent HIV infection completely. Interventions to prevent HIV transmission should particularly be directed at HIV-negative and unaware MSM and excite timely HIV testing (i.e., after danger events or when experiencing symptoms of seroconversion illness) as well as regular testing when sexually active.
Because conclusions on UAI seem to be partly based on sensed HIV concordance, precise knowledge of one's own and the partner's HIV status is essential. In HIV-negative men and HIV status-oblivious guys, decisions on UAI WOn't only be based on perceived HIV status of the partner but also on one's own negative status. HIV serosorting is challenged by the frequency of HIV testing and also the HIV window period during which individuals can transmit HIV but cannot be diagnosed with the commonly used HIV tests. Therefore serosorting can't be regarded as an extremely successful way of preventing HIV transmission 22 Besides interventions to stimulate the uptake of HIV and STI testing in sexually active men, interventions to warn against UAI based on sensed HIV-negative concordant status are in order, irrespective of whether this concerns online or offline dating.
For HIV-unaware guys the impact of dating location on UAI did not change by adding partner characteristics, but it improved when adding lifestyle and drug use. It's hard to assess the real risk for HIV for these guys: do they act as HIV negative men that are trying to protect themselves from HIV infection, or as HIV-positive guys trying to shield their HIV-negative partner from HIV infection? A study by Horvath et al. reported that 72% of men who were never tested for HIV, profiled themselves online as being HIV negative, which might be problematic if they are HIV-positive and participate in UAI with HIV negative partners 12 Previously Matser et al. reported that 1.7% of the unaware and sensed HIV-negative MSM were analyzed HIV positive. The study population included the MSM reported in this study 15
Online dating wasn't correlated with UAI among HIV negative guys, a finding in agreement with some previous studies, largely among young men 21 , but in contrast with other studies 1 - 5 This may be due to the fact that most earlier studies compared sexual behavior of two groups of MSM rather than comparing two sexual behavior patterns within one group of men. However it might also represent secular changes; possibly in the beginning of online dating a more high risk group of guys used the Internet, and over time online dating normalized and not as high-risk MSM now additionally use the Internet for dating.
A vital strength of this study was that it investigated the relationship between online dating and UAI among MSM who had recent sexual contact with both online and also offline casual partners. This prevented prejudice brought on by potential differences between guys just dating online and those just dating offline, a weakness of numerous previous studies. By recruiting participants at the greatest STI outpatient clinic in the Netherlands we could comprise a great number of MSM, and prevent potential differences in guys sampled through Internet or face to face interviewing, weaknesses in a few previous studies 3 , 11
Among HIV positive men, in univariate analysis UAI was reported significantly more frequently with on-line associates than with offline partners. When adjusting for partner characteristics, the effect of online/offline dating on UAI among HIV-positive MSM became somewhat smaller and became non significant; this suggests that differences in partnership variables between online and also offline partnerships are responsible for the increased UAI in online established partnerships. This could be due to a mediating effect of more information on associates, (including perceived HIV status) on UAI, or to other factors. Among HIV-negative men no effect of online dating on UAI was discovered, either in univariate or in any of the multivariate models. Women Escorts nearby Calamvale, Queensland. Among HIV-oblivious men, online dating was correlated with UAI but only significant when adding associate and venture variants to the model.
In this large study among MSM attending the STI clinic in Amsterdam, we found no signs that online dating was independently related to a higher risk of UAI than offline dating. Women Escorts nearest Calamvale Queensland. For HIV-negative men this dearth of assocation was clear (aOR = 0.94 95 % CI 0.59-1.48); among HIV positive men there was a non-significant association between online dating and UAI (aOR = 1.62 95 % CI 0.96-2.72). Only among guys who indicated they were not conscious of their HIV status (a little group in this study), UAI was more common with on-line than offline associates.
The number of sex partners in the preceding 6months of the index was also connected with UAI (OR = 6.79 95 % CI 2.86-16.13 for those with 50 or more recent sex partners compared to those with fewer than 5 recent sex partners). UAI was significantly more likely if more sex acts had occurred in the partnership (OR = 16.29 95 % CI 7.07-37.52 for >10 sex acts within the venture compared to just one sex act). Other variables significantly associated with UAI were group sex within the venture, and sex-connected multiple drug use within partnership.
In multivariate model 3 (Tables 4 and 5 ), also including variables concerning sexual behaviour in the venture (sex-associated multiple drug use, sex frequency and partner type), the independent effect of online dating place on UAI became somewhat more powerful (though not significant) for the HIV positive men (aOR = 1.62 95 % CI; 0.96-2.72), but remained similar for HIV-negative men (aOR = 0.94 95 % CI 0.59-1.48). The effect of online dating on UAI became stronger (and essential) for HIV-oblivious guys (aOR = 2.55 95 % CI 1.11-5.86) (Table 5 ).
In univariate analysis, UAI was significantly more prone to occur in online than in offline partnerships (OR = 1.36 95 % CI 1.03-1.81) (Table 4 ). The self-perceived HIV status of the participant was firmly correlated with UAI (OR = 11.70 95 % CI 7.40-18.45). The impact of dating place on UAI differed by HIV status, as can be seen best in Table 5 Table 5 shows the organization of online dating using three different reference categories, one for each HIV status. Among HIV-positive guys, UAI was more common in online when compared with offline partnerships (OR = 1.61 95 % CI 1.03-2.50). Among HIV-negative men no association was evident between UAI and online ventures (OR = 1.07 95 % CI 0.71-1.62). Among HIV-oblivious guys, UAI was more common in online when compared with offline ventures, though not statistically significant (OR = 1.65 95 % CI 0.79-3.44).
Characteristics of on-line and offline partners and partnerships are shown in Table 2 The median age of the partners was 34years (IQR 28-40). Compared to offline partners, more on-line partners were Dutch (61.3% vs. 54.0%; P 0.001) and were defined as a known partner (77.7% vs. 54.4%; P 0.001). The HIV status of on-line partners was more often reported as known (61.4% vs. 49.4%; P 0.001), and in online ventures, perceived HIV concordance was higher (49.0% vs. 39.8%; P 0.001). Participants reported that their online partners more frequently understood the HIV status of the participant than offline partners (38.8% vs. 27.2%; P 0.001). Participants more often reported multiple sexual contacts with internet partners (50.9% vs. 41.3%; P 0.001). Sex-related material use, alcohol use, and group sex were less often reported with internet partners.
To be able to examine the possible mediating effect of more information on partners (including perceived HIV status) on UAI, we developed three multivariable models. In model 1, we adapted the association between online/offline dating place and UAI for characteristics of the participant: age, ethnicity, number of sex partners in the preceding 6months, and self-perceived HIV status. In model 2 we added the venture characteristics (age difference, ethnic concordance, lifestyle concordance, and HIV concordance). In model 3, we adjusted additionally for venture sexual risk behavior (i.e., sex-related drug use and sex frequency) and partnership sort (i.e., casual or anonymous). As we assumed a differential effect of dating location for HIV-positive, HIV negative and HIV status unknown MSM, an interaction between HIV status of the participant and dating location was contained in all three models by making a new six-category variable. For clarity, the effects of online/offline dating on UAI are also presented individually for HIV-negative, HIV-positive, and HIV-unaware men. We performed a sensitivity analysis limited to partnerships in which only one sexual contact occurred. Statistical significance was defined as P 0.05. No adjustments for multiple comparisons were made, in order not to lose potentially significant associations. As a fairly big number of statistical evaluations were done and reported, this strategy does lead to an elevated risk of one or more false positive associations. Analyses were done utilizing the statistical programme STATA, version 13 (STATA Intercooled, College Station, TX, USA).
Before the investigations we developed a directed acyclic graph (DAG) representing a causal model of UAI. In this model some variables were putative causes (self-reported HIV status; on-line partner acquisition), others were considered as confounders (participants' age, participants' ethnicity, and no. Calamvale Women Escorts. of male sex partners in preceding 6months), and some were presumed to be on the causal pathway between the primary exposure of interest and outcome (age difference between participant and partner; ethnic concordance; concordance in life styles; HIV concordance; partnership sort; sex frequency within partnership; group sex with partner; sex-associated material use in partnership).
We compared characteristics of participants by self-reported HIV status (using 2-tests for dichotomous and categorical variables and using rank sum test for continuous variables). Women Escorts Near Me Toowoomba Queensland. We compared characteristics of participants, partners, and venture sexual behaviour by online or offline partnership, and computed P values predicated on logistic regression with robust standard errors, accounting for related data. Continuous variables (i.e., age, amount of sex partners) are reported as medians with an interquartile range (IQR), and were categorised for inclusion in multivariate models. Random effects logistic regression models were used to analyze the association between dating place (online versus offline) and UAI. Odds ratio tests were used to assess the value of a variable in a model.
In order to explore potential disclosure of HIV status we also asked the participant whether the casual sex partner knew the HIV status of the participant, together with the answer alternatives: (1) no, (2) perhaps, (3) yes. Sexual behavior with each partner was dichotomised as: (1) no anal intercourse or just shielded anal intercourse, and (2) unprotected anal intercourse. To determine the subculture, we asked whether the participant characterised himself or his partners as belonging to one or more of the following subcultures/lifestyles: casual, formal, alternate, drag, leather, military, sports, trendy, punk/skinhead, rubber/lycra, gothic, bear, jeans, skater, or, if not one of these characteristics were applicable, other. Concordant lifestyle was categorised as: (1) concordant; (2) discordant. Accidental partner kind was categorised by the participants into (1) known traceable and (2) anonymous partners.
HIV status of the participant was obtained by asking the question 'Do you understand whether you are HIV infected?', with five answer choices: (1) I 'm definitely not HIV-infected; (2) I believe that I'm not HIV-contaminated; (3) I don't know; (4) I believe I may be HIV-infected; (5) I know for sure that I am HIV-infected. We categorised this into HIV-negative (1,2), unknown (3), and HIV positive (4,5) status. The questionnaire enquired about the HIV status of each sex partner together with the question: 'Do you know whether this partner is HIV-infected?' with similar answer choices as above. Perceived concordance in HIV status within ventures was categorised as; (1) concordant; (2) discordant; (3) unknown. Women Escorts nearest Calamvale QLD. The final category represents all partnerships where the participant didn't understand his own status, or the status of his partner, or both. In this study the HIV status of the participant is self-reported and self-perceived. The HIV status of the sexual partner is as perceived by the participant.