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). Local Cougars nearest Bateau Bay New South Wales. UAI was significantly more likely if more sex acts had happened in the venture (OR = 16.29 95 % CI 7.07-37.52 for >10 sex acts within the partnership compared to just one sex act). Local Cougars Near Me Dulwich Hill New South Wales. Other variables significantly associated with UAI were group sex within the venture, and sex-related multiple drug use within venture.
In multivariate model 3 (Tables 4 and 5 ), additionally including variables concerning sexual behavior in the venture (sex-related multiple drug use, sex frequency and partner type), the separate effect of online dating location on UAI became somewhat stronger (though not critical) 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 critical) for HIV-oblivious guys (aOR = 2.55 95 % CI 1.11-5.86) (Table 5 ).
In univariate analysis, UAI was significantly more prone to happen in on-line than in offline partnerships (OR = 1.36 95 % CI 1.03-1.81) (Table 4 ). Local cougars nearest New South Wales, Australia. The self-perceived HIV status of the participant was strongly associated with UAI (OR = 11.70 95 % CI 7.40-18.45). The effect 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 distinct reference categories, one for each HIV status. Among HIV-positive men, UAI was more common in online when compared with offline partnerships (OR = 1.61 95 % CI 1.03-2.50). Among HIV negative guys no association was evident between UAI and internet partnerships (OR = 1.07 95 % CI 0.71-1.62). Among HIV-oblivious men, UAI was more common in online in comparison to offline partnerships, though not statistically significant (OR = 1.65 95 % CI 0.79-3.44).
Features 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 online 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 understood (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 on-line partners more frequently understood 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 internet partners (50.9% vs. 41.3%; P 0.001). Bateau Bay NSW Australia local cougars. Sex-associated substance use, alcohol use, and group sex were less frequently reported with internet partners.
To be able to analyze the possible mediating effect of more info on partners (including perceived HIV status) on UAI, we developed three variant 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 venture characteristics (age difference, ethnic concordance, lifestyle concordance, and HIV concordance). In version 3, we adjusted additionally for venture sexual risk behavior (i.e., sex-associated drug use and sex frequency) and partnership kind (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 new six-class variable. For clarity, the effects of online/offline dating on UAI are also presented separately for HIV negative, HIV positive, and HIV-oblivious guys. We performed a sensitivity analysis confined to partnerships in which only one sexual contact occurred. Statistical significance was defined as P 0.05. Local cougars closest to Bateau Bay, Australia. No adjustments for multiple comparisons were made, in order not to miss potentially significant associations. As a rather big number of statistical tests were done and reported, this approach does lead to a heightened risk of one or more false positive organizations. Analyses were done using the statistical programme STATA, version 13 (STATA Intercooled, College Station, TX, USA).
Before the analyses 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. of male sex partners in preceding 6months), and some were supposed to be on the causal pathway between the primary exposure of interest and results (age difference between participant and partner; ethnic concordance; concordance in life styles; HIV concordance; venture type; sex frequency within venture; group sex with partner; sex-related 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). We compared features of participants, partners, and venture sexual conduct by on-line or offline venture, and calculated P values based 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 examine the association between dating place (online versus offline) and UAI. Likelihood ratio tests were used to evaluate the value of a variable in a model.
As a way to explore possible disclosure of HIV status we also asked the participant whether the casual sex partner understood the HIV status of the participant, with the response alternatives: (1) no, (2) perhaps, (3) yes. Sexual behavior with each partner was dichotomised as: (1) no anal intercourse or simply protected 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, fashionable, punk/skinhead, rubber/lycra, gothic, bear, jeans, skater, or, if not one of these characteristics were related, other. Concordant lifestyle was categorised as: (1) concordant; (2) discordant. Accidental partner type 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're HIV infected?', with five response options: (1) I 'm certainly not HIV-contaminated; (2) I believe that I am not HIV-infected; (3) I do not know; (4) I believe I may be HIV-infected; (5) I know for sure that I am HIV-contaminated. 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 with all the question: 'Do you know whether this partner is HIV-infected?' with similar response alternatives as previously. Perceived concordance in HIV status within ventures was categorised as; (1) concordant; (2) discordant; (3) unknown. The last group represents all partnerships where the participant did not know 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 survey throughout their trip to the STI outpatient clinic while waiting for preliminary test results after their consultation with a nurse or doctor. 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 behaviour with those partners. A thorough description of the study design and the questionnaire is provided elsewhere 15 , 18 Our main determinant of interest, dating place (e.g., the name of a bar, park, club, or the name of a website) was obtained for every partner, and categorised into online (websites), and offline (physical sites) dating locations. To simplify the language of recognizing the partners per dating location, 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. Individuals could participate more than once, if subsequent visits to the clinic were related to a potential 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 approved 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 men who reported sexual contact with at least one casual partner dated online as well one casual partner dated offline.
With increased familiarity 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 acquired casual partnerships to that in offline obtained casual partnerships among MSM who reported both on-line and offline casual partners in the preceding six months. Local cougars nearby Bateau Bay NSW 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 increases the risk of unprotected anal intercourse (UAI) 3 Many previous studies compared men with online partners to men with offline partners. Local Cougars Near Me Mosman New South Wales. Yet, guys preferring online dating might differ in a variety of unmeasured respects from guys preferring offline dating, leading to incomparable behavioural profiles. A more recent meta-analysis contained several studies analyzing MSM with both online and offline acquired sex partners and found evidence for an association between UAI and internet partners, which would imply a mediating effect of more info on partners, (including perceived HIV status) on UAI 13
Men who have sex with men (MSM) frequently use the Net to locate sex partners. Bateau Bay, NSW local cougars. Several research have shown that MSM are more inclined to engage in unprotected anal intercourse with sex partners they meet through the Internet (on-line) than with partners they meet at social venues (offline) 1 - 3 This suggests that guys who acquire 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 on-line partners, the danger of HIV transmission also depends on exact 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-oblivious) reported UAI in 26% of 878 online, 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). Corrected 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 associates (aOR = 1.65 95 % CI 1.05-2.57). After correction for partner and partnership characteristics the effect of online/offline dating on UAI among HIV positive MSM was reduced and no longer critical.
Believe it or not believe it, I didn't come out of this experiment feeling awful about myself---simply smarter about the way gay men (or maybe men in general) area way too much emphasis on foolish features like beards and ballcaps (hint: that is why you're all still cranky and single). And actually, I do not think having long hair itself is the huge hang-up; it's what my hair implies. Local cougars near me Bateau Bay. Having long hair (especially for a black man) means you're likely a bitchy dramatic queen that nobody needs to date. Even if the premise isn't that extreme, the inherent anxiety is you spent too much time on your look and that is not manly." That's frustrating, of course, since stereotypical masculinity requires only as much work---we just don't think of it that way. I recall chatting with this scruffy, pretty muscular man with tattoos and torso hair and an Instagram full of masc pics; after we got to speaking, he revealed his fixation with Beyonc and said yasss!" every other paragraph. But no matter---his image is butch, so his dating life is constantly full.