The number of sex partners in the preceding 6months of the index was likewise 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). Free Fuck Book in Coburg Victoria. 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 venture compared to only one sex act). Free Fuck Book Near Me Noble Park Victoria. Other variables significantly associated with UAI were group sex within the partnership, and sex-related multiple drug use within partnership.
In multivariate model 3 (Tables 4 and 5 ), additionally including variants concerning sexual behavior in the venture (sex-associated multiple drug use, sex frequency and partner type), the independent effect of online dating place on UAI became somewhat stronger (though not essential) for the HIV positive men (aOR = 1.62 95 % CI; 0.96-2.72), but remained similar for HIV-negative guys (aOR = 0.94 95 % CI 0.59-1.48). The effect of online dating on UAI became more powerful (and essential) for HIV-unaware guys (aOR = 2.55 95 % CI 1.11-5.86) (Table 5 ).
In univariate analysis, UAI was significantly more likely to occur in on-line than in offline ventures (OR = 1.36 95 % CI 1.03-1.81) (Table 4 ). Free Fuck Book closest to Victoria Australia. The self-perceived HIV status of the participant was strongly connected with UAI (OR = 11.70 95 % CI 7.40-18.45). The result of dating place on UAI differed by HIV status, as can be seen best in Table 5 Table 5 shows the association of online dating using three different reference classes, one for each HIV status. Among HIV-positive guys, UAI was more common in online when compared with offline ventures (OR = 1.61 95 % CI 1.03-2.50). Among HIV negative guys no association was apparent between UAI and internet partnerships (OR = 1.07 95 % CI 0.71-1.62). Among HIV-oblivious men, 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 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 frequently 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 online partners (50.9% vs. 41.3%; P 0.001). Coburg VIC, Australia Free Fuck Book. Sex-associated substance use, alcohol use, and group sex were less often reported with internet partners.
To be able to examine the potential mediating effect of more info 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 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 characteristics (age difference, ethnic concordance, lifestyle concordance, and HIV concordance). In version 3, we adapted also for partnership sexual risk behaviour (i.e., sex-related drug use and sex frequency) and venture 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 place was included in all three models by making a fresh six-category variable. For clarity, the effects of online/offline dating on UAI are also presented separately for HIV-negative, HIV-positive, and HIV-oblivious men. We performed a sensitivity analysis limited to partnerships in which just one sexual contact occurred. Statistical significance was defined as P 0.05. Free Fuck Book nearest Coburg, Australia. No adjustments for multiple comparisons were made, in order not to lose potentially important organizations. As a rather big number of statistical tests were done and reported, this strategy does lead to an increased danger of one or more false positive associations. Investigations were done utilizing the statistical programme STATA, version 13 (STATA Intercooled, College Station, TX, USA).
Prior to the investigations we developed a directed acyclic graph (DAG) representing a causal model of UAI. In this model some variants were putative causes (self-reported HIV status; online partner acquisition), others were considered as confounders (participants' age, participants' ethnicity, and no. of male sex partners in preceding 6months), and some were presumed to be on the causal pathway between the main exposure of interest and results (age difference between participant and partner; ethnic concordance; concordance in life styles; HIV concordance; partnership sort; sex frequency within venture; group sex with partner; sex-associated substance use in partnership).
We compared characteristics of participants by self-reported HIV status (using 2-evaluations for dichotomous and categorical variables and using rank sum test for continuous variables). We compared characteristics of participants, partners, and venture sexual conduct by on-line or offline venture, and computed P values predicated on logistic regression with robust standard errors, accounting for related data. Continuous variables (i.e., age, number 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 location (online versus offline) and UAI. Likelihood ratio tests were used to evaluate the value of a variable in a model.
To be able to explore possible disclosure of HIV status we additionally asked the participant whether the casual sex partner understood the HIV status of the participant, together with the answer options: (1) no, (2) maybe, (3) yes. Sexual behaviour with each partner was dichotomised as: (1) no anal intercourse or merely shielded anal intercourse, and (2) unprotected anal intercourse. To ascertain 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, alternative, drag, leather, military, sports, trendy, punk/skinhead, rubber/lycra, gothic, bear, jeans, skater, or, if none of these features were related, other. Concordant lifestyle was categorised as: (1) concordant; (2) discordant. Casual partner sort was categorised by the participants into (1) known traceable and (2) anonymous partners.
HIV status of the participant was got by asking the question 'Do you know whether you are HIV infected?', with five answer alternatives: (1) I 'm definitely not HIV-infected; (2) I think that I'm not HIV-infected; (3) I do not know; (4) I think 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 survey enquired about the HIV status of every sex partner together with the question: 'Do you know whether this partner is HIV-infected?' with similar reply options as above. Perceived concordance in HIV status within ventures was categorised as; (1) concordant; (2) discordant; (3) unknown. The last 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.
Participants completed a standardised anonymous questionnaire throughout their trip to the STI outpatient clinic while waiting for preliminary evaluation results after their consultation using a nurse or physician. The questionnaire elicited information on socio-demographics and HIV status of the participant, the three most recent partners in the preceding six months, and information on sexual behavior with those partners. A detailed description of the study design and also the questionnaire is supplied elsewhere 15 , 18 Our chief determinant of interest, dating place (e.g., the name of a pub, park, club, or the name of a site) was obtained for every partner, and categorised into online (websites), and offline (physical sites) dating places. To simplify the language of recognizing the partners per dating place, we refer to them as online or offline partners.
We used data from a cross-sectional study focusing on spread of STI via sexual networks 15 Between July 2008 and August 2009 MSM were recruited from the STI outpatient clinic of the Public Health Service of Amsterdam, the Netherlands. Men were eligible for participation if they reported sexual contact with men during the six months preceding the STI consultation, they were at least 18years old, and might understand written Dutch or English. People could participate more than once, if following visits to the practice were related to a possible new STI episode. Participants were regularly screened for STI/HIV according to the standard procedures of the STI outpatient clinic 15 , 17 The study was accepted by the medical ethics committee of the Academic Medical Center of Amsterdam (MEC 07/181), and written informed consent was obtained from each participant. Included in this evaluation were guys who reported sexual contact with at least one casual partner dated online as well one casual partner dated offline.
With increased acquaintance in sexual partnerships, for example by concordant ethnicity, age, lifestyle, HIV status, and raising sex frequency, the likelihood for UAI increase as well 14 - 16 We compared the occurrence of UAI in online got casual partnerships to that in offline got casual partnerships among MSM who reported both online and offline casual partners in the preceding six months. Free fuck book closest to Coburg, VIC, Australia. We hypothesised that MSM who date sex partners both online and offline, report more UAI with the casual partners they date on the internet, and that this effect is partly explained through better knowledge of partner features, including HIV status.
A meta-evaluation in 2006 found limited evidence that getting a sex partner online raises the risk of unprotected anal intercourse (UAI) 3 Many previous studies compared men with online partners to guys with offline partners. Free Fuck Book Near Me Epping Victoria. Nonetheless, men favoring online dating might differ in a variety of unmeasured respects from men preferring offline dating, leading to incomparable behavioural profiles. A more recent meta-analysis contained several studies examining MSM with both online and also offline acquired sex partners and found evidence for an association between UAI and internet partners, which may indicate a mediating effect of more info on partners, (including perceived HIV status) on UAI 13
Men who have sex with men (MSM) often make use of the Web to locate sex partners. Coburg, VIC free fuck book. Several studies have shown that MSM are prone to engage in unprotected anal intercourse with sex partners they meet through the Internet (online) than with partners they meet at social venues (offline) 1 - 3 This indicates that guys who get partners online may be at a higher risk for sexually transmitted infections (STI) and HIV 4 - 6 Although higher rates of UAI are reported with online partners, the danger of HIV transmission also depends upon accurate knowledge of one's own and the sex partners' HIV status 7 - 10
Five hundred seventy-seven guys (351 HIV negative, 153 HIV positive, and 73 HIV-unaware) reported UAI in 26% of 878 on-line, and 23% of 903 offline casual partnerships. The crude OR of online dating for UAI was 1.36 (95 % CI 1.03-1.81). HIV-positive men were more likely to report UAI than HIV negative men (49% vs. 28% of partnerships). Fixed for demographic features, online dating had no important effect on UAI among HIV-negative and HIV status-unaware guys, but HIV positive men were more likely to have UAI with on-line partners (aOR = 1.65 95 % CI 1.05-2.57). After correction for associate and partnership features the effect of online/offline dating on UAI among HIV positive MSM was reduced and no longer critical.
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