RESEARCH ARTICLE Prevalence and patterns of illicit drug use in people living with HIV in Spain: A cross- sectional study Maria Jose Fuster-RuizdeApodaca ID1☯*, Vanessa Castro-Granell2,3☯*, Noé Garin4,5,6, Ana Laguı́a7, Ángeles Jaén ID8, Carlos Iniesta ID1,9, Santiago Cenoz10, Marı́a José Galindo1,11 1 Spanish Interdisciplinary Aids Society (Sociedad Española Interdisciplinaria del Sida, SEISIDA), Madrid, a1111111111 Spain, 2 Doctoral Programme in Pharmacy, Granada University, Granada, Spain, 3 Department of a1111111111 Pharmacy, Hospital Marina Baixa, Villajoyosa, Alicante, Spain, 4 Department of Pharmacy, Hospital Santa a1111111111 Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain, 5 Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de salud Mental (CIBERSAM), Madrid, Spain, 6 School of Health a1111111111 Science Blanquerna, Universitat Ramon Llull, Barcelona, Spain, 7 Department of Social and Organizational a1111111111 Psychology, Facultad de Psicologı́a, Universidad Nacional de Educación a Distancia (UNED), Madrid, Spain, 8 Research Unit, Research Foundation MútuaTerrassa, Universitat de Barcelona, Barcelona, Spain, 9 Centro Nacional de Epidemiologı́a, Instituto de Salud Carlos III, Madrid, Spain, 10 Medical Department, ViiV Healthcare, Tres Cantos, Madrid, Spain, 11 Department of Infectious Diseases, Hospital Clı́nico Universitario, Valencia, Spain OPEN ACCESS ☯ These authors contributed equally to this work. Citation: Fuster-RuizdeApodaca MJ, Castro-Granell * gerencia@seisida.net (MJFRA); vanemcg@hotmail.com (VCG) V, Garin N, Laguı́a A, Jaén Á, Iniesta C, et al. (2019) Prevalence and patterns of illicit drug use in people living with HIV in Spain: A cross-sectional study. PLoS ONE 14(6): e0211252. https://doi.org/ Abstract 10.1371/journal.pone.0211252 This study assessed the prevalence and patterns of drug use among people living with HIV Editor: Henry F. Raymond, Rutgers School of (PLHIV) in Spain. We conducted an observational cross-sectional study including 1401 Public Health, UNITED STATES PLHIV. Data were collected through 33 sites across Spain using an online computer-assis- Received: January 9, 2019 ted self-administered interview. The survey measured use of illicit drugs and other sub- Accepted: June 3, 2019 stances, treatment adherence and health-related variables. To analyse patterns of drug use Published: June 17, 2019 we performed cluster analysis in two stages. The most frequently consumed substances were: alcohol (86.7%), tobacco (55.0%), illicit drugs (49.5%), other substances (27.1%). Copyright: © 2019 Fuster-RuizdeApodaca et al. This is an open access article distributed under the The most prevalent illicit drugs used were cannabis (73.8%), cocaine powder (53.9%), and terms of the Creative Commons Attribution poppers (45.4%). Results found four clusters of PLHIV who used drugs. Two of them were License, which permits unrestricted use, composed mainly of heterosexuals (HTX): Cluster 1 (n = 172) presented the lowest polydrug distribution, and reproduction in any medium, provided the original author and source are use and they were mainly users of cannabis, and Cluster 2 (n = 84) grouped mostly men credited. who used mainly heroin and cocaine; which had the highest percentage of people who inject Data Availability Statement: Data are available drugs and presented the lowest level of treatment adherence (79.8±14.2; p < .0001). The from doi: 10.6084/m9.figshare.8059784. other two clusters were composed mainly of men who have sex with men (MSM), who were Funding: This study was funded by ViiV Healthcare mostly users of recreational drugs. Cluster 3 (n = 285) reported moderate consumption, (grant nº: SEISIDA 001/2016). SC is Medical both regarding frequency and diversity of drugs used, while Cluster 4 (n = 153) was charac- Manager at ViiV Healthcare. ViiV Healthcare was terized by the highest drug polyconsumption (7.4±2.2; p < .0001), and 4 grouped MSM who the promoter of the study but they did not play any injected recreational drugs, and who reported the highest frequency of use of drugs in a sex- role in data collection and analysis. ual context (2.6±0.8; p < .0001) and rates of sexually transmitted infections (1.8±1.1; p < Competing interests: This study was funded by .01). This is the largest multi-centre cross-sectional study assessing the current prevalence ViiV Healthcare (www.viivhealthcare.com), and ViiV Healthcare was involved in the study design and and patterns of drug use among PLHIV in Spain. The highest prevalence of drug use was PLOS ONE | https://doi.org/10.1371/journal.pone.0211252 June 17, 2019 1 / 18 Illicit drug use in people living with HIV in Spain preparation of the manuscript, without influencing found among MSM, although HTX who used heroin and cocaine (Cluster 2) had the most the data collection and analysis or the decision to problems with adherence to HIV treatment and the worst health status. publish. All listed authors meet the criteria for authorship set forth by the International Committee of Medical Journal Editors. All authors had full access to the data and are responsible for the veracity and completeness of the reported data. SC is employed full time in ViiV Healthcare. MJFRA, AJ, CI and MJG are members of the Spanish Introduction Interdisciplinary Aids Society (SEISIDA) Executive Board. SEISIDA has received grants from MSD, The human immunodeficiency virus (HIV) continues to be a major public health challenge in ViiV, Janssen, and Gilead. MJFRA has provided Spain, with 145,000 people living with HIV (PLHIV) in 2016 [1]. Among the new HIV cases consultancy services to ViiV, Gilead, and Janssen, that year, sexual transmission accounted for 79.6% of them, 53.1% of whom corresponded to and have received payments for lectures or men who have sex with men (MSM) and 26.5% to heterosexuals (HTX), while only 3.6% were educational presentations from MSD, Gilead, and attributed to people who inject drugs (PWID) [1]. Regarding prevalence, HTX and PWID ViiV. MJG has provided consultancy services to were still the largest subgroups of PLHIV, 32.5%, and 30.9% respectively, although their rela- ViiV, Abbie, MSD, Gilead, and Janssen, and has received payments for travelling to meetings from tive weight continued to decrease gradually in favour of MSM [2]. Both the effectiveness of the MSD and for lectures or educational presentations highly active antiretroviral therapy (ART) and the high rate of access to treatment − nine out from MSD, Janssen, Gilead, and ViiV. CI has of ten PLHIV in Spain − have led to a substantial mortality reduction over the last decades [3]. received payments for consultancy services to Despite the increased life expectancy for PLHIV, certain personal aspects may have an MSD. important impact on their health care and health-related quality of life. One of these aspects is substance use. A review on recreational drug use in PLHIV in Europe showed consumption prevalence above 50% in most studies, especially in those focusing on MSM. Prevalence ranged from 5.5 to 82.4% [4]. The ASTRA study found that 51% of 2,248 MSM PLHIV had used recre- ational drugs in the previous three months in the UK [5]. In Spain, the prevalence of illicit drug use in PLHIV remains unclear. The EMIS Survey, addressed to MSM only, found higher consumption of illicit drugs in those PLHIV using many different recall periods [6]. A recent study focusing on MSM with HIV in Madrid, Spain, found that 59% of them had used illicit drugs during the previous year [7]. A similar prevalence over the same period has been reported in the area of Catalonia, Spain [8]. With regard to individuals under treatment, a study focusing on PLHIV attending one hospital found a prevalence of use of 44.2% in the last 12 months [9]. Studies to date have reported higher drug consumption rates in PLHIV compared with the general population [10]. There is, however, considerable variability regarding the frequency of use of the different drugs in the literature [4]. The EMIS study showed that poppers (56.2%), cannabis (41.9%), cocaine (38.2%), sildenafil (32.9%), ecstasy (24.2%) and GHB/GBL (18.9%) were the substances most frequently consumed over the past 12 months by MSM living with HIV in Spain [11]. Some studies found that polydrug use, the use of various drugs over a pre- defined period, was about 50% in some cases [9]. Studies have failed to identify clear patterns of drug consumption because the list of drugs to be assessed varies significantly with time and across countries or social groups [9]. However, the literature has highlighted two important patterns of drug use [12]. The first one, ‘chemsex’, covers sexualized drug use and is practised mainly by MSM [12,13]. In the UK, the most com- mon ‘chemsex’ drugs are crystal methamphetamine, GHB/GBL, mephedrone, and to a lesser extent, ketamine [14,15]. In Spain, according to the U-SEX GESIDA-9416 study, cocaine was the most frequent drug used in a sexual context, while crystal methamphetamine was the least frequent [7]. Also, studies suggested that the practice of injecting recreational drugs at sex par- ties − ‘slamming or slamsex’ − might be increasing in MSM [16]. The second pattern would involve ‘party drugs’, such as cocaine, GHB, ketamine and amphetamines [12]. In addition to these patterns, there are still PLHIV using traditional intravenous drugs, such as heroin or crack cocaine [6]. The literature on trends of drug use suggested that either PLOS ONE | https://doi.org/10.1371/journal.pone.0211252 June 17, 2019 2 / 18 Illicit drug use in people living with HIV in Spain fewer people are taking these drugs nowadays or users are switching to new drugs [17,18]. In Spain, both the prevalence of use of heroin and its intravenous use decreased markedly from the nineties to 2006 thanks to opioid substitution therapy, syringe exchange programmes and replacement by other non-intravenous administration routes [19]. To our knowledge, although the percentage of PLHIV using these drugs nowadays in Spain may be low, there are no studies on the current prevalence and patterns of use of these substances. Substance use may have a negative impact on HIV care and prevention. Some literature showed a negative effect of illicit drug use on HIV disease [20]; on transmission risk behaviour leading to the acquisition of sexually transmitted infections (STIs) [7,11,16], low adherence to ART [21,22], and interactions with ART [23,24]. The first step to tackle this situation is to understand the current use of these drugs. Thus, this study aimed to assess the prevalence of drug use and to explore the patterns of consumption among PLHIV in Spain. Materials and methods Study design This observational, cross-sectional study consisted of an electronic interview focusing on illicit drug use in PLHIV. The study was performed in Spain, including data from 12 Spanish Auton- omous Communities between November 2016 and May 2017. The interview was offered to adults over 18 years old living with HIV under ART for at least one year. Participants with severe psychiatric or cognitive disorders were considered not eligible. We used a community-based participatory research paradigm, involving members of the population under study in all research phases [25,26]. Also, a group of experts from several social and health-care fields guided the research and participated in its different stages. The Ethics Committee of the Hospital Clı́nico de Valencia approved the research protocol. All procedures of the study followed the Helsinki Declaration principles, as well as the guide- lines for good clinical practice. Procedures The study was coordinated by the Spanish AIDS society (SEISIDA), which contacted profes- sionals from 36 institutions across the country. A total of 33 sites agreed to collaborate in the study, 12 hospitals and 21 Non-Governmental Organizations (NGOs), which used conve- nience sampling for participants’ inclusion. Of the total sample, 51.7% of the individuals were recruited in NGOs. The collaborating professionals included participants during their clinical visits or while attending to various services. Additionally, a few NGOs recruited participants by e-mail. The goals of the study were explained to potential participants, requesting their participation and obtaining their signed informed consent. An online computer-assisted self-administered inter- view (CASI) designed with Qualtrics was administered to participants with a tablet after pro- viding appropriate instructions. Professionals were available to clarify any doubts or difficulties during questionnaire completion. The average time needed to complete the ques- tionnaire was 40 minutes. We calculated an initial sample of 1,500 PLHIV distributed among the different participat- ing sites across Spain. We distributed the sample in order to: (1) maintain the distribution of the burden of HIV in the main Spanish regions, and (2) have an extensive geographical repre- sentation. S1 Table shows the number and percentage of surveys collected by the different Spanish regions and its HIV incidence in the last five years [1]. A total of 1,401 PLHIV agreed to participate and finished the online survey (data are available from 10.6084/m9.figshare. 8059784). The final response rate was 93.4%, and it varied across sites ranging from 82 to PLOS ONE | https://doi.org/10.1371/journal.pone.0211252 June 17, 2019 3 / 18 Illicit drug use in people living with HIV in Spain 100%. There were lower rates in hospitals compared with NGOs. Main reasons for refusing to participate were lack of time, survey length, visual impairment or lack of skills to use tablets. Participants were compensated with 15 euros. Measures We designed the survey according to the results of an earlier qualitative study and previous evidence in the literature, following the methodological recommendations on the construction of scales and wording of items [27,28]. The research team and the group of expert consultants collaborated in the design process. The questionnaire was previously piloted and refined using a sample of 61 PLHIV who used drugs. The survey contained the following variables: Use of illicit drugs and other substances. The survey included a list of 18 illicit drugs (Fig 1), their frequency of use and their route of administration. Besides, it included questions asking participants about the frequency of alcohol use and smoking status. The survey also incorporated items related to the consumption of other substances or medicines: erection enhancers; methadone, morphine, and other opioids; anabolic steroids; sedatives or hypnotics, antidepressants. The frequency of use for all substances except tobacco was rated on a 6-point scale ranging from ‘sometimes in the last year’ to ‘daily’. Tobacco use was measured by the amount of cigarettes smoked per day. We also included items related to the drug consumption context: (a) use of drugs previous to HIV diagnosis (yes/no); (b) main reasons for using drugs (8 reasons were listed and one open question); and (c) frequency of use of drugs in a sexual context. Two items were rated on a 4-point scale; these items were merged in the analyses due to the good correlation observed (r = .59). Treatment adherence and other health-related variables. We used the Questionnaire to Evaluate the Adherence to HIV Therapy (CEAT-VIH) [29]. The 2.0 version of the scale is comprised of 17 items rated on a 5-point scale. Negative items were reverse-coded. We calcu- lated a composite score, with higher scores indicating higher treatment adherence. The scale showed an adequate reliability in our study (Cronbach’s α = .78). Moreover, the survey included the following questions related to participants’ health status: years living with HIV; CD4 cell count; viral load; and STIs in the last year. Finally, the questionnaire collected several socio-demographic characteristics: age; gender; sexual orientation; level of education; employment status; financial resources; and city of residence. Data analysis Frequencies, proportions, ranges, means, SDs and cross-tabulations were applied for descrip- tive analysis. To analyse the diverse typologies of PLHIV, we performed a two-step cluster analysis using demographics, health-related variables, types of drugs used, and route of con- sumption. This analysis had been suggested as appropriate in clustering large data sets with mixed attributes and allows the creation of models of clusters based on both categorical and continuous variables [30,31]. Schwarz’s Bayesian criteria determined the number of clusters. This method is known to be one of the most useful and objective selection criteria because it avoids the arbitrariness in traditional clustering techniques [32,33]. Because the solution of the cluster analysis could not be unique, the analysis was sometimes run changing the order of the cases [32]. The research team discussed the final solution according to its conceptual meaning. Once the groups were established, differences in variables under study were assessed using Pearson’s chi square statistic for categorical variables and one-way analysis of variance PLOS ONE | https://doi.org/10.1371/journal.pone.0211252 June 17, 2019 4 / 18 Illicit drug use in people living with HIV in Spain Fig 1. Prevalence and frequency of use of illicit drugs among PLHIV using drugs. N = 694. https://doi.org/10.1371/journal.pone.0211252.g001 (ANOVA) for continuous variables. Tukey’s HSD test was performed to compare differences among groups. Before starting the analysis, we examined the assumptions of multivariate analysis. We found that the assumptions of independence and absence of multicollinearity of the variables were fulfilled. However, some continuous variables did not meet the normality criteria of the PLOS ONE | https://doi.org/10.1371/journal.pone.0211252 June 17, 2019 5 / 18 Illicit drug use in people living with HIV in Spain distribution. Nevertheless, the literature suggests that two-step cluster analysis is robust about the violations of distribution and independence criteria [32]. Furthermore, ANOVA is also robust about the violations of normality and homoscedasticity criteria [34]. Nevertheless, we checked the assessed differences with a non-parametric technique (Kruskal−Wallis). The analyses were performed using the SPSS v.22 software. Results Participant characteristics The study population consisted of 1,401 participants, with a mean age of 45.38 years (SD = 10.19). Table 1 shows a summary of the socio-demographic characteristics of the Table 1. Characteristics of the participants (n = 1,401). Variables n (%) Gender Cis-men 1,100 (78.5) Cis-women 280 (20) Transgender 21 (1.5) Sexual orientation Heterosexual 580 (41.4) Homosexual 713 (50.9) Bisexual 61 (4.4) Others 28 (2) Prefer not to answer 19 (1.4) Mode of transmission Sexual intercourse 946 (67.5) Sharing needles 272 (19.4) Various practices concur 141 (10.1) Other 42 (3) Educational level No studies 57 (4.1) Primary 383 (27.4) Secondary 484 (34.6) University degree 439 (31.4) Other 37 (2.6) Work situation Working 685 (48.9) Unemployed 257 (18.3) Retired or occupational disability 325 (23.2) Other 134 (9.6) Monthly incomes None 185 (13.2) � 1,000 € 539 (38.5) 1,000−1,500 € 405 (28.9) 1,500−2,000 € 104 (7.4) > 2,000 € 168 (12) Years since diagnosis, mean ±SD 14.1±9.6 Years taking ART, mean ±SD 11.6±8.4 Age, mean ±SD 45.3±10.1 Note: Data provided in percentages, except where specified. ART: antiretroviral therapy. SD: standard deviation. https://doi.org/10.1371/journal.pone.0211252.t001 PLOS ONE | https://doi.org/10.1371/journal.pone.0211252 June 17, 2019 6 / 18 Illicit drug use in people living with HIV in Spain participants. The survey did not collect gender identity in those participants who identified themselves as transgender. Taking into account this limitation, we considered and labelled self-defined male and female participants as cisgender throughout the manuscript. Use of drugs and other substances Alcohol was the substance most frequently consumed (86.7%). Ten per cent of the participants consumed it daily. More than half of the individuals were smokers (55%). Most of them smoked daily (84%), with an average of 13.1 cigarettes per day (SD = 8.5). A total of 49.5% (n = 694) of participants stated to have used illicit drugs in the previous 12 months. The proportion of PLHIV who used illicit drugs was significantly higher in partici- pants recruited from NGOs (54.9%) than from hospitals (43.8%), χ2 = 17.27, p < .0001. Over- all, the vast majority of these participants had consumed illicit drugs before the HIV diagnosis (84.7%). The most prevalent illicit drugs were cannabis, cocaine and poppers. Cannabis was also the most regularly consumed substance (Fig 1). Almost a quarter of PLHIV who used illicit drugs consumed only cannabis (24.9%). The average number of different drugs used per participant in the last 12 months was 3.3 (SD = 0.7; range: 1−14). Injected and rectal routes of administra- tion accounted for 6.8% and 3.2% of the cases, respectively (Fig 2). Heroin, cocaine, and mephedrone were the most frequent injected drugs; mephedrone and methamphetamine the most intrarectally administered. Fig 2. Frequencies of consumption routes used for the different types of illicit drugs. N = 694. https://doi.org/10.1371/journal.pone.0211252.g002 PLOS ONE | https://doi.org/10.1371/journal.pone.0211252 June 17, 2019 7 / 18 Illicit drug use in people living with HIV in Spain Fig 3. Percentage of PLHIV who used other medicines or substances. https://doi.org/10.1371/journal.pone.0211252.g003 The use of some types of illicit drugs differed between the two biggest cities in Spain (Madrid and Barcelona). Drugs that showed more differences between these cities were pop- pers, ecstasy and mephedrone. In this sense, consumption of mephedrone and poppers were higher in Madrid than in Barcelona (33.3% vs. 19.8%; χ2 = 7.78, p = .005 and, 68.5% vs. 56.9%; X2 = 4.75, p = .029, respectively). Conversely, consumption of ecstasy and ketamine were higher in Barcelona than in Madrid (37.1% vs. 27.2%; χ 2 = 3.73, p = .053 and, 22.8% vs. 13.0%; χ 2 = 5.35, p = .021, respectively). In addition to illicit drugs, 27.1% of the total sample (n = 379) consumed other substances. PLHIV who used illicit drugs consumed them more prevalently than PLHIV who did not use illicit drugs (37.0% vs. 17.3%, χ 2 = 69.40; p < .0001). The most frequent substance consumed both among the total sample, and among PLHIV who used illicit drugs were erection enhanc- ers (Fig 3). Patterns of use of illicit drugs The two-stage cluster analysis classified the participants into four groups. All the variables included in the analysis contributed significantly to the formation of the groups. Table 2 sum- marizes the consumers’ profiles in clusters according to socio-demographic characteristics and use of drugs and other medicines or substances. Tables 3 and 4 display detailed information and statistics. Two clusters were composed mostly of HTX: cluster 1 (CL1) represented about 25% of PLHIV who used illicit drugs and Cluster 2 (CL2) 12%. In these clusters, the mean age was about 50 years, and participants had been living with HIV for more than 20 years. The analysis classified most cisgender women in CL1. More than half of the participants in both clusters had completed compulsory education only, and the majority had a monthly income of less than 1,000 €. A large proportion of individuals in these clusters were retired or disabled. Shar- ing needles was a frequent cause of HIV acquisition in both clusters, and was the main cause in CL2. Patterns of drug use varied between these clusters. Individuals in CL1 consumed can- nabis principally, followed by cocaine powder in 23% of cases. The analysis classified users of PLOS ONE | https://doi.org/10.1371/journal.pone.0211252 June 17, 2019 8 / 18 Illicit drug use in people living with HIV in Spain Table 2. Cluster’s profile according to demographics, health-related data, use of drugs and other medicines. Characteristics C1 (24.8%, n = 172) C2 (12.1%, n = 84) C3 (41.1%, n = 285) C4 (22.0%, n = 153) Gender Mostly cis-men but the highest Mainly cis-men but some cis- Mainly cis-men but Only cis-men percentage of cis-women among women and transgender some transgender clusters Age ~ 50 years ~ 50 years ~ 40 years < 40 years Sexual orientation Mainly HTX Mainly HTX Mainly MSM Mainly MSM Educational level Low level The lowest level High level The highest level Work situation Most retired or unemployed Most retired and the highest Most working Most working, the lowest percentage percentage of unemployed of retired Economic status Low The lowest Middle−high The highest Mode of HIV Mainly injection Mainly (the highest) injection Mainly sexual Mainly sexual transmission Time living with HIV More than 20 years More than 20 years Near to 10 years Less than 10 years Type of drugs used Mainly users of cannabis and some of Mainly users of cannabis, heroin Mainly users of The highest percentage of using most them cocaine powder and cocaine cannabis, cocaine and types of drugs except heroin poppers Polyconsumption Low Medium Medium High Routes of Mainly smoked, some sniffed Mainly smoked and sniffed, Mainly smoked, sniffed, All routes. Some PWID. Anal route consumption highest % of PWID inhaled and around 1/3 oral Other medicines or Most sedatives and around 1/3 Mainly sedatives, methadone or Mainly erection Most erection enhancers (the highest substances antidepressants. Some methadone and other opioids. Half of them enhancers and near to 1/ %), good few sedatives. The highest erection enhancers antidepressants 3 sedatives % of anabolic users Reasons for Mainly relaxing or avoiding worries Mainly relaxing or avoiding Mainly to enjoy and Mainly to enjoy and sexual purposes consumption worries and negative feelings sexual purposes N = 694. HTX: heterosexual; MSM: men who have sex with other men. https://doi.org/10.1371/journal.pone.0211252.t002 heroin in CL2, 32% of whom declared having used the injection route. Moreover, near to 60% were also taking methadone and half of them antidepressants. Polydrug use in CL2 group was higher than in CL1. The main reasons in both clusters to use drugs were ‘relaxing and avoiding worries’, 47.1% and 63.1% in CL1 and CL2, respectively, and ‘removing negative feelings’, 35.4% and 44.1% in CL1 and CL2, respectively. According to their described profile, CL1 was labelled ‘HTX mainly users of cannabis’ and CL2 ‘HTX users of heroin and cocaine’. On the other hand, the other two clusters grouped MSM who had acquired HIV principally through sexual intercourse. Cluster 3 (CL3) represented about 42% and Cluster 4 (CL4) 22% of PLHIV using drugs. They were younger, had a higher level of education, higher socio-eco- nomic status, and a more recent HIV diagnosis compared with HTX clusters (CL1 and CL2). MSM in CL4 were the youngest participants and the ones with the most recent HIV diagnosis. Both clusters differed in their pattern of drug use. CL3 presented a moderate consumption of cannabis, poppers, and cocaine, while CL4 showed high rates of substance use for the most types of drugs and the highest polydrug use. Furthermore, almost 10% of PLHIV in CL4 used the injection route of consumption and 14.4% of them the anal route. Individuals in CL3 and CL4 clusters reported a higher use of erection enhancers’ than in HTX clusters (CL1 and CL2). The highest percentage was found among PLHIV in CL4 (92.2%). The main reasons to use drugs in both clusters (CL3 and CL4) were ‘to enjoy the substances’ (54.7% and 81.1% for CL3 and CL4, respectively) and ‘sexual purposes’ (38.9% and 61.4%, respectively). According to their described profile, CL3 was labelled ‘MSM with moderate drug use’, and CL4 ‘MSM high polydrug users’. PLOS ONE | https://doi.org/10.1371/journal.pone.0211252 June 17, 2019 9 / 18 Illicit drug use in people living with HIV in Spain Table 3. Cluster’s profile according to socio-demographic and health data. Variable C1 C2 C3 C PLHIV who did not use drugs Contrast statistica (n = 172) (n = 84) (n = 285) (n = 153) (n = 707) Genderb χ2 = 186.97 Cis-men 61 78.6 96.1 100 71 Cis-women 38.4 19 0 0 28 Transgender 0.6 2.4 3.9 0 1 Sexual orientationb χ2 = 547.10 Heterosexual 86.6 85.7 6 0 48.4 Homosexual 2.9 3.6 87 94.8 44.1 Bisexual 6.4 6 4.6 3.3 3.8 Others 1.7 1.2 2.1 2 2.1 Prefer not to answer 2.3 3.6 0.4 0 1 Mode of transmission b χ2 = 458.65 Sexual intercourse 31.4 16.7 87 92.2 69.2 Sharing needles 57.6 75 0 0 15.6 Various practices concur 9.9 6 10.2 6.5 11.3 Other 1.2 2.4 2.8 1.3 4 Educational levelb χ2 = 273.76 No studies 8.7 14.5 1.1 0 3.8 Primary 50.6 61.4 11.6 8.5 28.1 Secondary 31.4 13.3 40.4 29.4 36.6 University degree 7 8.4 43.5 58.2 29.3 Other 2.3 2.4 3.5 3.9 2.1 Work situationb χ2 = 198.77 Working 23.8 13.1 69.1 69.3 46.7 Unemployed 22.1 34.5 16.1 20.9 15.8 Retired or occupational disability 41.3 41.7 8.4 3.9 26.7 Other 12.8 10.7 6.3 5.9 10.7 Monthly incomesb χ2 = 148.76 None 14.5 21.4 10.5 12.4 13.2 � 1,000 € 61 60.7 23.5 17.6 40.9 1,000−1,500 € 15.1 9.5 41.8 39.2 27.2 1,500−2,000 € 3.5 4.8 8.8 13.1 6.9 > 2,000 € 5.8 3.6 15.4 17.6 11.9 Inmunological status χ2 = 28.23 3 < 200 CD4 mm 9.6 7.2 3.5 1.7 6.6 200−400 CD4 mm3 14.4 17.4 7.1 6 15.4 > 400 CD4 mm3 76 75.4 89.4 92.2 78 Undetectable viral load 93.3 87.8 94.4 97.4 93 χ2 = 9.02; p = .061 Years since diagnosisb,1, mean ±SD 22.5±8.3 23.2±6.1 9.2±7.3 7.0±5.1 17.7±9.5 F = 114.36 Years taking ART2, mean ±SD 18.0±7.2 18.2±6.8 7.8±6.8 5.6±4.5 12.4±8.4 F = 82.09; p = .000 ART adherence3, mean±SD 84.1±10.5 79.8±14.3 87.4±8.7 86.3±9.1 88.3±8.5 F = 20.83 Ageb,4, mean ±SD 50.9±6.4 49.5±5.5 41.1±9.4 36.8±8.3 47.1±10.3 F = 73.20 (Continued ) PLOS ONE | https://doi.org/10.1371/journal.pone.0211252 June 17, 2019 10 / 18 Illicit drug use in people living with HIV in Spain Table 3. (Continued) Variable C1 C2 C3 C PLHIV who did not use drugs Contrast statistica (n = 172) (n = 84) (n = 285) (n = 153) (n = 707) STIs� 5 (%, (m±SD) 10.5 (1.3±0.5) 13.1 (1.4±1.2) 30.9 (1.4±0.7) 60.8 (1.81±1.1) 16 (1.4±0.8) F = 3.71; p < .01 Note: Data provided in percentages, except where specified. ART: antiretroviral therapy. STIs: sexually transmitted infections suffered in the last year (� percentage of people in each cluster who had suffered any STI in the last year and mean of number of STIs suffered in the last year). a All differences were significant at p < .0001 except when it is specified in the table. b Variables included in two-stage cluster analysis. 1 HSD Tukey results found differences between C1 and C2, C3, C4 and PLHIV who did not use illicit drugs (p < .0001); differences between C3 and C4 were marginally different (p = .069) 2 Differences were found between C1, C2, C3, C4 and PLHIV who did not use illicit drugs (p < .0001), and between C3 and C4 (p < .05) 3 Differences were found between C1 and: C2 (p = .005),C3 (p = .002) and PLHIV who did not use illicit drugs (p < .0001), and between C2 and C3, C4 and PLHIV who did not use illicit drugs (p < .0001) 4 There were differences between all the groups (p < .0001) except between C1 and C2, and C2 and PLHIV who did not use illicit drugs 5 Significant differences were found between C4 and both C3 and PLHIV who did not use illicit drugs. https://doi.org/10.1371/journal.pone.0211252.t003 Almost 40% of the individuals in CL3 and about 60% in CL4 reported using drugs in a sex- ual context, while only around 3% in each HTX cluster used it. The frequency of use of drugs in a sexual context also differed among clusters, and was higher in CL4 than in CL3 (Table 4). Differences in ART adherence and other health-related variables according to the profile of use of drugs HTX ‘users of heroin and cocaine’ (CL2) showed the lowest score in ART adherence, followed by HTX ‘mainly users of cannabis’ (CL1). MSM ‘high polydrug users’ (CL4) reported the high- est percentage of STIs. MSM clusters of PLHIV who used illicit drugs (CL3 and CL4) reported the highest lymphocytes CD4 mm3 count. The lowest percentage of patients with undetectable viral load was found in CL2 (Table 3). Discussion The present research revealed the prevalence of illicit drug use as well as the particular patterns of consumption among PLHIV in Spain. The most frequently consumed substances among PLHIV in Spain, according to our results, were: alcohol (86.7%), tobacco (55.0%), illicit drugs (49.5%) and other substances (27.1%). The prevalence of last-year alcohol consumption among PLHIV was higher than that reported for the general Spanish population (77.6%), although daily consumption resulted in similar results [35]. The prevalence of active smoking was high compared with the general population (30.8%) [35]. Studies in other countries focus- ing on PLHIV have reported similar results to those we found [36,37]. Almost half of the participants in our study had used illicit drugs in the last 12 months, with cannabis, cocaine, and poppers being the most frequent ones. Cannabis and cocaine are also the most consumed drugs in the general population [35,38] but the prevalence found in our results was three times higher for cannabis and 13 times higher for cocaine than the respective figures reported by the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) in the general population [10]. As for studies focusing on PLHIV, the prevalence found in our study was slightly higher compared with the results by Garin et al. [9]. In addi- tion, the prevalence of cocaine use among MSM who consume drugs in our sample was higher than that found recently by González-Baeza et al. [7], but results were similar for most of the PLOS ONE | https://doi.org/10.1371/journal.pone.0211252 June 17, 2019 11 / 18 Illicit drug use in people living with HIV in Spain Table 4. Cluster’s profile according to the type and frequency of drugs used, routes of consumption and polyconsumption. C1 (n = 172) C2 (n = 84) C3 (n = 285) C4 (n = 153) Contrast statistica b,e Drugs % (mean±SD) Cannabis 86.6 (4.4±1.8) 78.6 (4.1±2.0) 63.9 (3.1±2.0) 75.2 (3.1±2.0) χ2 = 30.32��� (F = 16.66��� ) Cocaine (powder) 22.7 (1.6±0.9) 60.7 (2.5±1.6) 54.0 (1.6±0.9) 85.0 (1.9±1.1) χ2 = 128.49��� (F = 10.19��� ) Cocaine (base) 0 3.6 (2.7±1.6) 0 15.7 (2.1±0.8) χ2 = 75.45��� (F = .50, ns) Heroin 0 69 (2.3±1.7) 0.4 (1.0±0.0) 0.7 (1.0±0.0) χ2 = 441.50��� (F = .55, ns) Poppers 0 0 62.5 (1.8±1.2) 89.5 (2.2±1.3) χ2 = 366.59��� (F = 6.47� ) MDMA (crystal) 1.2 (1.0±0.0) 6 (1.8±1.7) 12.6 (1.0±0.2) 75.2 (1.4±0.7) χ2 = 314.70��� (F = 3.24� ) MDMA (pills) 0 16.7 (3.0±2.4) 11.9 (1.0±0.2) 72.5 (1.5±0.9) χ2 = 285.87��� (F = 16.99��� ) Speed 4.1 (1.1±0.3) 21.4 (2.2±1.6) 8.1 (1.04±0.2) 67.3 (1.3±0.7) χ2 = 249.55��� (F = 6.96��� ) Methamphetamine 0.6 (1.0±0.0) 2.4 (2.0±1.4) 3.9 (1.0±0.0) 43.8 (1.5±1.0) χ2 = 197.53��� (F = 1.17, ns) GHB 0 2.4 (1.0±0.0) 19.3 (1.1±0.4) 77.1 (1.7±1.0) χ2 = 305.12��� (F = 11.45��� ) Mephedrone 0 0 11.6 (1.0±0.3) 62.1 (1.6±0.9) χ2 = 260.60��� (F = 11.78�� ) Ketamine 0.6 (1.0±0.0) 4.8 (1.0±0.0) 3.9 (1.0±0.0) 45.8 (1.4±0.8) χ2 = 202.55��� (F = .97, ns) LSD 0 8.3 (1.3±0.7) 0.7(1.0±0.0) 9.8 (1.0±0.0) χ2 = 37.08��� (F = 1.24, ns) Opium 0 7.1 (1.8±2.0) 0 2 (1.0±0.0) χ2 = 28.95��� (F = .46, ns) Spice drugs 0 2.4 (1.5±0.7) 0.4 (1.0±0.0) 2 (1.0±0.0) χ2 = 6.77(ns) (F = 1.0, ns) Mushrooms 0 3.6 (1.0±0.0) 0 15.7 (1.0±0.0) χ2 = 75.45��� (—) Other hallucinogenic plants 0 8.3 (1.0±0.0) 0.4 (1.0±0) 2.6 (1.0±0.0) χ2 = 28.47��� (—) 2C-B nexus 0 1.2 (6.0±0) 0 1.3 (1.0±0.0) χ2 = 5.82(ns) (—) 1 Number of drugs used (mean±SD) 1.2±0.5 3.4±2.0 2.5±1.4 7.4±2.2 F = 461.06��� c,2 Use of drugs in sexual context% (mean±SD) 3.5 (1.7±1.2) 3.6 (2.0±1.0) 38.9 (1.8±0.7) 61.4 (2.6±0.7) F = 16.67��� d,e Routes of consumption % Smoke 85.5 89.3 65.6 82.4 χ2 = 37.55��� Sniff 21.5 52.4 62.5 95.4 χ2 = 185.79��� Oral 5.2 31 35.1 98 χ2 = 304.21��� Injection 1.2 32.1 1.1 9.8 χ2 = 111.20��� Anal 0 0 0 14.4 χ2 = 80.33��� Inhaled 0.6 6 41.4 62.7 χ2 = 183.15��� Other medicines or substances used Erection enhancers 19.4 18.8 62 92.2 χ2 = 89.86��� Methadone 19.4 59.4 0 0 χ2 = 113.99��� Morphine 3.2 9.4 0 1 χ2 = 11.84�� Other opioids 9.7 28.1 5.4 4.9 χ2 = 18.59��� Anabolic 0 0 2.2 18.6 χ2 = 24.87��� Sedatives 61.3 93.8 30.4 40.2 χ2 = 42.65��� Antidepressants 32.3 50 15.2 14.7 χ2 = 22.54��� a Measure of the importance of the categorical (χ2 = Pearson’s chi square) and continuous variables (one-way ANOVA) within each cluster. All χ2 differences were significant at p < .0001 except when it is specified in the table. (—) F was not calculated in drugs for which only one cluster had the variance calculated. b The frequency of consumption ranges from 1 to 6 (1: sometimes in the last 12 months; 2: once a month; 3: several times in a month; 4:once a week; 5: several times a week; 6: daily). c The frequency of the scale ranges from 1: sometimes, to 4: always. d The score of each route of consumption was calculated summing the use of the route in each drug. e Variables included in the two-step cluster analysis. � p < .05 �� p < .01 ��� p < .0001. 1 HSD Tukey results found differences between all the clusters except between C2 and C3. 2 HSD Tukey results found differences between CL4 and CL1 and CL3. https://doi.org/10.1371/journal.pone.0211252.t004 PLOS ONE | https://doi.org/10.1371/journal.pone.0211252 June 17, 2019 12 / 18 Illicit drug use in people living with HIV in Spain other substances, such as poppers or ketamine. At an international level, several studies have also highlighted the significant prevalence of illicit drug use in PLHIV across Europe. For example, our results were similar to those found by Daskalopoulou et al. [5] in the United Kingdom, although direct comparison is not possible since that study evaluated last-three- months consumption. Grabovak et al. [39] found a moderately higher prevalence of drug use in PLHIV in Austria but their analysis included sildenafil/tadalafil, categorized as ‘other sub- stances’ in our study. In contrast, our prevalence results were higher compared with other studies in France [40] or Scotland [37] although, again, differences in time frame make comparisons. Our study also found some differences in the pattern of drug use between the two largest cities in Spain (Madrid and Barcelona). Similar results were found in a study conducted in 2016 that collected data from 486 MSM in Spain, who had practised ‘chemsex’ in the previous 12 months [41]. Findings of the EMIS study showed that the prevalence of use of the different drugs varies substantially across cities, suggesting that drug use patterns appear to be culturally and socially determined [42]. The association of the city of residence with drug use could be influenced not only by psychological factors, but also by structural drivers such differences in drug availability and differences in national, regional, or local norms and cultures concerning drug use [42,43]. Regarding routes of consumption, we found that near to 7% of PLHIV who used illicit drugs were using the injection route. They represented 3.4% of the total sample. This percent- age is comparable to the HIV incidence results reported in Spain and the countries from the European Union and European Economic Area [1,44]. Regarding patterns of drug use, our results found four clusters of PLHIV who used drugs. Two of them were composed mostly of HTX and the other two principally of MSM, which resulted in being the most prevalent group of PLHIV who used illicit drugs. MSM were the youngest participants, had the most recent HIV diagnosis and the best socio-economic status. These socio-demographic and epidemiologically different characteristics between MSM and HTX living with HIV are concordant with those existing in the Spanish national HIV data about HIV prevalence and incidence [1,2,45]. MSM and HTX clusters of PLHIV who used illicit drugs found in the present study also differ in their reasons for using drugs. While HTX aimed at avoiding worries or negative feelings, MSM pointed to issues such as enjoying their use and sexual purposes. Regarding clusters of HTX who used illicit drugs, the largest one was composed of people who presented the lowest average of polydrug use and who were users of cannabis mainly fol- lowed by cocaine powder. More than a half of them were former PWID and nearly one-fifth of them were taking methadone in the period assessed by our study. Thus, they have given up or replaced the use of heroin (or other injected drugs). In addition, a small group of HTX was also found who were polydrug users and who showed the highest prevalence of heroin use and current injection route. Although the majority of PLHIV in this cluster acquired HIV infection through sharing needles, during the study period only near a third of them continued injecting drugs. Taking the previous results conjointly, we can conclude that according to previous liter- ature [19], both the use of heroin and its intravenous use have continued to decrease in Spain. In our study, PLHIV in CL2 (mainly users of heroin and cocaine) represented around 6% of the total sample and among them, 2% were PWID. Despite this decrease, it is essential to pay attention to these groups of people because we found they presented the lowest levels of adher- ence to treatment [20,21]. With this regard, PLHIV who were users of heroin and cocaine pre- sented the poorest biological markers of HIV infection. However, not only the impact of their use of drugs but also their socio-epidemiological profile could explain these results. The litera- ture shows that PLHIV who use illicit drugs are more likely to experience problematic PLOS ONE | https://doi.org/10.1371/journal.pone.0211252 June 17, 2019 13 / 18 Illicit drug use in people living with HIV in Spain adherence and that they have increased age-matched morbidity compared to those who do not use drugs [46,47]. A systematic review of interventions to improve adherence and virological outcomes among PLHIV who used drugs concluded that directly administered antiretroviral therapy (DAAT) obtained the most substantial evidence of efficacy but that it is labour-inten- sive and costly to implement [46]. The arrival of long-acting treatments could be an opportu- nity for DAAT in PLHIV who use illicit drugs. Nevertheless, DAAT should be complemented with other interventions that have shown efficacy, such as cognitive behavioural therapy, moti- vational interviewing and peer-driven interventions [46]. Besides interventions to promote adherence, pharmacokinetic drug interactions must be adequately addressed in people who use illicit drugs [47]. Among the MSM using drugs, there was a majority that reported moderate consumption, both regarding frequency and diversity of drugs used. However, there was another pattern of use in MSM, including younger patients with the highest frequency of illicit drug use and rele- vant polydrug consumption. Some of them used drugs intra-rectally (around 14%) and intra- venously (around 10%). PWID represented around 2% of the total MSM in our study. This percentage was lower than that found by González-Baeza et al. [7] (around 4%) and similar to the one found by Folch et al. [11] (1.4%). Prevalence of PWID in Folch et al. [11] was higher in the largest towns. Baeza et al. [7] conducted their study exclusively in MSM with HIV living in a large Spanish city (Madrid), where the use of recreational drugs and the practice of ‘slamsex’ seems to be higher than in smaller cities [11,18]. Regarding other countries, Pufall et al. [13] found that 10% of the MSM interviewed in UK practised slamming in the previous year. Although MSM clusters reported frequent use of drugs in a sexual context (32%) and high rates of STIs in the previous 12 months, the percentages were the highest in MSM polydrug users. These results are similar to those reported in the study of González-Baeza et al. [7]. Recent studies are highlighting the importance of the ‘chemsex’ phenomenon and its health consequences among those who practise it [13,48,49]. Thus it will be necessary to monitor the impact of drug use in the health and psycho-social sphere of MSM who use illicit drugs. It will also be necessary to implement coordinated and multi-dimensional strategies that reduce drug-related harm among them. Specific interventions could include: direct client service sup- port to manage or reduce the use of drugs, health promotion activities, peer education support, training healthcare providers and drug services about new recreational drugs and their role in sexual intercourse, services to address specific psychological and psychiatric problems in MSM who practice ‘chemsex’, advice about healthy leisure alternatives, harm-reduction services such as needle exchange, among others. [41,50,51]. Moreover, several study findings suggest that MSM who combine drugs with sex are more likely to engage in high-risk sexual practices when compared with MSM who do not combine drugs with sex [43]. Thus, it will be necessary to examine and increase the use of bio-medical risk reduction interventions such as STI test- ing, post-exposure and pre-exposure prophylaxis to reduce the potential negative conse- quences of ‘chemsex’ on public health [43]. Our study has several limitations. First, its cross-sectional nature does not allow causal rela- tionships to be established. Second, we did not use a probabilistic sampling, although the large sample size and extensive geographical data collection could mitigate this limitation. In this sense, the socio-demographic characteristics of our participants were concordant with Spanish epidemiological data for PLHIV [1]. Also, we aimed to provide a general overview of drug use, including different PLHIV subgroups in Spain. This may make difficult direct comparison with studies focusing on MSM only. However, the sample in our study involved a large pro- portion of MSM, similar to that found in other studies [7], and specific analysis and results are provided for this subgroup. Furthermore, we used a self-reported data collection method, and this could underestimate the prevalence of PLHIV using drugs because some people would not PLOS ONE | https://doi.org/10.1371/journal.pone.0211252 June 17, 2019 14 / 18 Illicit drug use in people living with HIV in Spain desire to reveal this information to their health-care providers. However, we tried to overcome this limitation through the anonymity of the survey and by balancing the data collection from hospitals and NGOs. Furthermore, another limitation was that we measured the use of sub- stances using single items. However, it allowed us to assess the use of several substances. More- over, other studies had concluded the utility of single screening questions to identify substance use [52]. Likewise, our survey asked about gender categories (men, women, transgender) con- sidering them as mutually exclusive. However, many transgender people identify as men or women, not as a third gender. Conclusions The present research is the largest multi-centre study assessing the current prevalence and pat- terns of drug use among PLHIV in Spain. Our results showed a relatively high prevalence of illicit drug use among the PLHIV in Spain. Prevalence of drug use in PLHIV was higher in MSM than in HTX. MSM were mostly users of recreational and most recent drugs. Most of them presented a moderate profile of drug consumption, although there was a specific sub- group of MSM with high polyconsumption, which was associated with a higher risk of STIs. HTX tend to use mainly cannabis, heroin or cocaine. Although the use of heroin and the injec- tion route of consumption have decreased among them, PLHIV who still used heroin and cocaine showed the most problems to adhere to HIV treatment and the worst health status. Future studies should monitor the evolution of the patterns of drug use, and the longitudinal impact of recreational drug use in their users’ health. Furthermore, it will be necessary to design strategies that provide adequate responses to the diverse problems associated with each pattern of drug use. Supporting information S1 Table. Percentage of surveys collected and percentage of HIV incidence in the different Spanish regions. (DOCX) Acknowledgments The authors thank the experts who participated in the research: Noé Garı́n, Percy Fernández, Fernando Caudevila, Antonio Alba, Diego Garcı́a, Victor Baceiredo, Jorge Garrido, and Juanse Hernández. We also thank the NGOs and hospitals that collaborated in the recruitment and data collection: ACCAVIH, Adhara, ACCAS, AMUVIH, Apoyo Positivo, AVACOS, BCN Checkpoint, CASDA, CALCSICOVA, Comité antisida de Burgos, Colectivo Lambda, Euskal- sida, Gais Positius, GTT, Imagina Más, No estamos solos, Stop Sida, Hospital Carlos Haya, Hospital Clı́nico Universitario de Valencia, Hospital Mutua Terrassa, Hospital Germans Trias i Pujol, Hospital del Mar, Hospital Miguel Servet, Hospital Gregorio Marañón, Hospital Alvaro Cunqueiro, Hospital La Paz, Hospital Son Llazer. Finally, the authors thank all the people who participated in this study. This article is part of the Doctoral Thesis of Vanessa Marı́a Castro Granell with the Doctoral Programme in Pharmacy, Granada University, Spain. Author Contributions Conceptualization: Maria Jose Fuster-RuizdeApodaca, Vanessa Castro-Granell, Noé Garin, Marı́a José Galindo. PLOS ONE | https://doi.org/10.1371/journal.pone.0211252 June 17, 2019 15 / 18 Illicit drug use in people living with HIV in Spain Data curation: Maria Jose Fuster-RuizdeApodaca, Vanessa Castro-Granell, Ana Laguı́a. Formal analysis: Maria Jose Fuster-RuizdeApodaca, Vanessa Castro-Granell. Funding acquisition: Maria Jose Fuster-RuizdeApodaca. Investigation: Maria Jose Fuster-RuizdeApodaca, Vanessa Castro-Granell, Noé Garin, Ana Laguı́a, Marı́a José Galindo. Methodology: Maria Jose Fuster-RuizdeApodaca, Vanessa Castro-Granell, Ángeles Jaén. Project administration: Maria Jose Fuster-RuizdeApodaca. Software: Ana Laguı́a. Supervision: Ángeles Jaén, Carlos Iniesta, Santiago Cenoz, Marı́a José Galindo. Writing – original draft: Maria Jose Fuster-RuizdeApodaca, Vanessa Castro-Granell, Noé Garin. Writing – review & editing: Maria Jose Fuster-RuizdeApodaca, Vanessa Castro-Granell, Noé Garin, Ana Laguı́a, Ángeles Jaén, Carlos Iniesta, Santiago Cenoz, Marı́a José Galindo. References 1. Dirección General de Salud Pública Calidad e Innovación. Vigilancia Epidemiológica del VIH y SIDA en España, actualización 30 de junio de 2017. Ministerio de Sanidad Servicios Sociales e Igualdad. 2016. Available from: https://www.msssi.gob.es/ciudadanos/enfLesiones/enfTransmisibles/sida/vigilancia/ InformeVIH_SIDA_2017_NOV2017.pdf. 2. Dirección General de Salud Pública Calidad e Innovación. Encuesta Hospitalaria de pacientes con infección por el VIH: Resultados 2016. Análisis de la evolución 2001–2016. Ministerio de Sanidad, Ser- vicios Sociales e Igualdad. 2017. Available from: https://www.msssi.gob.es/ciudadanos/enfLesiones/ enfTransmisibles/sida/vigilancia/InformeEncuestaHospitalaria2016DEF.pdf. 3. Joint United Nations Programme on HIV/AIDS(UNAIDS).UNAIDS Data 2017. Available from: http:// www.unaids.org/sites/default/files/media_asset/20170720_Data_book_2017_en.pdf. 4. Garin N, Velasco C, de Pourcq JT, Lopez B, Gutierrez MM, Haro JM, et al. Recreational drug use among individuals living with HIV in Europe: review of the prevalence, comparison with the general pop- ulation and HIV guidelines recommendations. Front Microbiol. 2015; 6: 690. https://doi.org/10.3389/ fmicb.2015.00690 PMID: 26236288 5. Daskalopoulou M, Rodger A, Phillips AN, Sherr L, Speakman A, Collins S, et al. Recreational drug use, polydrug use, and sexual behaviour in HIV-diagnosed men who have sex with men in the UK: results from the cross-sectional ASTRA study. Lancet HIV. 2014; 1: e22–31. https://doi.org/10.1016/S2352- 3018(14)70001-3 PMID: 26423813 6. The EMIS Network. EMIS 2010: the European men-who-have-sex-with-men internet survey. Findings from 38 countries. Stockholm: European Centre for Disease Prevention and Control; 2013. Available from: http://www.emis-project.eu 7. González-Baeza A, Dolengevich-Segal H, Pérez-Valero I, Cabello A, Téllez MJ, Sanz J, et al. Sexual- ized drug use (chemsex) is associated with high-risk sexual behaviors and sexually transmitted infec- tions in HIV-positive men who have sex withmen: data from the U-SEX GESIDA 9416 Study. AIDS Patient Care STDS. 2018; 32(3): 112–118. https://doi.org/10.1089/apc.2017.0263 PMID: 29620925 8. Folch C, Esteve A, Zaragoza K, Muñoz R, Casabona J. Correlates of intensive alcohol and drug use in men who have sex with men in Catalonia, Spain. Eur J Public Health. 2010; 20(2): 139–45. https://doi. org/10.1093/eurpub/ckp091 PMID: 19564240 9. Garin N, Zurita B, Velasco C, Feliu A, Gutierrez M, Masip M, et al. Prevalence and clinical impact of rec- reational drug consumption in people living with HIV on treatment: a cross-sectional study. BMJ Open. 2017; 7: e014105. https://doi.org/10.1136/bmjopen-2016-014105 PMID: 28100565 10. European Monitoring Centre for Drugs and Drug Addiction. European Drug Report. Available from: http://www.emcdda.europa.eu/system/files/publications/4541/TDAT17001ESN.pdf. 11. Folch C, Fernández-Dávila P, Ferrer L, Soriano R, Dı́ez M, Casabona J. Alto consumo de drogas recreativas y conductas sexuales de riesgo en hombres que tienen relaciones sexuales con hombres. Med Clin (Barc). 2015; 145(3): 102–107. https://doi.org/10.1016/j.medcli.2014.04.030 PMID: 25256434 PLOS ONE | https://doi.org/10.1371/journal.pone.0211252 June 17, 2019 16 / 18 Illicit drug use in people living with HIV in Spain 12. Semple SJ, Strathdee SA, Zians J, Patterson TL. Sexual risk behavior associated with co-administra- tion of methamphetamine and other drugs in a sample of HIV-positive men who have sex with men. Am J Addict. 2009; 18(1): 65–72. https://doi.org/10.1080/10550490802544466 PMID: 19219667 13. Pufall EL, Kall M, Shahmanesh M, Nardone A, Gilson R, Delpech V, et al. Sexualized drug use (“chem- sex”) and high-risk sexual behaviours in HIV-positive men who have sex with men. HIV Med. 2018; 19 (4): 261–70. https://doi.org/10.1111/hiv.12574 PMID: 29368440 14. Stuart D, Weymann J. ChemSex and care-planning: one year in practice. HIV Nurs. 2015; 15: 24–28. 15. Edmundson C, Heinsbroek E, Glass R, Hope V, Mohammed H, White M, et al. Sexualised drug use in the United Kingdom (UK): a review of the literature. Int J Drug Policy. 2018; 55: 131–148. https://doi. org/10.1016/j.drugpo.2018.02.002 PMID: 29625796 16. Ottaway Z, Finnerty F, Amlani A, Pinto-Sander N, Szanyi J, Richardson D. Men who have sex with men diagnosed with a sexually transmitted infection are significantly more likely to engage in sexualised drug use. Int J STD AIDS. 2017; 28(1): 91–93. https://doi.org/10.1177/0956462416666753 PMID: 27542697 17. Stuart D. Sexualised drug use by MSM: background, current status and response. HIV Nurs. 2013; 6– 10. 18. Strathdee SA, Stockman JK. Epidemiology of HIV among injecting and non-injecting drug users: current trends and implications for interventions. Curr HIV/AIDS Rep. 2010; 7(2): 99–106. https://doi.org/10. 1007/s11904-010-0043-7 PMID: 20425564 19. De la Fuente L, Brugal MT, Domingo-Salvany A, Bravo M, Neira-León M, Barrio G. Más de treinta años de drogas ilegales en España: una amarga historia con algunos consejos para el futuro. Rev Esp Salud Pública. 2006; 80(5): 505–520. PMID: 17193814 20. Dawson-Rose C, Draughon JE, Zepf R, Cuca YP, Huang E, Freeborn K, et al. Prevalence of substance use in an HIV primary care safety net clinic: a call for screening. J Assoc Nurses AIDS Care. 2017; 28 (2): 238–249. https://doi.org/10.1016/j.jana.2015.12.001 PMID: 26763795 21. Claborn K, Becker S, Operario D, Safren S, Rich JD, Ramsey S. Adherence intervention for HIV- infected persons who use drugs: adaptation, open trial, and pilot randomized hybrid type-1 trial protocol. Addict Sci Clin Pract. 2018; 13(1): 12. https://doi.org/10.1186/s13722-018-0113-5 PMID: 29606129 22. Korthuis PT, Edelman EJ. Substance use and the HIV care continuum: important advances. Addict Sci Clin Pr. BioMed Central; 2018; 13: 13. https://doi.org/10.1186/s13722-018-0114-4 PMID: 29530080 23. Staltari O, Leporini C, Caroleo B, Russo E, Siniscalchi A, Sarro G De, et al. Drug−Drug interactions: Antiretroviral drugs and recreational drugs. Recent Pat CNS Drug Discov. 2014; 9(3): 153–163. PMID: 25429704 24. Kumar S, Rao P, Earla R, Kumar A. Drug–drug interactions between anti-retroviral therapies and drugs of abuse in HIV systems. Expert Opin Drug Metab Toxicol. 2015; 11(3): 343–55. https://doi.org/10. 1517/17425255.2015.996546 PMID: 25539046 25. Cashman SB, Adeky S, Allen AJ, Corburn J, Israel BA, Montaño J, et al. The power and the promise: working with communities to analyze data, interpret findings, and get to outcomes. Am J Public Health. 2008; 98(8): 1407–17. https://doi.org/10.2105/AJPH.2007.113571 PMID: 18556617 26. Wallerstein NB, Duran B. Using community-based participatory research to address health disparities. Health Promot Pract. 2006; 7(3): 312–323. https://doi.org/10.1177/1524839906289376 PMID: 16760238 27. Revicki DA, Gnanasakthy A, Weinfurt K. Documenting the rationale and psychometric characteristics of patient reported outcomes for labeling and promotional claims: the PRO evidence dossier. Qual Life Res. 2007; 16(4): 717–723. https://doi.org/10.1007/s11136-006-9153-5 PMID: 17268927 28. Eignor DR. Standards for the development and use of tests: the standards for educational and psycho- logical testing. Eur J Psychol Assess. 2001; 17(3): 157–163. https://doi.org/10.1027//1015-5759.17.3. 157 29. Remor E. Systematic review of the psychometric properties of the questionnaire to evaluate the adher- ence to HIV therapy (CEAT-VIH). Patient. 2013; 6(2): 61–73. https://doi.org/10.1007/s40271-013-0009- 0 PMID: 23558754 30. Chiu T, Fang D, Chen J, Wang Y, Jeris C. A robust and scalable clustering algorithm for mixed type attri- butes in large database environment. In: KDD ‘01: Proceedings of the Seventh ACM SIGKDD Interna- tional Conference on Knowledge Discovery and Data Mining. San Francisco, California: ACM; 2001. pp. 263–268. https://doi.org/10.1145/502512.502549 31. Norušis MJ. SPSS 12.0 statistical procedures companion. Chicago:ed. Prentice Hall; Upper Saddle River, NJ; 2004. 32. Pérez C. Técnicas de análisis multivariante de datos. aplicaciones con SPSS®. Madrid: ed. Prentice Hall; 2004. PLOS ONE | https://doi.org/10.1371/journal.pone.0211252 June 17, 2019 17 / 18 Illicit drug use in people living with HIV in Spain 33. Okazaki S. What do we know about mobile Internet adopters? A cluster analysis. Inf Manag. 2006; 43 (2): 127–141. https://doi.org/10.1016/j.im.2005.05.001 34. Lix LM, Keselman JC, Keselman HJ. Consequences of assumption violations revisited: a quantitative review of alternatives to the one-way analysis of variance F-test. Rev Educ Res. 1996; 66(4): 579–619. https://doi.org/10.3102/0034653066004579 35. Observatorio Español de Drogas y Adicciones. Informe 2017: Alcohol, Tabaco y Drogas ilegales en España. Ministerio de Sanidad Servicios Sociales e Igualdad. Available from: http://www.pnsd.mscbs. gob.es/profesionales/sistemasInformacion/informesEstadisticas/pdf/2017OEDA-INFORME.pdf 36. Williams EC, Hahn JA, Saitz R, Bryant K, Lira MC, Samet JH. Alcohol use and human immunodefi- ciency virus (HIV) infection: current knowledge, implications, and future directions. Alcohol Clin Exp Res. 2016; 40(10): 2056–2072. https://doi.org/10.1111/acer.13204 PMID: 27696523 37. Li J, Mcdaid LM. Alcohol and drug use during unprotected anal intercourse among gay and bisexual men in Scotland: what are the implications for HIV prevention? Sex Transm Infect. 2014; 90(2): 125– 132. https://doi.org/10.1136/sextrans-2013-051195 PMID: 24345556 38. European Monitoring Centre for Drugs and Drug Addiction. Spain Drug Report 2018. Available from: http://www.emcdda.europa.eu/countries/drug-reports/2018/spain_en. 39. Grabovac I, Meilinger M, Schalk H, Leichsenring B, Dorner TE. Prevalence and associations of illicit drug and polydrug use in people living with HIV in Vienna. Sci Rep. 2018; 8(1): 8046. https://doi.org/10. 1038/s41598-018-26413-5 PMID: 29795303 40. Allavena C, Guimard T, Billaud E, de la Tullaye S, Reliquet V, Pineau S, et al. Prevalence and risk fac- tors of sleep disturbances in a large HIV-infected adult population. J Int AIDS Soc. 2014; 17: 19576. https://doi.org/10.7448/IAS.17.4.19576 PMID: 25394083 41. Zaro I, Navazo T, Vázquez J, Garcı́a A, Ibarguchi L. A closer look at chemsex in Spain, 2016. Imagina Más. Apoyo Positivo. Avalaible from: https://apoyopositivo.org/wp-content/uploads/2017/04/A-closer- look-at-Chemsex-in-Spain-2016.pdf. 42. Schmidt AJ, Bourne A, Weatherburn P, Reid D, Marcus U, Hickson F, et al. Illicit drug use among gay and bisexual men in 44 cities: Findings from the European MSM Internet Survey (EMIS). Int J Drug Pol- icy. 2016; 38:4–12. https://doi.org/10.1016/j.drugpo.2016.09.007 PMID: 27788450 43. Maxwell S, Shahmanesh M, Gafos M. Chemsex behaviours among men who have sex with men: A sys- tematic review of the literature. Int J Drug Policy. 2019; 63:74–89. https://doi.org/10.1016/j.drugpo. 2018.11.014 PMID: 30513473 44. Joint United Nations Programme on HIV/AIDS (UNAIDS). UNAIDS DATA 2018. Available from: http:// www.unaids.org/sites/default/files/media_asset/unaids-data-2018_en.pdf. 45. Fuster-Ruiz de Apodaca MJ, Arazo P, López JC, Sánchez N, Cotarelo M, Dalmau D. HIV patients ‘ appraisal of antiretroviral treatment characteristics in Spain. Rev Multidiscip del SIDA. 2015; 3(5): 7–20. 46. Binford MC, Kahana SY, Altice FL. A systematic review of antiretroviral adherence interventions for HIV-infected people who use drugs. Curr HIV/AIDS Rep. 2012; 9:287–312. https://doi.org/10.1007/ s11904-012-0134-8 PMID: 22936463 47. Altice FL, Kamarulzaman A, Soriano V V., Schechter M, Friedland GH. Treatment of medical, psychiat- ric, and substance-use comorbidities in people infected with HIV who use drugs. Lancet. 2010; 376:367–87. https://doi.org/10.1016/S0140-6736(10)60829-X PMID: 20650518 48. Glynn RW, Byrne N, O ‘Dea S, Shanley A, Codd M, Keenan E, et al. Chemsex, risk behaviours and sex- ually transmitted infections among men who have sex with men in Dublin, Ireland. Int J Drug Policy. 2018; 52: 9–15. https://doi.org/10.1016/j.drugpo.2017.10.008 PMID: 29223761 49. Coll J, Fumaz CR. Drogas recreativas y sexo en hombres que tienen sexo con hombres: chemsex. Riesgos, problemas de salud asociados a su consumo, factores emocionales y estrategias de interven- ción. Rev Enf Emerg. 2016; 15(2): 77–84. 50. Ramos C, Pardo L, Clara CG, Prado M, Soler V. Programa de educación y salud sexual para usuarios de chemsex: una respuesta coordinada desde la ONG Apoyo Positivo y el Instituto de Adicciones de Madrid. Rev Multidiscip del Sida. 2019; 7(16):48–52. 51. Stardust Z, Kolstee J, Joksic S, Gray J and Hannan S. A community-led, harm-reduction approach to chemsex: case study from Australia’s largest gay city. Sex Health. 2018; 15:179–81. https://doi.org/10. 1071/SH17145 PMID: 29592830 52. Saitz R, Cheng DM, Allensworth-Davies D, Winter MR, Smith PC. The ability of single screening ques- tions for unhealthy alcohol and other drug use to identify substance dependence in primary care. J Stud Alcohol Drugs. 2014; 75(1): 153–157. https://doi.org/10.15288/jsad.2014.75.153 PMID: 24411807 PLOS ONE | https://doi.org/10.1371/journal.pone.0211252 June 17, 2019 18 / 18