To be able to analyze the potential mediating effect of more information on partners (including perceived HIV status) on UAI, we developed three multivariable models. In model 1, we adjusted the association between online/offline dating location 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 version 3, we adjusted additionally for partnership sexual risk behavior (i.e., sex-related drug use and sex frequency) and partnership 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 contained in all three models by making a fresh six-class variable. For clarity, the effects of online/offline dating on UAI are also presented individually for HIV-negative, HIV positive, and HIV-unaware men. Cheap prostitutes near Fort Norman Northwest Territories. 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 large number of statistical evaluations were done and reported, this approach does lead to a higher danger of one or more false positive organizations. Analyses were done utilizing the statistical programme STATA, version 13 (STATA Intercooled, College Station, TX, USA).
Characteristics of on-line and offline partners and ventures 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 online partners was more often reported as understood (61.4% vs. 49.4%; P 0.001), and in online partnerships, 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 often reported multiple sexual contacts with online partners (50.9% vs. Cheap Prostitutes nearest Fort Norman. 41.3%; P 0.001). Sex-associated substance use, alcohol use, and group sex were less frequently reported with online partners.
In univariate analysis, UAI was significantly more likely to happen in on-line than in offline ventures (OR = 1.36 95 % CI 1.03-1.81) (Table 4 ). The self-perceived HIV status of the participant was firmly associated 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 distinct reference types, one for each HIV status. Cheap Prostitutes nearest Northwest Territories. Among HIV-positive men, UAI was more common in online in comparison to offline ventures (OR = 1.61 95 % CI 1.03-2.50). Among HIV negative men no association was apparent between UAI and on-line ventures (OR = 1.07 95 % CI 0.71-1.62). Among HIV-oblivious guys, UAI was more common in online when compared with offline partnerships, though not statistically significant (OR = 1.65 95 % CI 0.79-3.44).
In multivariate model 3 (Tables 4 and 5 ), also including variants concerning sexual behavior in the partnership (sex-associated multiple drug use, sex frequency and partner type), the independent effect of online dating location 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 more powerful (and important) for HIV-oblivious guys (aOR = 2.55 95 % CI 1.11-5.86) (Table 5 ).
The amount of sex partners in the preceding 6months of the index was likewise correlated 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 happened 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-related multiple drug use within partnership.
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. Cheap prostitutes nearest Fort Norman. 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). Cheap prostitutes near Fort Norman. Just among guys who suggested they were not conscious of their HIV status (a little group in this study), UAI was more common with on-line than offline partners.
Among HIV-positive men, in univariate analysis UAI was reported significantly more frequently with on-line partners than with offline partners. When correcting 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 offline partnerships are responsible for the increased UAI in online established ventures. This may be due to a mediating effect of more information on partners, (including perceived HIV status) on UAI, or to other factors. Among HIV-negative guys no effect of online dating on UAI was detected, either in univariate or in some of the multivariate models. Among HIV-oblivious men, online dating was correlated with UAI but only significant when adding associate and partnership variables to the model.
A vital strength of this study was that it investigated the connection between online dating and UAI among MSM who had recent sexual contact with both online and also offline casual partners. This avoided prejudice due to potential differences between men just dating online and those only dating offline, a weakness of numerous previous studies. By recruiting participants at the largest STI outpatient clinic in the Netherlands we could include a high number of MSM, and prevent potential differences in guys sampled through Internet or face-to-face interviewing, weaknesses in some previous studies 3 , 11
Online dating was not associated with UAI among HIV negative men, 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 guys. Yet it might also represent secular changes; possibly in the beginning of online dating a more high risk group of men used the Internet, and over time online dating normalized and not as high risk MSM nowadays also utilize the Net for dating.
For HIV-unaware guys the effect of dating location on UAI didn't change by adding partner characteristics, but it improved when adding lifestyle and drug use. It is hard to assess the actual risk for HIV for these guys: do they act as HIV negative men who are trying to shield themselves from HIV infection, or as HIV-positive men attempting to safeguard 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're HIV-positive and engage in UAI with HIV-negative partners 12 Formerly Matser et al. reported that 1.7% of the oblivious and perceived HIV negative MSM were examined HIV-positive. The study population included the MSM reported in this study 15
Because determinations on UAI seem to be partly based on perceived HIV concordance, accurate knowledge of one's own and the partner's HIV status is very important. In HIV-negative men and HIV status-oblivious men, determinations 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 as well as 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 a very powerful method of avoiding HIV transmission 22 Besides interventions to trigger the uptake of HIV and STI testing in sexually active men, interventions to caution against UAI based on sensed HIV-negative concordant status are in order, irrespective of whether this concerns online or offline dating. Cheap Prostitutes closest to Fort Norman Northwest Territories.
Relationship online may offer other opportunities for communicating on HIV status than dating in physical environments. Facilitating more online HIV status disclosure during partner seeking makes serosorting easier. However, serosorting may increase the burden of other STI and will not prevent HIV infection entirely. Interventions to prevent HIV transmission should particularly be directed at HIV negative and oblivious MSM and arouse timely HIV testing (i.e., after hazard occasions or when experiencing symptoms of seroconversion illness) as well as regular testing when sexually active.
New research should remain up to date when it comes to accelerated altering dating methods and sero-adaptive behaviours (such as viral sorting and pre exposure prophylaxis). With every new way of dating and preventative chances, the rules of battles will be different. Our data are 8years old and internet-based dating has developed since then. Cheap Prostitutes Near Me Fort Mcpherson Northwest Territories. Cheap Prostitutes Near Me Fort Resolution Northwest Territories. Yet these results are useful, as they reveal how internet-based partner acquisition can lead to more information on the sex partner, and this might influence 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 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
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