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  1. whatsapp gay open group | VK
  2. Introduction
  3. Why gay men are better at negotiating sex than straight guys

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  4. Manu, 24 years. Chakkarpur, Gurgaon, Haryana Pure bottom I am pure bottom. Matthew Tharrett. Matthew Tharrett is a writer, filmmaker, and above all else, a Britney fan. He once shared a milkshake with Selena Gomez. NewNowNext about archive. About Logo Press. Participants eligible for inclusion in our analysis were men in NHBS-MSM1 who had at least one main or casual male sex partner within the 12 months before the interview [ 16 ].

    Further restriction according to complete information on male partner number and the covariates included in our analyses resulted in the final dataset. Respondents' demographic and risk-behavior characteristics were summarized descriptively. The number of participants reporting a casual partner in the 12 months before the interview was tallied, along with the median numbers of casual and main male partners. We computed the median casual partner number separately for those who did and did not have a main male partner.

    The median numbers of participants' casual male partners were computed and compared across the above demographic and risk factors using Wilcoxon and Kruskal-Wallis tests. To better understand the factors that were independently associated with higher casual partner count, we fit several multiple linear regression models with the number of casual partners in the 12 months before the interview as the outcome.

    Poisson regression and proportional-odds ordinal logistic regression models were also considered, but the models' goodness-of-fit assumptions were not upheld. We first fit a model that adjusted for the main effects of the following demographic factors and risk behaviors possibly associated with partner number: We then fit interaction models that individually considered each of our four pre-specified interactions. Least-squares means were calculated for the levels of each factor of interest by plugging the pertinent value for the factor into the estimated model, along with values for the other model terms according to their marginal distribution in the sample observed-margins weighting.

    Since the casual partner counts were log-transformed, these means were then back-transformed by exponentiation and the resulting values provided estimates of the geometric mean partner count at each factor level for an 'average' person in the study sample. Since the data were found to be approximately log-normally distributed, the geometric mean partner count approximates the median count [ 18 ]. Exponentiated model coefficients estimate the geometric mean ratio approximately the median ratio , a measure of the average relative change in casual partner number associated with each level of a factor compared to the referent group.

    The model fit and assumptions were evaluated.

    Model fit was evaluated by examining the proportion of variability explained by the model r 2. Model assumptions pertaining to data normality, equality of variance, and the presence of outliers were evaluated via normal probability plots, residual plots, and Cook's distance, respectively. Distribution of characteristics and model results for the number of casual male partners in the prior 12 months.

    Introduction

    Sexual identity. Participants had a median of 3 casual male partners first quartile: The results of a main-effects multivariable model of the number of casual male partners are presented in Table 1. The estimated adjusted median number of casual male partners was 3. Men ages had an estimated median of 2. Participants who did not report a main male partner in the 12 months before the interview had an estimated 6. MSM who reported a male exchange-sex partner had an estimated median number of 8.

    A dose-response in casual male partners was seen among chat room users, ranging from non-users, who reported an estimated median 2. Model-based estimated median number of casual male partners in the prior twelve months, by age and chat room usage, among 11, men who have sex with men who participated in the National HIV Behavioral Surveillance System, 15 US cities, Among those who used chat rooms most frequently several times a day , the difference was even greater; those between ages 18 and 24 had an estimated median of 4.

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    Why gay men are better at negotiating sex than straight guys

    An examination of the interaction between HIV status and age group revealed heterogeneity in the association between being infected with the virus and an increase in the number of casual male partners. Modeling of the interaction between sexual identity and reporting a female sex partner in the 12 months before the interview provided further insight. Homosexual men who had a female sex partner had an estimated median of 4.

    Model fits were good; the main-effects model had an r 2 of 0. Examinations of normal probability and residual plots, as well as of Cook's distance indicated that model assumptions were upheld. Our data provide additional information about this factor for Hispanic MSM, for whom there has been less focus on individual risk behaviors relative to white MSM.

    Several possible explanations for this may exist. One is that black MSM tend to be less aware of their true serostatus, and thus self-reported HIV status may appear to have a weaker relationship with casual partner number because of misclassification. This higher misclassification of self-reported HIV status may 'smooth out' any differences in casual partner number reported among black MSM.

    Alternatively, transmission among black MSM may be more related to other risk-behaviors or mechanisms than to having more casual partners, compared to white and Hispanic MSM. Although young men ages 18 to 24 years tended to have fewer casual male partners overall, we found that it was important to interpret this observation in the context of chat room use.

    There has been a growing interest in the association between using the internet to meet MSM partners and the practice of higher-risk sexual behavior [ 20 , 21 ]. While the direction of causality is still unclear, Mustanski has reported in a prospective diary study of MSM that it was those who practiced riskier sex UAI who tended to find their partners online, rather than the reverse [ 22 ].


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    As frequency of chat room use increased, so did the reported number of partners, with greater increases reported by older MSM. While the magnitude of partner counts among frequent users is striking, it is important to be aware of how many respondents had such levels of usage. About a fifth of MSM used chat rooms several times a week or more, a level of use at which a highly significant difference in casual partner count was seen between younger and older MSM.

    Thus we see that age disparities in casual partner count among MSM are concentrated in a minority that uses gay or bisexual chat rooms heavily. There are several possible hypotheses for the observed differences of chat room usage by age. It may be that younger men use MSM chat rooms more for general socialization, such that high usage is less associated with a propensity to find partners, compared to older MSM who may use chat rooms more exclusively for meeting partners. Alternatively, there may be a generational difference in nomenclature, where younger MSM associate the term "chat rooms" with a different array of services such as social networking websites than do older men.

    Whatever the reasons underlying this age difference, it may be more important to target interventions towards older MSM who frequently use chat rooms. Having had a male exchange sex partner was the factor associated with the largest increase in casual male partners. Exchange sex has long known to be a correlate of HIV risk behaviors [ 23 , 24 ] and specifically of an increased numbers of casual partners [ 25 , 26 ].

    We observed, as have others [ 27 ], that MSM reporting a main male partner within the previous year had on average substantially fewer casual male partners.