Pharmacie française en ligne: Acheter des antibiotiques sans ordonnance en ligne prix bas et Livraison rapide.
AIDS CARE (November 2004), VOL. 16, NO. 8, pp. 1036 Á/1047
Substance use and high-risk sex among menwho have sex with men: a national onlinestudy in the USA
S. HIRSHFIELD,1 R. H. REMIEN,2 M. HUMBERSTONE,1I
1Medical and Health Research Association of New York City, Inc. & 2HIV Center for Clinical andBehavioral Studies, New York State Psychiatric Institute and Columbia University, New York, USA
This paper describes drug and sexual risk behaviors during a six-month period in 2001 of
2,916 gay and bisexual men who were recruited online. Bivariate and multivariate analysesexamined correlates of unprotected anal intercourse (UAI). Drug and alcohol use were also examinedby US region. UAI was associated with using alcohol or drugs, including poppers, crystalmethamphetamine, cocaine, marijuana and Viagra before or during sex. Meeting sex partners bothonline and offline and having multiple sex partners were also predictive of UAI. Significant regionaldifferences were seen in the prevalence of drug use and alcohol use. Findings are discussed in relation tothe need to integrate messages about the relationship between drug use and sexual behavior into HIVprevention programs.
A resurgence in HIV transmission among men who have sex with men (MSM) is cause forserious concern as the number of newly diagnosed HIV infections among MSM has increased17% since 1999 (CDC, 2003). MSM have a considerably higher HIV prevalence than theoverall population, and studies have reported continual increases in unprotected analintercourse (UAI) since the mid-1990s (CDC, 1999; Chen et al., 2002; Ekstrand et al.,1999; Wolitski et al., 2001). Having multiple sex partners (CDC, 2002; Erbelding et al., 2003)and using drugs and alcohol (CDC, 2002; Colfax et al., 2001; Mansergh et al., 2001) continueto be associated with UAI; however, drugs of abuse and ways to meet partners have bothexpanded. Emerging drugs of abuse include crystal methamphetamine (crystal meth) andViagra, and the Internet has become an important new venue to meet sex partners.
Among MSM, drugs may be used within a sexual context (Stall & Purcell, 2000). Men
who begin having sex with men while on drugs may continue to use drugs during sexualexperiences (‘party and play’), and certain drugs such as nitrite inhalants (poppers), ecstasy
Address for correspondence: Sabina Hirshfield, PhD, Medical & Health Research Association of New York City,
Inc., 40 Worth Street, Suite 720, New York, NY 10013, USA. Tel: '/1 (212) 285 0220 x115; Fax: '/1 (212) 385 0565;E-mail: email@example.com
ISSN 0954-0121 print/ISSN 1360-0451 online/04/081036-12 # Taylor & Francis Ltd
SUBSTANCE USE AND HIGH-RISK SEX AMONG MEN
and crystal meth may be used specifically to enhance sexual experiences. The use of clubdrugs such as ecstasy, Gamma Hydroxy Butyrate (GHB), ketamine and crystal meth has beenassociated with high-risk sexual behaviors (Colfax et al., 2001; Lewis & Ross, 1995; Manserghet al., 2001; Mattison et al., 2001; Romanelli et al., 2003). Furthermore, the misuse of Viagra,alone and in combination with other substances (Chu et al., 2003; Colfax et al., 2001; Kimet al., 2002; Sherr et al., 2000), has been linked with unsafe sex (Mattison et al ., 2001; Woodyet al ., 1999).
We had the unique opportunity to study non-injection drug use and high-risk sexual
behavior among MSM on a national level. The majority of research on HIV and risk behaviorhas been conducted in small geographic areas or within cities where HIV is endemic (Leigh &Stall, 1993). However, there may be differing levels and correlates of risk, such as substanceuse, across geographic regions (Leigh & Stall, 1993), contributing to or resulting in changingepidemic trends. The aim of this study was to learn more about the association betweensubstance use and unprotected sex among MSM recruited online.
We conducted an anonymous, cross-sectional Internet study, inquiring about sexual anddrug-using behaviors among MSM between June and December 2001. The banner linking tothe survey was posted online between June 3 and July 24, 2002. Overall, 2,284 individualsclicked on the banner and exited the survey without answering any questions; 3,697 clickedon the banner and answered the survey. A total of 2,949 questionnaires were complete enoughfor statistical analysis (79% completion rate): 2,934 by men (18 of whom were exclusivelyheterosexual), ten by women and five by transgendered individuals. Analysis was limited tothe 2,916 men who reported sex with other men or who self-identified as gay or bisexual.
The online survey included information on demographics (age group, race/ethnicity,
education, income and residence) and assessment of risk behaviors, such as type of sexualcontact (anal, oral, vaginal */with and without condoms), knowledge of partners’ HIV status,type of illicit drug use, frequency of alcohol consumption, whether drugs or alcohol were usedbefore or during sex, how sex partners were met, and HIV testing. No personally identifyinginformation was collected, e.g. only the first three digits of the zip code and year of birth wereobtained. Links to STD/HIV prevention and treatment websites and mental health hotlinesappeared at the end of the survey. Survey questions were adapted from questionnaires used bythe investigators in previous studies.
Study participation was limited to those 18 and older, and all participants clicked on an
Descriptive statistics, bivariate and multivariate analyses, and factor analyses were
conducted using SPSS 11.5 for Windows (SPSS, 2001). Bivariate categorical data relation-ships were evaluated using x2 and odds ratios, and were simultaneously assessed by multiplelogistic regression models. Factor analysis was conducted for data reduction purposes for theeight drug variables, poppers, crystal meth, GHB, ketamine, ecstasy, cocaine, marijuana andViagra. The scree plot (Cattell, 1966) of eigenvalues suggested a two-factor solution, in which
Viagra was found to act as a stand-alone, additional variable. We performed several obliquerotations (using Direct Oblimin rotation) on maximum likelihood extraction solutions,specifying three-factor and then two-factor models with Viagra included in both. The findingssuggested that Viagra should not be included in the preferred two-factor model since it didnot load on either factor. The two-factor model fit the data substantially better than the three-factor model, provided better interpretability of factor loadings and was more parsimonious.
This model accounted for 50% of the common variance. The factors were accordingly labeledDrug Factor 1 (poppers, crystal meth, cocaine, marijuana) and Drug Factor 2 (ecstasy, GHB,ketamine).
In this cross-sectional study, respondents were asked how many sex partners they had duringtwo distinct three-month periods. Respondents could only choose one response from a pull-down menu for each time period. Answer choices were none, one, 2 Á/5, 6 Á/10, 11 Á/20, 21 Á/50and 51 or higher. This variable was collapsed for the entire six-month period; men whoreported no partners or one were grouped into the first category. Men who reported 2 Á/5partners were grouped into the second category; those who reported six partners or more weregrouped into the third category. In the bivariate analyses the second and third categories weremerged for ease of analysis and considered as multiple sex partners. Regarding unprotectedsex, respondents were asked about insertive and receptive sex without a condom. The UAIvariable represents men who reported any unprotected receptive and/or insertive analintercourse.
We did not ask if people had ever been tested, but rather were they tested during the
study period or had they ever tested positive. A large proportion of the sample had not beentested during the six-month study period; however, most (95%) reported that they had nevertested HIV-positive. Thus, for the analyses in this paper, HIV serostatus was divided into twogroups: those who reported testing HIV-positive (at some point) and those who testednegative during the study or who were not tested but never tested positive (HIV-positiveversus HIV-negative/unknown).
Demographic and behavioral characteristics
Analysis was limited to men who completed the survey and reported sex with other men orwho self-identified as gay or bisexual. Participants resided in all 50 states, roughly inproportion to the population of each state. Less than 1% resided in Guam, Puerto Rico and afew locations outside the US. The sample was predominately white (see Table 1). Nearly halfof the sample was between 18 and 29 years of age, with a range of 18 to 60 years or older.
Most reported up to $40,000 income and the majority reported at least some collegeeducation or more. Most men (80%) reported having sex only with men, while 20% reportedhaving sex with both men and women. Overall, 8% of the sample reported testing HIV-positive. The HIV prevalence by age group (which included men who were not tested duringthe study in the denominator) was 2% for 18 Á/24, 6% for 25 Á/29, 12% for 30 Á/39, 10% for40 Á/49 and 13% for 50 or older.
The number of lifetime sex partners ranged from 0 to over 1,000, with about one-quarter
of the participants reporting more than 100 lifetime partners (see Table 2). The majority(80%) reported more than one sex partner (multiple sex partners) during the six-month study
SUBSTANCE USE AND HIGH-RISK SEX AMONG MEN
Table 1. Demographic characteristics of men who have sex with men recruited online N 0/2,916
(NY, NJ, CT, PA, MA, RI, NH, ME, VT)South Atlantic
(DE, DC, MD, VA, WV, NC, SC, GA, FL)North Central
(IN, MI, IA, WI, MN, SD, ND, IL, MO, KS, NE)South Central
(AL, TN, MS, KY, OH, LA, AR, OK, TX)Mountain
period. Forty-five per cent of the overall sample reported any illicit drug use, with over a thirdreporting drinking until drunk at least 1 Á/3 days per week on average. About half reporteddrinking alcohol before or during sex. Injection drug use was extremely low ( B/1%).
Approximately 68% of those reporting drug use reported drugs before or during sex. Most(91%) used drugs from Drug Factor 1 before or during sex, with less than one-third usingdrugs from Drug Factor 2 before or during sex.
The drug use data were analyzed by six US regions, North East (NE), South Atlantic (SA),North Central (NC), South Central (SC), Mountain (MTN) and Pacific (PAC). We wereable to ascertain which state (and therefore which region) the respondent was from, based onthe first three digits of their zip codes. There were significant regional differences among those
Table 2. Behavioral characteristics of men who have sex with men recruited online
Overall drug use, past 6 months (n 0/2,741)
Drunk at least 1 Á/3 days per week (n 0/2,870)
Unprotected anal intercourse, past 6 months
$Drug Factor 1: poppers, crystal meth, cocaine, marijuana; $$Drug Factor 2: Ecstasy, GHB, ketamine; %alcoholuse before or during sex defined as sometimes or on most occasions.
reporting poppers, crystal meth, cocaine or GHB before or during sex, and drinking untildrunk at least 1 Á/3 days per week on average (see Table 3). There were no regional differencesin reporting of alcohol use before sex. ANOVA and the Bonferroni method were used for eachvariable to determine whether there was a mean difference in the percentage of reporting ofthese variables among and between each regional pair. Crystal meth use was most frequentlyreported in the SC, MTN and PAC regions, compared to the NE (SC mean difference 0/0.07,p B/0.001; MTN mean difference 0/0.07, p B/0.01; PAC mean difference 0/0.07, p B/0.001)and NC regions (SC mean difference 0.05, p B/0.01; MTN mean difference 0.06, p B/0.05;PAC mean difference 0.06, p B/0.01). There was a 7% reporting difference of cocaine usebetween the SC and NC regions (SC mean difference 0.07, p B/0.001). Respondents in theNC and SC regions were significantly more likely to report drinking until drunk several days aweek on average compared to the PAC region (NC mean difference 0.09, p B/0.05; SC meandifference 0.09, p B/0.05). There were no mean differences found by region for poppers orGHB.
SUBSTANCE USE AND HIGH-RISK SEX AMONG MEN
Table 3. Regional variation by drug and alcohol use
Note . ANOVA test F -statistic used.
Categories are not mutually exclusive.
Correlates of unprotected anal intercourse
In the bivariate analyses (see Table 4), significant correlates of UAI included being youngerthan 50, having less than a college degree, earning less than $40,000, being HIV-positive,using drugs from Drug Factors 1 and 2 before or during sex, using Viagra before or duringsex, drinking until drunk at least 1 Á/3 days per week on average, drinking alcohol before/during sex, meeting sex partners both online and offline, and having 2 Á/5 or 6 or more sexpartners during the study. Race was not significantly associated with UAI. By individual drugsin Drug Factors 1 and 2, men who reported UAI, compared to those who did not, weresignificantly more likely to report poppers (OR 3.2, 95% CI 2.5 Á/3.9, p B/0.001), crystal meth(OR 3.7, 95% CI 2.5 Á/5.6, p B/0.001), cocaine (OR 2.7, 95% CI 1.9 Á/3.8, p B/0.001),marijuana (OR 1.6, 95% CI 1.4 Á/1.9, p B/0.001), ecstasy (OR 2.4, 95% CI 1.8 Á/3.1,p B/0.001), GHB (OR 11.0, 95% CI 4.8 Á/25.4, p B/0.001) and ketamine (OR 2.6, 95% CI1.6 Á/4.1, p B/0.001).
To ensure that men with no sex partners during the study did not bias the overall findings
of the multivariate analysis, we ran the analysis with ‘no sex partners’ combined with ‘1 sexpartner’ (as the reference group), and then re-ran the analysis excluding men with ‘no sexpartners’. Findings were virtually identical, thus we kept the ‘no sex partners’ group in theanalysis. Additionally, since the variable, drinking until drunk at least 1 Á/3 days per week, washighly correlated with alcohol use before/during sex, we excluded the former from themultivariate analysis.
In the multivariate analysis (Table 4), the strongest predictors of unprotected anal
intercourse were having less than a college degree, using drugs before/during sex from DrugFactor 1, using Viagra, drinking alcohol before/during sex, meeting sex partners both onlineand offline and having multiple sex partners. Compared to men who reported less than twosex partners, men who reported 2 Á/5 sex partners were not more likely to report UAI,although men reporting six or more partners were. Drug Factor 2, age, income and HIVstatus were not predictive of UAI in the multivariate analysis.
Table 4. Bivariate and multivariate analyses: correlates of unprotected anal intercourse (UAI)
OR 0/odds ratio; CI 0/confidence interval; UAI 0/receptive or insertive unprotected anal intercourse.
Drug Factor 1: poppers, crystal methamphetamine, cocaine, marijuana; Drug Factor 2: ecstasy, GHB, ketamine.
Multivariate model adjusted for age, education, income, HIV status, Drug Factors 1 and 2, Viagra, alcohol before or during sex, how partners were met, and number of sexpartners in the past 6 months.
SUBSTANCE USE AND HIGH-RISK SEX AMONG MEN
In an analysis of drug use by HIV status, HIV-positive men were significantly more likely toreport using two or more drugs before or during sex than HIV-negative/unknown men (OR2.1, 95% CI 1.5 Á/2.9, p B/0.001), but there were no differences with the use of only one drugbefore or during sex. We used ANOVA to further investigate differing levels of drug useby UAI. The number of drugs used significantly affected the risk of UAI F (2, 2735) 0/52.59,p B/0.001. A trend analysis indicated that the data were well fit by a linear model (F 0/105.15,p B/0.001). The more drugs a respondent reported, the more likely he was to engage in UAI.
In order to assess the potential for HIV transmission, we compared the HIV status of the
participants to that of their partners. Among HIV-positive men with multiple sex partnerswho reported UAI (n 0/123), 46% reported UAI with HIV negative/unknown partners only,42% reported UAI with positive and negative/unknown partners and 12% reported UAI withpositive partners only.
This anonymous Internet survey provided important new information on the types of drugscurrently being used by MSM, by region and in the context of sexual behavior. Relatively highprevalence rates of drug and alcohol use, UAI and multiple sex partners were reported.
Overall, men who reported poppers, crystal meth, cocaine, marijuana, Viagra or alcohol usebefore or during sex were significantly more likely to report unprotected anal intercourse.
Also, men with less education, who met sex partners both online and offline and who reportedhaving six or more sex partners during the six-month study period were significantly morelikely to report UAI.
Main findings from this study indicate that drugs from Drug Factor 1 (poppers, crystal
meth, cocaine, marijuana) and Viagra are associated with UAI and are consistent with otherstudies of MSM, where poppers, crystal meth and Viagra have been associated with high-risksexual behavior (Colfax et al., 2001; Mattison et al., 2001; Molitor et al., 1998; Woody et al.,1999); cocaine and marijuana have also been associated with crystal meth use (Rotheram-Borus, 1999). It is possible that the drugs in Drug Factor 2 (ecstasy, GHB, ketamine) werenot predictive of UAI because they were less likely to be used before or during sex. Anotherlarge national study had similar findings (Colfax et al., 2004).
Regional findings from this study indicate that the highest prevalence of crystal meth use
was found in the western regions, where it has historically been most prevalent (Sullivan et al.,1998; Thiede et al., 2003). According to a recent national report (NIDA, 2003), indicators ofmethamphetamine use remained highest in West Coast areas and parts of the Southwest.
Crystal meth abuse is spreading to major cities such as Atlanta, Chicago, Detroit and St.
Louis. Relatively low indicators of crystal meth abuse were found in East Coast and Mid-Atlantic areas. Findings from our survey may not necessarily be representative of theseregions; however, the differing regional levels of reporting of crystal meth and cocaine may besignifying changes in drugs of abuse (Leigh & Stall, 1993). Additionally, it is possible thatstate and local agencies may have already missed an opportunity for targeted drugintervention and/or prevention in the North East, as reports of crystal meth use in MSMappear to be on the rise (Newsday, 2004 ; Reuters, 2004).
Nearly half of the sample reported drinking alcohol before or during sex, and this
behavior was associated with unprotected sex. Alcohol use and sexual risk behavior is acontroversial topic with mixed findings. However, a recent review of event-level alcoholstudies (Weinhardt, 2000) indicated that, more often than not, alcohol use was associated
with high-risk sexual behavior. Additionally, a recent event-level study (Colfax et al., 2004)examining drug and alcohol use before sex among HIV-negative MSM found that heavy useof alcohol, use of poppers, amphetamines and cocaine before or during sex were significantlyassociated with increased risk of engaging in UAI with a serodiscordant partner. Thesefindings complement our main findings. Additionally, the risk of reporting UAI in our studyincreased as the number of drugs used increased.
A review of research on substance use indicates that MSM who report drug use are more
likely to use multiple drugs, at once or sequentially, and use particular drugs such as poppersand amphetamines, compared to heterosexual men (Stall & Purcell, 2000; Stall & Wiley,1988). In a longitudinal study of HIV-negative MSM non-injecting drug users, consistentabuse of poppers and amphetamines was linked to later HIV seroconversion (Chesney et al.,1998). Thus, substance use and its relationship to high-risk sexual behavior among MSM is ofparticular concern, as drugs and alcohol may help men to avoid feelings of anxiety associatedwith same-sex behavior and self-awareness of HIV risk (McKirnan et al., 1996; McKirnanet al., 2001), and certain drugs such as poppers, MDMA and crystal meth may be usedspecifically to enhance sexual experiences (Lewis & Ross, 1995).
There has been an apparent cultural shift since the introduction of highly active
antiretroviral therapy (HAART), as studies report reduced concerns about contracting HIV(among HIV-negative MSM) and about transmitting it among HIV-positive MSM (Chenet al., 2002; Katz et al., 2002; Rietmeijer et al., 2003). Complacency about safer sex amongboth HIV-positive and HIV-negative men, coupled with an increase in UAI, may be partiallyrelated to changed attitudes towards HIV because of the antiretroviral medications nowavailable (Dilley et al., 2003; Elford et al., 2000; Halkitis et al., 2003; Remien, 1998; Vanable etal., 2000).
The majority of HIV-positive men with multiple sex partners reported unprotected sex
with HIV-negative or status unknown partners, which signifies the continued risk of spreadingHIV and other sexually transmitted diseases (STDs). Other studies of HIV-positive menreport a range of serodiscordant or potentially discordant sex, from 21% to 49% (Chen et al.,2003; Halkitis & Parsons, 2003; Whittington et al., 2002).
There are important limitations in our study. First, the survey was only posted on one
general interest, gay-oriented site, thus we do not know how the findings would differ (if at all)if men were recruited from sites whose sole purpose is to facilitate meeting sex partners.
Second, minority MSM were under-represented in the sample. Third, we could neither verifythe reliability of respondents’ identity nor their responses since the survey was anonymous.
Finally, it is not possible to determine whether the population that participated in thisInternet-based survey is representative of the population of MSM using the Internet, of MSMin general or of MSM with HIV, since the MSM population has never been enumerated.
Nevertheless, Internet research is an efficient and inexpensive way to reach large samples ofhigh-risk groups. Our preliminary data suggest that white, non-Hispanic MSM wereunintentionally over-sampled, as those who have computer skills and access to participatein online sex surveys tend to be younger, wealthier, educated white males (Binik et al., 1999;Lenhart et al., 2003; Toomey & Rothenberg, 2000).
In spite of these limitations, there are important benefits of conducting Internet-based
research and using technical and non-technical mechanisms to minimize non-valid data. Forexample, we asked age and year of birth in different sections of the survey to ensure reliabilityof responses. In order to minimize the likelihood of participants completing multiple surveys,the study banner was rotated through the online chat-rooms at the end of a string of paidadvertisements approximately every 20 minutes, and it was not technically possible for
SUBSTANCE USE AND HIGH-RISK SEX AMONG MEN
participants to bookmark the questionnaire. Also, there were no monetary incentives tocomplete the survey.
Regarding validity of responses, higher reporting of risk behaviors has been found on
computer versus other survey methods. A recent survey found that injection drug users weremore likely to report high-risk sexual and drug-using behaviors on computer assisted self-interviewing (CASI) than in face-to-face interviews (Newman et al ., 2002). Another recentsurvey comparing online and offline samples found that the online sample of HIV-negativemen and never-tested men were significantly more likely to report serodiscordant UAI thanmen surveyed offline (Elford et al., 2004).
Studies conducted over the past 20 years have found associations between substance
abuse treatment and a reduction in HIV risk behaviors (Metzger & Navaline, 2003). Primaryand secondary substance abuse treatment among MSM has been successful at reducing druguse and other high-risk behaviors, as treatment can affect decisions about sexual behavioruninfluenced by drugs and alcohol (Shoptaw & Frosch, 2000). There is clearly a need for theintegration of sexual behaviors and substance use in HIV prevention efforts. By identifyingspecific drug use and other high-risk behavior(s) associated with HIV infection, we can informonline education, prevention and/or harm reduction. Our study findings indicate a strongcontinuing need for HIV information and education. Ongoing drug surveillance is necessaryto document new trends in substance use patterns (or emerging substances) among MSM(Stall et al., 2001). We need to fully understand the complexities of current sexual and drugtrends in order to create multifaceted interventions.
Findings from this study raise serious public health concerns. There is a need to better
understand changing behaviors in this population of MSM that may be associated with HIVtransmission in order to develop effective prevention and education strategies. Since onlineresearch is such a young field, research, ethical and technical issues are in need of refinement.
However, there are opportunities to collect information on high-risk and traditionally hard-to-reach populations. More research is needed to disentangle the intersections of drug use,unprotected sex, serodiscordant sex and the use of the Internet to meet sex partners.
Data analysis and manuscript preparation were funded in part through CDC ContractNumber 200-97-0621, Task 33 to RTI International, and Subcontract Number 10-46U-6900from RTI to Medical and Health Research Association of New York City, Inc. The content ofthis publication does not necessarily reflect the views or policies of the Department of Healthand Human Services, nor does mention of trade names, commercial products, ororganizations imply endorsement by the US Government.
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Frederic Boudrenghien Key Account Manager at Belgacom Key Account Manager at Belgacom July 2012 - Present (1 year 8 months) For assigned list of key accounts, I plan and implement sales and business plan in order to reach salesobjectives, especially in terms of development of new business, customer loyalty and market share. I establish and translate to key partners a sales approach based o
Disciplinary Hearing Present: Prosecutor - Gordon Garnett (BHRC Chairman) Enquiry Panel: Barry Delaney (BHRC Vice Chairman), John Wright (BHRC Steward), Robert Thompson (Regional Steward) Parties: Mark Eltringham (Trainer), Anthony Fettah (Owner), Craig Nuttall (witness for the defence) On Sunday 29th July 2012 at Musselburgh a blood sample was obtained from the horse Cutcha