In order to examine the potential 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 location and UAI for features of the participant: age, ethnicity, number of sex partners in the preceding 6months, and self-perceived HIV status. In model 2 we added the partnership features (age difference, ethnic concordance, lifestyle concordance, and HIV concordance). In model 3, we adjusted also for venture sexual risk behaviour (i.e., sex-associated drug use and sex frequency) and venture type (i.e., casual or anonymous). As we assumed a differential effect of dating place for HIV positive, HIV-negative and HIV status unknown MSM, an interaction between HIV status of the participant and dating place was included in all three models by making a new six-class variable. For clarity, the effects of online/offline dating on UAI are also presented individually for HIV negative, HIV positive, and HIV-oblivious men. Cheap Prostitutes in Mabou Nova Scotia. We performed a sensitivity analysis restricted 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 important organizations. As a fairly large number of statistical tests were done and reported, this strategy does lead to an elevated danger of one or more false-positive associations. Analyses were done using the statistical programme STATA, version 13 (STATA Intercooled, College Station, TX, USA).
Characteristics of online and offline partners and ventures are revealed 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 online 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 often knew the HIV status of the participant than offline partners (38.8% vs. 27.2%; P 0.001). Participants more frequently reported multiple sexual contacts with online partners (50.9% vs. Cheap prostitutes nearest Mabou. 41.3%; P 0.001). Sex-related material use, alcohol use, and group sex were less often reported with online partners.
In univariate analysis, UAI was significantly more likely to occur in online than in offline ventures (OR = 1.36 95 % CI 1.03-1.81) (Table 4 ). The self-perceived HIV status of the participant was strongly correlated with UAI (OR = 11.70 95 % CI 7.40-18.45). The impact of dating location 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 classes, one for each HIV status. Cheap Prostitutes in Nova Scotia. Among HIV-positive guys, UAI was more common in online compared to offline partnerships (OR = 1.61 95 % CI 1.03-2.50). Among HIV-negative men no association was apparent between UAI and internet ventures (OR = 1.07 95 % CI 0.71-1.62). Among HIV-oblivious guys, UAI was more common in online in comparison to offline ventures, though not statistically significant (OR = 1.65 95 % CI 0.79-3.44).
In multivariate model 3 (Tables 4 and 5 ), additionally including variables concerning sexual behaviour in the partnership (sex-associated multiple drug use, sex frequency and partner kind), the independent effect of online dating location on UAI became somewhat more powerful (though not essential) for the HIV-positive guys (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 more powerful (and significant) for HIV-oblivious guys (aOR = 2.55 95 % CI 1.11-5.86) (Table 5 ).
The number of sex partners in the preceding 6months of the index was also associated 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 partnership 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 this large study among MSM attending the STI clinic in Amsterdam, we found no evidence that online dating was independently related to a higher danger of UAI than offline dating. Cheap prostitutes near Mabou. For HIV negative guys this dearth of assocation was clear (aOR = 0.94 95 % CI 0.59-1.48); among HIV-positive guys there was a nonsignificant association between online dating and UAI (aOR = 1.62 95 % CI 0.96-2.72). Cheap prostitutes near Mabou. Only among men who indicated they were not aware of their HIV status (a small group in this study), UAI was more common with online than offline associates.
Among HIV positive guys, in univariate analysis UAI was reported significantly more often with on-line associates than with offline associates. When correcting for partner characteristics, the effect of online/offline dating on UAI among HIV-positive MSM became somewhat smaller and became nonsignificant; this implies that differences in partnership factors between online and also offline partnerships are accountable for the increased UAI in online established ventures. This could be because of a mediating effect of more info on partners, (including perceived HIV status) on UAI, or to other variables. Among HIV-negative guys no effect of online dating on UAI was detected, either in univariate or in any of the multivariate models. Among HIV-unaware men, online dating was associated with UAI but only essential when adding partner and partnership variables to the model.
A key strength of this study was that it investigated the relation between online dating and UAI among MSM who had recent sexual contact with both online and offline casual partners. This averted bias due to potential differences between men only dating online and those just dating offline, a weakness of several previous studies. By recruiting participants at the biggest STI outpatient clinic in the Netherlands we could contain a lot of MSM, and avoid potential differences in guys tried through Internet or face-to-face interviewing, weaknesses in some previous studies 3 , 11
Online dating was not associated with UAI among HIV negative guys, a finding in agreement with some previous studies, mainly 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 behaviour patterns within one group of guys. Nevertheless it could also reflect secular changes; perhaps in the beginning of online dating a more high risk group of men used the Internet, and over time online dating normalized and less high-risk MSM today additionally make use of the Internet for dating.
For HIV-unaware men the impact of dating location on UAI didn't change by adding partner characteristics, but it increased when adding lifestyle and drug use. It is difficult to evaluate the actual risk for HIV for these guys: do they act as HIV-negative guys that are attempting to protect themselves from HIV infection, or as HIV positive guys trying to guard their HIV negative partner from HIV infection? A study by Horvath et al. reported that 72% of guys who were never tested for HIV, profiled themselves online as being HIV-negative, which might be debatable 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 perceived HIV negative MSM were tested HIV-positive. The study population comprised the MSM reported in this study 15
Because conclusions on UAI appear to be partly based on perceived HIV concordance, exact knowledge of one's own and the partner's HIV status is essential. In HIV-negative men and HIV status-oblivious men, decisions on UAI WOn't only be based on perceived HIV status of the partner but in addition on one's own negative status. HIV serosorting is challenged by the frequency of HIV testing and also the HIV window period during which people can transmit HIV but cannot be diagnosed with the commonly used HIV tests. Hence serosorting can't be regarded as an extremely successful method of averting 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. Cheap prostitutes in Mabou Nova Scotia.
Dating online may offer other chances for communication on HIV status than dating in physical surroundings. Easing more online HIV status disclosure during partner seeking makes serosorting easier. Nonetheless, serosorting may raise the burden of other STI and will not prevent HIV disease entirely. Interventions to prevent HIV transmission should especially be directed at HIV-negative and unaware MSM and excite timely HIV testing (i.e., after risk occasions or when experiencing symptoms of seroconversion illness) as well as routine testing when sexually active.
New research should remain up to date when it comes to accelerated changing dating procedures and sero-adaptive behaviours (like viral sorting and pre exposure prophylaxis). With each new way of dating and preventative opportunities, the rules of engagements will vary. Our data are 8years old and internet-based dating has developed since then. Cheap Prostitutes Near Me Lynn Nova Scotia. Cheap Prostitutes Near Me Mabou Harbour Nova Scotia. However these results are useful, as they reveal how web-based partner acquisition can lead to more info on the sex partner, and this might affect on the frequency of UAI.
AMC, Academic Medical Center; aOR, adjusted odds ratio; CI, confidence interval; CINIMA, Center for Infection and Immunology Amsterdam; DAG, directed acyclic graph; HIV, human immunodeficiency virus; i.e., id est, it's, 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
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