Sexual Risk Behaviors among Club Drug Users in Shanghai, China: Prevalence and Correlates

Abstract

We surveyed 276 club drug users in Shanghai, China. Overall, 43.8% reported ≥2 sex partners in the past 30 days, and 48.9% reported having sex with non-regular partners, 67.4% of whom had unprotected sex. Having ≥2 recent sex partners was associated with being 35 years or older, male, living with friends or others, introduced to club drug use by non-regular sex partners, using methamphetamine recently, self-identified as gay/lesbian or bisexual, had sexual debut before 20 years old, and recently had sex under the influence of drugs. Having unprotected sex with non-regular partners in the past 30 days was associated with lower education levels, having sex to obtain drugs, and lower levels of HIV/AIDS knowledge. Club drug users should be targeted for intervention programs. Future research needs to identify other protective and risk factors for sexual risk behaviors and design interventions to reduce club drug use and associated sexual risk behaviors.

Introduction

In recent years, research has increasing been focused on the use of club drugs because of their increasing prevalence in many parts of the world over the past two decades [1–3] and their relationship to HIV risk and other health issues [4–6]. In general, the term “club drugs” refers to a category of drugs that is commonly used at clubs, “raves”, or dance parties, including cocaine, methamphetamine, ecstasy, LSD, GHB, etc. [7–10]. In China, club drugs are called new-type drugs because they are relatively new compared to opium and heroin [11,12]. New-type drugs such as “magu”, “happy water”, “magic mushrooms”, and cough mixture for nonmedical use were also included in the survey. The most commonly used new-type drugs in China are methamphetamine, ketamine, and ecstasy [2].

Club drugs put users at increased risk of acquiring and transmitting HIV and other sexually transmitted diseases (STDs) by encouraging sexual risk-taking behaviors, including increased numbers of sexual partners, prolonging duration of sexual contact with partners, and/or decreased condom use [4,5,13]. The relationship between drug use and sexual risk behaviors is complex and complicated by the type, frequency, and mode of substance use [14]. Although not all club drug use leads to sexual risk behaviors, the association between sexual risk behaviors and certain club drugs such as ecstasy and methamphetamine has been well established [5,15–17].

At the end of 2010, there was a total of more than 1.5 million registered drug users in China, of whom 430,000 (28%) were registered as users of synthetic drugs (amphetamine-type stimulants, ketamine, etc). Of the newly identified drug users in 2010, about 0.12 million (55%) had used synthetic drugs, and most were younger than 25 years [2]. Most research about club drugs has been conducted in Western societies, and is focused on gay and bisexual men. There have been few studies that formally address these issues in China. One exception is a recent study that collected data from a total of 730 club drug users who were “administratively detained” (incarcerated for drug use or in mandatory detox centers), and reported a higher prevalence of risky sexual behaviors, but correlates other than polydrug use were not examined [12]. Nonetheless, in China, little is known about the individuals who use club drugs and their sexual behaviors that may place them at risk for HIV and other STDs. Understanding these issues will provide important information for designing effective sexual risk-reduction interventions, as well as useful directions for future research. The current study was undertaken to examine the prevalence of sexual risk behaviors and to identify factors associated with them among a sample of club drug users in Shanghai recruited through respondent-driven sampling (RDS).

Methods

Participants and Procedures

Two hundred and seventy six participants were recruited over a six-month period in 2011 in Shanghai. Eligibility criteria included being 18 years or older, residing in Shanghai, not participating in any formal drug abuse treatment program within the past 30 days, and self-reporting use of methamphetamine, MDMA/ecstasy, and/or ketamine at least once in the past three months and three times or more in the past 12 months. RDS was used to recruit participants [18,19], as it has been used successfully to recruit drug users in several areas of the world [20–23].

We distributed flyers to recruit “seeds” for the study, and posted them at universities and voluntary counseling and testing (VCT) sites, but none were successfully recruited this way. A total of nine seeds were recruited, two through referrals by NGO personnel who knew them, three by social workers from a social work station that provides services and care for drug users and were knowledgeable about the drug-using community in Shanghai, and four by outreach workers. After the seeds completed the interview, they were asked to refer people “like themselves” who had recently used club drugs. Usually three coupons were given to each participant to recruit his/her peers, but sometimes additional coupons were given to try to reach particularly difficult-to-access subpopulations, such as females or those with specific occupations, or when the recruitment process slowed. Sixteen participants requested additional coupons.

The study was approved by the Institutional Review Board of the University of California, Los Angeles and the Ethics Board of Fudan University, Shanghai. Informed consent was obtained from all participants. The participants completed a self-administered paper-and-pencil survey in a location of their choice. We had a private room available at Fudan University, but no participants chose to be interviewed there. Most chose to be interviewed at tea or coffee shops, and a small proportion chose to be interviewed at their work. Interviews took 30–45 minutes to complete. A research assistant was available to answer questions and give assistance. Participants received approximately $US 15 for completing the questionnaire and were given coupons to recruit others, and received approximately $6 US for each of their referred participants who were interviewed.

Measures

Introduction of participants to club drug use

Participants were asked about those who introduced them to club drug use, such as non-regular sex partners (commercial, casual, anonymous) or others (i.e., regular sex partners, friends, etc.).

Recent club drug use

Participants were ask to report their recent (past 30 days) use of methamphetamine, MDMA/ecstasy, ketamine, magu (a mixture of methamphetamine and caffeine), marijuana, cocaine, happy water (a mixture of methamphetamine, amphetamine and ketamine), cough mixture for non-medical use, magic mushrooms (hallucinogens that contain the “psychedelic” chemical, psilocybin), and LSD (lysergic diethylamide acid).

Sexual behavior and HIV infection

Participants were asked how many sex partners they had in the past 30 days and in the past 12 months (coded as “1” if two or more and “0” if one or none). They were also asked if they had regular (spouse, boy/girlfriend, lover), commercial (paid and/or being paid by), casual, and/or anonymous sex partners in the past 30 days, as well as in the past 12 months. Frequency of condom use with regular, commercial, casual, and anonymous partners was indicated as “never”, “sometimes”, “nearly always”, or “every time”. These variables were re-coded as unprotected (never, sometimes, or nearly always) vs. protected (every time). Other variables included age at sexual debut, having sex to obtain drugs (ever vs. never), ever having sex under the influence of club drugs in the past three months, history of HIV testing (ever vs. never), and receiving a HIV diagnosis (positive vs. negative).

HIV/AIDS knowledge

HIV/AIDS knowledge was assessed by ten questions (three about transmission modes of HIV and condom use for HIV prevention, four regarding misconceptions about HIV transmission, one about availability of an HIV vaccine, one about physical appearance indicating HIV status, and one about ability to prevent HIV by physical exercise). The total scores for HIV/AIDS knowledge ranged from 0 to 10 (Cronbach’s alpha=0.69; a score of 0 was designated for a wrong answer or for unknown or unsure, and 1 for a correct answer).

Depressive symptoms

Depressive symptoms were measured using the short version of the Zung self-rating depression scale [24], which is a 10-item instrument adapted from the original 20-item questionnaire. This adapted version has been previously used in several studies conducted in China among persons living with HIV and their HIV-negative family members [25,26]. The participants were asked how often they felt certain feelings, including being down-hearted and blue, getting tired for no reason, and having trouble sleeping at night. Responses ranged from “a little bit of the time” (1) to “most of the time” (4). The overall scale was the sum of the individual items (Cronbach’s alpha=0.68). Some items were reverse-coded so that scores were in the same direction as the rest of the items. A higher score indicated a higher level of depressive symptoms.

Statistical Analysis

For categorical variables, we reported sample population proportion (SPP) and estimated population proportion (EPP) and their 95% confidence intervals (CI) generated by the RDS Analysis Tool 6.0 (RDSAT), a software package specifically developed to analyze data collected through RDS (www.respondentdrivensampling.org). EPP generated by RDSAT are adjusted proportions that account for differential social network sizes and homophily that are deemed representative of the population from which they are derived [19,27,28]. The network size was based on the response to “How many other club drug users in Shanghai do you now know and they also know you?”

In univariate and multivariate analyses, the individualized weights for the dependent variables generated by RDSAT 6.0 were used to weight the dataset [29,30]. Univariate logistic regression analyses were first performed to examine the odds associated with multiple sex partners (two or more) and unprotected sex with non-regular partners in the past 30 days. Subsequently, multivariate analyses were performed. Variables selected into multivariate analyses were based on prior knowledge and their associations with outcome variables in univariate analyses. Those that were significantly (p<0.05) or marginally (0.05<p<0.10) associated were entered into multivariate analyses or based on prior knowledge of the relationship between them and outcome variables. A backward stepwise procedure was used. The significance level for variable removal from the model was set at 0.15. If one category of a dummy variable was included in the final model, the other category was forced into the final model.

A sensitivity analysis was conducted by comparing results from multivariate regression models with and without RDSAT generated weights, and indicated that the results from two models did not substantially differ from each other. Only the results of weighted analyses are reported here. Statistical analyses were performed using the SAS 9.2 statistical software package (SAS Institute Inc., Cary, NC).

Results

The Recruitment Process (RDS)

Figure 1 shows the recruitment tree that was started by the nine seeds. Only four (44.4%) had four or more recruitment waves, but these four referral chains produced 236 recruits, accounting for 85.5% of total recruits. The two longest referral chains extended to eight waves, producing 101 and 83 recruits, respectively. Seven hundred and five coupons were distributed, but only 292 (41.4%) were returned by potential participants; a total of 267 were eligible and completed the survey. The initial sample composition was considered biased since it was not possible to select the seeds randomly from this hidden target population. Overall, stabilization with respect to socio-demographic characteristics was obtained after five to six waves.

Figure 1.

Referral networks generated by RDS (n = 276).

triangle=male; circle=female

Background Characteristics

Table 1 shows the crude and population-adjusted estimates of demographic characteristics. Crude estimates (SPP) showed that 72.8% were male, mean age was 28.6 years (SD=7.4), and 32.6% were younger than 25 years. In terms of marital status, 59.1% were married or living as married, 34.8% had never married, and the remaining (6.2%) were divorced, separated, or widowed. Two-thirds (64.1%) reported a monthly individual income of 3,000 Yuan or more, and 66.3% had at least a senior high school education. One-fifth (19.2%) were employed in an enterprise, public institution, or government; 66.3% were solo business owners or worked in a service industry; and 14.5% were unemployed, retired, or students. Over one-third (38.0%) lived alone, 32.2% lived with friends or other adults, and 29.7% lived with a spouse or boy/girlfriend. The majority (79.3%) self-identified as heterosexual, and 20.7% self-identified as gay/lesbian or bisexual. The average score of depressive symptoms was 22.6 (SD=4.9; possible range 10–36), and the average score for HIV/AIDS knowledge was 5.9 (SD=2.2; possible range of 0–10).

Table 1.

Participants’ socio-demographics, drug use and sexual behaviors, HIV status, HIV/AIDS knowledge, and depressive symptoms (N=276)

Characteristics	SPP		EPP
	N	%	%	95% CI
Socio-demographic
Age (years), mean ± SD	28.6 ±7.4
<25	90	32.6	35.3	28.1–43.2
25–34	136	47.1	43.6	37.1–50.0
≥35	56	20.3	21.2	14.5–28.0
Gender
Female	75	27.2	29.6	23.0–36.5
Male	201	72.8	70.4	63.6–77.0
Marital status
Never married	96	34.8	35.9	29.0–43.2
Married or living together	163	59.1	58.3	50.9–65.6
Divorced, separated or widowed	17	6.2	5.9	3.0–8.9
Monthly individual income (Yuan)
<3000a	99	35.9	40.3	32.5–47.8
≥3000	177	64.1	59.7	52.2–67.5
Education
<senior high school	93	33.7	33.5	25.9–41.9
≥senior high school	183	66.3	66.5	58.1–74.1
Occupation
Enterprise, public institution or government	53	19.2	20.2	14.2–25.9
Sole business owner or service industry	183	66.3	67.2	60.4–74.3
Retired, unemployed or student	40	14.5	12.6	8.3–17.8
Domestic companions
Spouse or girl/boyfriend	82	29.7	29.8	22.6–36.3
Friends or other adults	89	32.2	33.2	26.8–39.7
Alone	105	38.0	37.0	31.4–43.7
Drug use-related variables
Person who introduced to club drug use
Non-regular sex partner	45	16.3	15.7	11.6–20.4
Regular sex partner	68	24.6	23.7	18.2–28.9
Friend, colleague, or other	163	59.1	60.6	54.2–67.2
Drugs used in past 30 days (%)
Methamphetamine	143	51.8	42.8	35.8–50.1
Ecstasy	117	42.4	39.8	32.7–48.3
Ketamine	98	35.5	31.5	24.2–38.8
Magu	8	2.9	1.5	0.6–2.5
Marijuana	26	9.4	7.5	4.4–11.2
Cocaine	6	2.2	1.9	0.4–3.9
Happy water	10	3.6	4.7	2.1–8.4
Any of the above	228	82.6	79.3	73.7–84.7
Sexual behaviors
Age at sexual debut (years), mean ± SD	19.6 ± 3.1
<20	150	58.1	53.4	45.2–60.8
≥20	108	41.9	46.6	39.2–54.8
Self-identified as gay/lesbian or bisexual	57	20.7	14.8	8.2–21.5
Number of sex partners in past 12 months
0	18	6.5	7.4	4.1–11.1
1	43	15.6	18.3	11.6–24.1
2	91	33.0	34.6	29.2–42.8
3 or more	124	44.9	39.7	32.7–45.7
Number of sex partners in past 30 days
0	33	12.0	12.9	8.7–17.2
1	122	44.2	50.2	43.7–56.7
2	85	30.8	28.7	23.2–34.0
3 or more	36	13.0	8.2	5.0–12.1
Had sex in past 12 months with:
Regular partner(s)	235	85.1	86.6	82.2–90.8
Commercial partner(s)	123	44.6	41.0	34.0–47.5
Casual or anonymous partner(s)	167	60.5	58.1	51.6–64.7
Non-regular partner(s)c	194	70.3	66.9	60.3–73.0
Unprotected sex in past 12 months with b:
Regular partner(s)	192	81.7	77.1	70.1–83.3
Commercial partner(s)	77	62.6	65.6	54.4–78.1
Casual or anonymous partner(s)	109	65.3	64.1	52.5–71.4
Non-regular partner(s)c	135	69.6	69.4	60.1–76.5
Had sex in past 30 days with:
Regular partner(s)	209	75.7	76.7	70.9–81.2
Commercial partner(s)	83	30.1	25.5	19.6–31.1
Casual or anonymous partner(s)	109	39.5	35.9	28.9–42.5
Non-regular partner(s)c	135	48.9	43.1	35.4–49.9
Unprotected sex in past 30 days with b:
Regular partner(s)	171	81.8	77.8	67.4–82.9
Commercial partner(s)	53	63.9	59.1	43.1–79.9
Casual or anonymous partner(s)	76	69.7	57.2	42.8–70.4
Non-regular partner(s)c	91	67.4	62.1	48.4–72.9
Had sex with others to obtain drugs	118	42.8	40.0	33.4–47.1
Had sex under influence of club drugs in past 3 months	160	58.0	52.4	45.2–60.2
HIV Status
Ever tested for HIV
Yes	84	30.4	28.8	21.9–35.4
No	185	67.0	68.2	61.7–74.9
Don’t know/no response	7	2.6	3.0	1.2–5.4
HIV status of the 84 participants tested
Positive	4	4.8
Negative	62	73.8
Didn’t know/no response	18	21.4
HIV/AIDS knowledge, mean ± SD (range)	5.9 ± 2.2 (0–10)
Depressive symptoms, mean ± SD (range)	22.6 ± 4.9 (10–36)

CI, confidence interval; SD, standard deviation;

^a3000 Yuan = approximately $US 475;

^bnumbers of specific types of partners were used for denominator;

^cincludes commercial, casual and anonymous sex partners

Drug Use Behaviors

Table 1 shows the crude and population-adjusted estimates of drug use behaviors. Crude estimates showed that more than half of participants (59.1%) reported that they were introduced to club drug use by their friends, colleagues or others, 24.6% by regular sex partners, and 16.3% by non-regular sex partners. Most (82.6%) reported using at least one type of club drug in the past 30 days, of which methamphetamine was most commonly used, followed by ecstasy, ketamine, marijuana, happy water, magu, and cocaine. None reported taking cough mixtures, magic mushrooms, or LSD in the past 30 days.

Sexual Behaviors

As shown in Table 1, crude estimates showed that there were high rates of engaging in risky sexual behaviors, placing those individuals at greater risk for HIV and other STDs. The mean age for sexual debut was 19.6 years (SD=3.1). One-third (33.0%) reported having two sex partners, and 44.9%, three or more in the past 12 months; 30.8% reported having two sex partners and 13.0% reported having three or more in the past 30 days.

The majority (85.1%) of participants had regular sex partners, 44.6% had commercial sex partners, and 60.5% had casual or anonymous sex partners in the past 12 months. The highest rate of unprotected sex was with regular partners (81.7%), followed by casual or anonymous partners (65.3%) and commercial partners (62.6%). The latter two comprised 69.6% of those reporting unprotected sex with non-regular partners. Three-quarters (75.7%) reported that in the past 30 days they had sex with regular partners, 30.1% with commercial partners, and 39.5% had casual or anonymous partners. The rate of unprotected sex with different types of partners in the past 30 days was similar to that for the past 12 months. In addition, 42.8% reported ever having sex with others to obtain drugs. More than half (58.0%) reported ever having sex under the influence of club drugs in the past three months.

HIV Testing History and HIV Infection

About 30% of participants had been tested for HIV, of whom four (0.3%) self-reported being HIV-positive (Table 1). Those who had been tested for HIV reported a significantly higher level of HIV/AIDS knowledge than those who had not been tested, did not know if they had ever been tested, or gave no response (14.63 vs.13.56; p=0.0007).

Of the four HIV-positive participants, two self-identified as heterosexual and two as gay/lesbian or bisexual. Three had had multiple sex partners in the past three months and had unprotected sex with non-regular partners in the past three months.

Factors Associated with Multiple Sex Partners

Results from univariate and multivariate regression analyses examining factors associated with having multiple sex partners in the past 30 days are summarized in Table 2. Univariate analysis demonstrated that having multiple sex partners was significantly associated with being 35 years or older, being male, being divorced, separated or widowed (vs. never married), living alone, initiating club drug use through non-regular sex partners, self-identified as gay/lesbian or bisexual, had had sex with others to obtain drugs, had had sex under the influence of drugs in the past three months, had more knowledgeable about HIV/AIDS, and had more depressive symptoms.

Table 2.

Factors associated with having two or more sex partners in the past 30 days

Independent Variable	COR (95% CI)	P value	AOR (95% CI)	P value
Age (year)
< 25	1.00		1.00
25–34	1.63 (0.92–2.90)	0.0931	1.16 (0.50–2.72)	0.7245
≥35	2.02 (1.03–3.93)	0.0400	8.62 (2.44–30.44)	0.0014
Gender (male)	3.02 (1.64–5.56)	0.0004	4.45 (1.73–11.47)	0.0024
Marital status
Never married	1.00		1.00
Married or living together	1.40 (0.77–2.56)	0.2660	1.93 (0.70–5.36)	0.2049
Divorced, separated or widowed	3.00 (1.20–8.76)	0.0204	5.08 (0.93–26.72)	0.0579
Monthly individual income (≥3000 Yuan)	1.19 (0.72–1.96)	0.5009
Education (≥ senior high school)	0.74 (0.44–1.22)	0.2361
Occupation
Enterprise, public institutions or government	1.00		1.00
Sole business owner or service industry	1.66 (0.87–3.15)	0.1214	2.20 (0.87–5.54)	0.0946
Retired, unemployed or student	0.74 (0.29–1.90)	0.5376	0.37 (0.10–1.43)	0.1491
Domestic companions
Spouse or girl/boyfriend	1.00		1.00
Friends or other adults	1.89 (0.99–3.61)	0.0522	6.34 (2.07–19.41)	0.0012
Alone	2.23 (1.19–4.17)	0.0117	2.24 (0.71–7.03)	0.1680
Introduction to club drug use by non-regular sex partner	3.04 (1.57–5.90)	0.0010	4.77 (1.80–12.71)	0.0018
Drugs used in past 30 days:
Methamphetamine	1.32 (0.81–2.16)	0.2617	3.89 (1.80–8.40)	0.0006
Ecstasy	1.65 (1.00–2.71)	0.0503
Ketamine	1.28 (0.76–2.14)	0.3561
Magu	9.84 (0.63–153.01)	0.1023
Marijuana	1.24 (0.52–2.97)	0.6212
Cocaine	11.26 (0.90–141.48)	0.0608
Happy water	3.11 (0.79–12.29)	0.1055
Age at sexual debut (≥ 20 years old)	0.60 (0.36–1.00)	0.0519	0.28 (0.12–0.64)	0.0024
Self-identified as gay/lesbian or bisexual	4.67 (2.53–3.63)	<.0001	8.07 (3.07–21.16)	<.0001
Had sex with others to obtain drugs	2.65 (1.60–4.38)	0.0001
Had sex under the influence of drugs in past 3 mths	5.06 (2.93–8.72)	<.0001	8.78 (3.80–20.31)	<.0001
HIV/AIDS knowledge	1.19 (1.06–1.34)	0.0041
Depressive symptoms	1.07 (1.01–1.13)	0.0119	1.06 (0.98–1.15)	0.1234

AOR = adjusted odds ratio; CI = confidence interval; COR = crude odds ratio

In multivariate analysis, variables significantly associated with having multiple sex partners included being 35 years or older (vs. less than 25 years) (OR=8.62, 95% CI 2.44–30.44), being male (OR=4.45, 95% CI 1.73–11.47), living with friends or others (OR=6.34, 95% CI 2.07–19.41) (vs. living with spouse or girl/boyfriend), being introduced to club drug use by non-regular sex partners (OR=4.77, 95% CI 1.80–12.71), using methamphetamine in the past 30 days (OR=3.89, 95% CI 1.80–8.40), self-identified as gay/lesbian or bisexual (OR=8.07, 95% CI 3.07–21.16), had sexual debut at 20 years or older (OR=0.28, 95% CI 0.12–0.63), and having sex under the influence of drugs in the past three months (OR=8.78, 95% CI 3.80–20.31). Being divorced, separated or widowed (OR=5.08, 95% CI 0.95–27.20) and being a sole business owner or working in a service industry (vs. enterprise, institution or government) (OR=2.20, 95% CI 0.87–5.54) were marginally significantly positively associated with having multiple sex partners. We found that the estimates of adjusted odds ratio for age (≥35 vs. <25 years) was approximately four times higher than the crude odds ratio, possibly due to a high positive correlation between participants’ ages and ages at sexual debut.

Factors Associated with Unprotected Sex with Non-regular Partners

To assess factors associated with unprotected sex with non-regular partners in the past 30 days (Table 3), only data from drug users who had had sex with non-regular partners during the past 30 days were included in the analysis. Univariate analysis demonstrated that unprotected sex with non-regular partners was significantly positively associated with having less than a high school education or equivalent, being divorced, separated or widowed (vs. never married), being retired, unemployed or a student (vs. employment in enterprise, institution or government), having sex with others to obtain drugs, self-identifying as heterosexual, and having low levels of HIV/AIDS knowledge. Variables that were marginally associated with unprotected sex with non-regular partners included use of marijuana in the past 30 days.

Table 3.

Factors associated with unprotected sex with non-regular partners in the past 30 days

Independent Variable	COR (95% CI)	P value	AOR (95% CI)	P value
Age (years)
<25	1.00
25–34	0.61 (0.27–1.40)	0.2477
≥35	0.87 (0.33–2.26)	0.7704
Gender (male)	1.10 (0.42–2.93)	0.8406
Marital status
Never married	1.00
Married or living together	1.04 (0.43–2.54)	0.9301
Divorced, separated or widowed	0.28 (0.09–0.91)	0.0347
Monthly individual income (≥ 3000 Yuan)	1.11 (0.54–2.27)	0.7820
Education (≥ senior high school)	0.28 (0.13–0.62)	0.0017	0.28 (0.11–0.77)	0.0129
Occupation
Enterprise, institutions or government	1.00		1.00
Sole business owner or service industry	1.51 (0.59–3.86)	0.3843	1.27 (0.41–3.95)	0.6831
Retired, unemployed or student	5.05 (1.10–23.15)	0.0374	4.63 (0.76–28.09)	0.0961
Domestic companions
Spouse or girl/boyfriend	1.00
Friends or other adults	0.55 (0.20–1.53)	0.2547
Alone	0.57 (0.22–1.48)	0.2485
Initiation into club drug use by non-regular sex partner	1.86 (0.78–4.42)	0.1587	2.54 (0.88–7.32)	0.0838
Drugs used in the past 30 days:
Methamphetamine	0.90 (0.45–1.80)	0.7654
Ecstasy	0.61 (0.31–1.24)	0.1714
Ketamine	1.19 (0.58–2.42)	0.6366
Magu	1.30 (0.15–11.29)	0.8105
Marijuana	3.95 (0.98–15.83)	0.0526
Cocaine	0.18 (0.02–1.37)	0.0986
Happy water	0.89 (0.89–2.97)	0.8531
Age at sexual debut (≥ 20 years old)	0.56 (0.28–1.16)	0.1192
Self-identified as gay/lesbian or bisexual	0.48 (0.24–0.98)	0.0441
Had sex with others to obtain drugs	6.49 (2.81–14.01)	<.0001	7.06 (3.00–16.63)	<.0001
Had sex under the influence of drugs in past 3 months	1.52 (0.70–3.23)	0.2896
HIV/AIDS knowledge	0.79 (0.66–0.96)	0.0154	0.77 (0.61–0.96)	0.0226
Depressive symptoms	1.05 (0.97–1.14)	0.2330

AOR = Adjusted odds ratio; CI = confidence interval; COR = crude odds ratio

In multivariate analysis, variables significantly associated with unprotected sex with non-regular partners included having at least a senior high school education (OR=0.28, 95% CI 0.11–0.77), having sex with others to obtain drugs (OR=7.06, 95% CI 3.00–16.63), and lower levels of HIV/AIDS knowledge (OR=0.77, 95% CI 0.61–0.96). Being introduced to club drug use by non-regular sex partners (OR=2.54, 95% CI 0.88–7.32) was marginally associated with unprotected sex with non-regular partners.

Discussion

We found that more than two-thirds of participants in our study were male, which was consistent with findings from a study with a convenience sample of club drug users in China [12]. However, club drug users in our study sample were younger, had higher levels of education, and were more likely to have never married [12]. Since RDS and convenience sampling both have limitations, we do not know which sample was more representative of the characteristics of the club drug-using population in China. More studies with different sampling methods are needed to elucidate the characteristics of this population.

To the best of our knowledge, the present study was the first to examine the prevalence of sexual risk behaviors, as well as correlates, among club drug users in China. Unlike injecting drug use, which puts people at risk for HIV infection through sharing of needles, club drug users are at risk for HIV by engaging in risky sexual behaviors [31]. Our results suggest that a significant number of club drug users are engaging in risky sexual behaviors; e.g., having multiple sex partners, unprotected sex (no condom use), commercial, causal or anonymous sex partners, and having sex with others to obtain drugs, as indicated in the study with the convenience sample [12]. However, less than one-third of participants had been tested for HIV, indicating a lack of perception of their own risk for HIV infection. Although a number of HIV prevention programs and interventions in China have been implemented targeting typical high-risk populations such as injection drug users, men who have sex with men, and commercial sex workers [32–34], there are no interventions specifically targeting club drug users. Our findings suggest an urgent need for intervention efforts focusing on club drug users to prevent HIV infection and transmission. The association between having multiple sex partners and being male are similar to findings from other studies [35]. Our findings indicated that club drug users 35 years or older were more likely to report having multiple sex partners in the past month than those younger than 25 years, regardless of marital status, which was contrary to the findings from previous studies in which younger people were more likely to have multiple sex partners [36,37]. The reason is unknown, but it is possible that compared to other populations, club drugs influence users’ sexual practices, or that middle-aged persons with multiple sex partners are more likely to report use of club drugs and were thus included in our study. Therefore, research about club drugs, multiple sex partners, and concerns about HIV transmission should not be limited to youth (25 years or younger) [38]. In addition, we found that drug users who are sole business owners or work in a service industry were more likely to have multiple sex partners than those employed in enterprise, public institutions, or government, possibly because they have more free time or flexible hours, providing more opportunities to use drugs.

There is strong evidence that methamphetamine use is associated with HIV sexual risk behaviors in diverse populations [39–42]. Methamphetamine releases neurotransmitters in the brain that increase sexual desire and reduce sexual inhibitions [15,43], thereby stimulating sexual activity [44,45]. We found that at the multivariate level, methamphetamine was the only club drug significantly correlated with having multiple sex partners. Previous research indicated that use of ecstasy has been associated with increased numbers of sexual partners [46], which is inconsistent with our findings. It is possible that ecstasy is most commonly used at dance clubs, raves, and in settings with large crowds, loud music, and no privacy, limiting opportunities to have sex. Magu and happy water, two newly emerging drugs in China, are normally used to increase sexual desire. Our results indicated that they were marginally significantly associated with increased risk of having multiple sex partners at the bivariate level, but they were not included in the final stepwise model. It is possible that so few participants reported use of magu or happy water in the past 30 days that there was insufficient statistical power to detect a difference.

Consistent with previous literature [47–50], we found that those reporting having sex under the influence of club drugs were more likely to having multiple sex partners. Drugs are known to interfere with judgment and decision-making, and their use in conjunction with sexual activity likely increases the probability of risky behaviors [47]. However, we did not find a significant association between unprotected sex with non-regular partners and sex under the influence of club drugs or the use of any specific club drug examined in this study. This suggests that the factors affecting condom use during sex may not necessarily be use of club drugs, but types of sex partners. As indicated by our findings, participants were more likely to use condoms with non-regular partners than regular partners.

An interesting finding was that those introduced to club drug use by non-regular sex partners were more likely to have multiple sex partners and have unprotected sex with non-regular sex partners. This suggests that drug users may be more likely to use club drugs while having sex with non-regular sex partners. Our findings further confirmed that use of condoms was related to type of sex partner. A study of young men who have sex with men indicated that the association of a specific substance and unprotected anal intercourse depended upon partner type and role in anal intercourse [51]. Our results strongly suggest that future research should consider types of sex partners when exploring the link between the use of a specific club drug and condom use.

Participants who had sex with others to obtain drugs were more likely to report unprotected sex with non-regular sex partners; two possible explanations are that those who have sex in exchange for drugs may feel pressured to not use condoms, and/or they may be more likely to be using drugs during sex.

As indicated previously [52], we found that homo/bisexual participants were significantly more likely than heterosexual participants to report having more than one sex partner in the past 30 days. However, we observed that self-reported risk behaviors such as unprotected sex did not differ according to sexual orientation, which was consistent with previous studies [53,54].

We found that HIV/AIDS knowledge was an important predictor of unprotected sex behaviors with non-regular partners; participants with higher levels of knowledge about HIV/AIDS were less likely to have unprotected sex with non-regular partners. Of note, the average score for HIV/AIDS knowledge in our study sample was low, suggesting an urgent need for HIV and AIDS education among this population. Consistent with other studies [55], respondents with higher levels of education were less likely to having unprotected sex with non-regular sex partners, probably because they have better access to information about HIV/AIDS [56].

Other research has shown an association between depressive symptoms and having multiple sex partners [54,57,58], which could be attributed to club drug use, so depression itself may not be directly related to having multiple sex partners. Univariate analysis showed a significantly positive relationship, but multivariate analysis did not when drug use-related variables were taken into account.

Our research has a few potential limitations. First, due to the illegal status of drug use in China, eligible subjects may have refused to participate because of fear of being identified as a drug user and arrested, which may have led to selection bias. It is possible that use of RDS suffers some biases due to different levels of homophily and different sizes of personal networks across groups; population proportion estimates generated by RDSAT were provided, and individualized weights were used for data in regression analysis to reduce these biases. However, that might have been limited, because questions about network size did not include a definition of the population with all the eligibility restrictions, as required by RDS standards [30]. The overall response rate was low and we were not able to collect any information about those who did not respond, so those who did not respond may differ from those who participated, which may have led to selection bias. A possible source of selection bias due to providing more than three recruitment coupons might be individuals who have very large personal networks and may be overrepresented in the sample. On the other hand, it could have offered more depth in the population by recruiting more difficult-to-access subpopulations, such as females and those with high social status, thereby rendering a more representative sample.

Information bias is a possible problem; for example, participants may not have given accurate information on certain sensitive questions such as drug use and sexual behaviors. Some questions asking about events that took place a long time ago may have had recall bias. Our quantitative study used a cross-sectional design. We may not be able to make causal inferences due to the existence of temporal ambiguity.

This study underscores the importance of including club drug users as another high-risk population in current HIV/AIDS prevention and intervention programs in China. Since the number of HIV infections occurring through heterosexual transmission is increasing in China, risky sexual behaviors are of increasing concern. Intervention efforts should promote condom use and HIV testing and counseling among club drug users, as well as offering education to increase their levels of HIV/AIDS knowledge. Our findings also underscore the unique association between methamphetamine use and high-risk sexual behaviors, suggesting additional efforts should aim to reduce club drug use, especially methamphetamine. Further research is needed to identify other possible protective and risk factors for risky sexual behaviors among club drug users, and applied to designing interventions specifically targeting club drug users to reduce both clubdrug use and sexual risk behaviors.