Abstract
Objectives. We assessed factors associated with engagement in transactional sex among men who have sex with men recruited from one of the largest Internet sites for men seeking social or sexual interactions with other men in Latin America.
Methods. We constructed multilevel logistic regression models to analyze factors associated with engagement in transactional sex in 17 Latin American countries in 2012.
Results. Of 24 051 respondents, 1732 (7.2%) reported being paid for sexual intercourse in the past 12 months. In a multivariable model, higher country-level unemployment was associated with increased odds of transactional sex (adjusted odds ratio [AOR] = 1.07 per 1% increase in unemployment; 95% confidence interval [CI] = 1.00, 1.13). Individual or interpersonal factors associated with increased odds of engagement in transactional sex included self-reported HIV (AOR = 1.33; 95% CI = 1.04, 1.69) or sexually transmitted infection (AOR = 1.33; 95% CI = 1.11, 1.59), childhood sexual abuse history (AOR = 1.75; 95% CI = 1.48, 2.06), intimate partner violence (past 5 years, AOR = 1.68; 95% CI = 1.45, 1.95), and sexual compulsivity (AOR = 1.77; 95% CI = 1.49, 2.11).
Conclusions. Structural-level economic interventions and those that address individual and interpersonal factors may improve HIV prevention efforts among men who have sex with men who engage in transactional sex.
In Latin America, the HIV epidemic is driven by sexual transmission and is highly concentrated in men who have sex with men (MSM).1,2 MSM in Latin America have 30 times greater odds of HIV infection than do men in the general population.1 Although much of the literature has focused on HIV risk in MSM, limited research in Latin America has specifically assessed the associated risk characteristics of men who engage in transactional sex.2–10 Transactional sex, defined as the exchange of sexual intercourse for money or goods, is associated with increased vulnerability to HIV among women.11
Some men who engage in transactional sex may be engaged in regular sex work (in which transactional sex is a primary income source and individuals self-identify as sex workers); however, these men may also occasionally engage in transactional sex. There are likely important differences between men who engage in sex work and those who engage in occasional transactional sex. Some studies have shown an increased prevalence of HIV among MSM who report engagement in sex work compared with those who do not,3–5,12 and some evidence suggests that men engaged in sex work have higher HIV prevalence than do those who engage in transactional sex informally.5
Men who engage in transactional sex may have increased vulnerability to HIV via an increased burden of psychosocial morbidities, reduced power and condom use negotiation, and stigma and discrimination.6,13,14 Men who engage in transactional sex may also face a disproportionate burden of psychosocial factors, including a history of childhood sexual abuse (CSA), intimate partner violence (IPV), substance use, and depression, which can lead to increased sexual risk for HIV.15,16 These factors and others may differ depending on the type or frequency of transactional sex men are involved in.
Factors beyond those at the individual level may affect vulnerability to HIV infection. The political economy of health theory provides a framework in which to consider how unequal distribution of resources, wealth, and power can affect health. Structural drivers of the HIV/AIDS epidemic, which include social, economic, and political factors, contribute to social inequities.17–19 Recent research has pointed to the importance of these factors in HIV transmission and acquisition among vulnerable groups.11,18,20 In particular, urban unemployment has been implicated as a driver of the sex work industry among female sex workers as well as HIV infection among injection drug users in Eastern Europe.21,22
Latin America is a rapidly urbanizing area of the world,23 and country-level unemployment there may be a particularly salient structural driver of the transactional sex market among MSM and may have implications for the HIV epidemic. Even when employment opportunities are available, the inability to access them because of discrimination on the basis of sexual orientation could lead to engagement in transactional sex. Legal protections against employment discrimination may therefore result in decreased engagement in transactional sex.
The emergence of the Internet and mobile apps as popular venues for MSM to meet social and sexual partners provides a novel framework within which to assess factors associated with transactional sex. We have documented the prevalence of engagement in transactional sex and assessed which individual and interpersonal factors and whether employment-related factors are associated with transactional sex among a large sample of MSM in 17 Latin American countries who are users of one of the largest Internet sites for men seeking social or sexual interactions with other MSM.
METHODS
In 2012, we conducted an anonymous survey among members of one of the largest Internet sites for men seeking social or sexual interactions with other MSM in Spanish- and Portuguese-speaking countries in Latin America, the Caribbean, Spain, and Portugal. We sent an e-mail recruitment message to all site users at the time of the study if the individual had indicated that his residence was within Latin America. The recruitment message provided a description of the study purpose and included a link to the study Web site. On visiting the study Web site, individuals were able to read a more detailed description of the study procedures and, if interested, proceed to the study consent form.
Those who decided to participate were able to move directly from the consent form to the study questionnaire, completion of which took approximately 28 minutes. To minimize duplicate responses, we programmed the survey to allow access only from a unique Internet provider address on a single occasion. We did not provide any incentive for study participation. The recruitment message remained in each individual’s e-mail box for 30 days, after which any unopened e-mails were automatically removed.
Our analysis was limited to 17 countries in Latin America, including Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Uruguay, and Venezuela. We excluded individuals who reported a gender identity of female or transgender (identified either as transgender or a different gender at birth than the current gender identity) from our analysis.
Assessment
The online survey included questions related to sociodemographics, HIV, and sexually transmitted infection (STI) testing practices, self-reported HIV and STI (syphilis, gonorrhea, chlamydia, human papillomavirus, or genital herpes) prevalence, and psychosocial factors. We chose measures that have been shown to be associated with HIV risk among MSM for inclusion in the multivariable model.
We asked respondents about their country of residence, age, education (coded university or more vs less than university), about their income and class (no income, low income or lower class, middle income or middle class, high income or upper class), whether their residence was urban or rural, whether they were currently dating or in a relationship (coded as currently dating a regular partner or partners vs not currently dating), and about their sexual orientation (heterosexual or straight, bisexual, homosexual or gay, or unsure or questioning). We asked participants whether they had had a physical examination in the previous 12 months.
We assessed engagement in transactional sex with the following question: “In the past 12 months, did anyone pay you in exchange for engaging in any type of sexual activity (e.g., oral sex, anal intercourse)?” We also asked respondents about the gender of the person who paid them in exchange for sexual intercourse (nontransgender male, nontransgender female, transgender male to female, transgender female to male, or other).
We asked respondents whether in the past year a health care provider had told them that they had syphilis, gonorrhea, chlamydia, human papillomavirus or genital warts, genital herpes, or hepatitis a, B, or C. We assessed HIV serostatus by asking respondents whether a health care provider had ever told them they were infected with HIV. We assessed HIV testing history by asking whether participants had ever been tested for HIV infection.
We assessed depressive symptoms using the 10-item Center for Epidemiologic Studies Depression scale, which assesses clinically significant distress as a marker for clinical depression.24 We assessed the 10 items on a 4-point Likert scale, scored from 0 to 3 with a score of 10 or greater suggesting clinical depression. We determined alcohol dependence using the CAGE questionnaire,25,26 a 4-item validated scale that assesses hazardous and harmful alcohol use. A score of 2 or greater suggests alcohol dependence. We assessed sexual compulsivity using the Sexual Compulsivity Scale, a 10-item scale on a 4-point Likert scale (from “not at all like me” to “very much like me”).27,28 A score of 24 or higher indicates high sexual compulsivity. Participants could select “prefer not to answer” for any component of any psychosocial assessment, which we coded as missing.
We determined a history of CSA by asking respondents a series of questions regarding unwanted or forced sexual touching or intercourse with a person 5 years older (when the respondent was aged 13 years or younger) or 10 years older (when the respondent was aged 14–17 years). We assessed IPV by asking respondents if they had been psychologically (verbally threatened, demeaned in front of others, ridiculed for appearance, forced to get high or drunk, stalked, or had property destroyed or damaged) or physically (been hit with fists or open hand, hit with an object, pushed or shoved, kicked, or had something thrown at them) battered or forced to have sexual intercourse by a boyfriend or male partner within the past 5 years.
We assessed sexual behaviors by asking participants about their condom use patterns with female, male, and transgender partners. We considered participants who reported any anal intercourse (insertive or receptive) with a male or transgender partner without a condom in the past 3 months to have had unprotected anal intercourse. We considered participants who reported condom use at every sexual encounter or those who had not been sexually active in the past 3 months to not have had unprotected anal intercourse. We assessed hard drug use in the context of sexual intercourse by asking participants if they had used stimulants (e.g., methamphetamine, speed, crack, cocaine), ecstasy, gamma-Hydroxybutyric acid, ketamine, heroin, or amyl nitrates (“poppers”) during sexual intercourse.
To assess the relationship between a country’s economic development and proportion of respondents reporting engagement in transactional sex, we considered country-level unemployment (in 2012, as a percentage of total labor force; data source CIA World Factbook) as our primary country-level variable.29 We determined that a higher unemployment rate in a country may lead to reduced employment opportunities and thus an increased likelihood of engaging in transactional sex.21
We assessed the existence of legal sanctions prohibiting discrimination in employment on the basis of sexual orientation from the International Lesbian, Gay, Bisexual, Trans and Intersex Association 2013 report on state-sponsored homophobia.30 This report compiled laws related to criminalization, discrimination, and protection for lesbian, gay, bisexual, transgender, and intersex individuals globally on the basis of reviews of country penal codes and governmental and nongovernmental reports.
Data Analysis
For individual and interpersonal factors, we calculated the proportion of the sample reporting each characteristic by engagement in transactional sex. We calculated the Cronbach α for the Center for Epidemiologic Studies Depression scale, CAGE, and the Sexual Compulsivity Scale. We examined bivariate associations between individual-level and country-level factors and engagement in transactional sex with a 2-level logistic regression model with a random intercept, accounting for clustering by country of residence (using Stata’s XTMELOGIT procedure). We used a multivariable 2-level logistic regression model with random intercepts to assess odds of engagement in sex work, adjusting for both individual- and country-level risk factors.
We did not use any statistical model selection procedures to build the model, and we retained all initial variables considered in the final model. A second multivariable 2-level model restricted the sample only to men who reported transactional sex exclusively with male clients. However, the results of the multivariable model did not change substantively; therefore, we have not reported these results. We employed a complete case analysis for all analyses. We conducted all analyses in Stata 12.1 (StataCorp, College Station, TX).
RESULTS
A total of 202 837 individuals opened the recruitment e-mail and 46 744 (23.0%) of these men proceeded to the study Web site. Of those viewing the study information and consent form, 29 621 (63.7%) consented to and subsequently participated in the study. Of these, 24 051 (81.2%) respondents answered the question regarding engagement in transactional sex, of whom 1732 (7.2%) reported having been paid in the past 12 months to engage in sexual activity; 1627 (93.9%) reported having only male paying partners. The majority of participants (97.8%) reported male transactional partners, and 38 (2.2%) reported no male commercial partners. The Center for Epidemiologic Studies Depression scale, CAGE, and the Sexual Compulsivity Scale showed moderate to high internal consistency in this sample (0.82%, 0.72%, and 0.91%, respectively).
Figure 1 shows the prevalence of being paid for sexual intercourse in the past 12 months in each of the 17 countries, which differed significantly by country of residence (P < .001), ranging from a high of 11.6% in Bolivia to a low of 2.3% in Paraguay. Table 1 lists sociodemographic and psychosocial factors and self-reported HIV and STI prevalence in the past year by engagement in transactional sex in the past year. Men who engaged in transactional sex tended to be younger than were those who did not (aged 26.6 vs 30.9 years), were less likely to have completed a university education (70.5% vs 82.1%), were more likely to have been diagnosed with an STI (21.5% vs 14.0%) or HIV (11.2% vs 8.5%), were more likely to have used hard drugs during sexual intercourse (27.0% vs 11.9%), and were more likely to have a history of CSA (75.7% vs 58.2%) and IPV (53.9% vs 33.8%).
FIGURE 1—
Proportion of participants who self-report engagement in transactional sex divided into quartiles: Latin America, 2012.
Note. Proportion is the number of participants who reported transactional sex divided by the total number of participants who responded to the question by country. Black is the highest quartile (> 7.9% to 13.3%), dark gray the third quartile (> 6.5% to 7.9%), medium gray the second quartile (> 5.8% to 6.5%), and light gray the first quartile (2.3% to 5.8%).
TABLE 1—
Descriptive Characteristics of Participants Who Did (n = 1732) and Those Who Did Not (n = 22 319) Report Engaging in Transactional Sex: Latin America, 2012
| Characteristics | Exchanged Sexual Intercourse for Money or Goods in Previous 12 Months, No. (%) | Did Not Exchange Sexual Intercourse for Money or Goods in Previous 12 Months, No. (%) | Overall, No. (%) |
| Age, y | 26.6 (7.3) | 30.9 (9.4) | 30.5 (9.3) |
| Urban dwelling | 1 644 (94.9) | 21 438 (96.1) | 23 082 (96.0) |
| Sexual orientation | |||
| Homosexual or gay | 1 251 (73.1) | 17 057 (77.0) | 18 308 (76.7) |
| Bisexual | 405 (23.7) | 4 294 (19.4) | 4 699 (19.7) |
| Heterosexual | 9 (0.5) | 147 (0.7) | 156 (0.7) |
| Unsure | 47 (2.8) | 658 (3.0) | 705 (3.0) |
| Currently dating | 933 (54.3) | 11 028 (49.8) | 11 961 (50.1) |
| University education | 1 154 (70.5) | 17 618 (82.1) | 18 772 (81.3) |
| Income | |||
| No income | 175 (10.5) | 1 677 (7.8) | 1 852 (8.0) |
| Low income | 220 (13.2) | 1 815 (8.4) | 2 035 (8.8) |
| Middle income | 1 181 (70.6) | 16 126 (74.9) | 17 307 (74.6) |
| High income | 97 (5.7) | 1 901 (8.8) | 1 997 (8.6) |
| Had physical examination in past year | 1 131 (65.5) | 14 451 (65.0) | 15 582 (65.1) |
| Ever tested for HIV | 1 256 (74.1) | 16 340 (74.5) | 17 596 (74.5) |
| Diagnosed with STI in past year | 357 (21.5) | 3 020 (14.0) | 3 377 (14.5) |
| Ever diagnosed with HIV | 186 (11.2) | 1 849 (8.5) | 2 035 (8.7) |
| Any unprotected anal intercourse | 851 (65.1) | 8 674 (52.9) | 9 525 (53.8) |
| Hard drug use during sexual intercourse | 423 (27.0) | 2 436 (11.9) | 2 859 (13.0) |
| Alcohol dependency | 347 (22.4) | 3 080 (15.3) | 3 427 (15.8) |
| Depression | 502 (32.5) | 5 726 (28.3) | 6 228 (28.6) |
| Childhood sexual abuse | 1 146 (75.7) | 11 516 (58.2) | 12 662 (59.5) |
| Intimate partner violence | 808 (53.9) | 6 700 (33.8) | 7 508 (35.2) |
| Sexual compulsivity | 400 (26.9) | 2 816 (14.4) | 3 216 (15.3) |
Note. STI = sexually transmitted infection.
Table 2 lists bivariate and multivariable multilevel logistic regression models with a random intercept for country of residence assessing factors associated with engagement in transactional sex. In the multivariable model, which included all individual and interpersonal level factors assessed in the bivariate models, country-level unemployment was significantly associated with engagement in transactional sex (adjusted odds ratio [AOR] = 1.07; 95% CI = 1.00, 1.14; P = .035). Legal protection against employment discrimination was not associated with engagement in transactional sex (AOR = 1.08; 95% CI = 0.85, 1.36; P = .53).
TABLE 2—
Bivariate and Multivariable Analyses Predicting Having Engaged in Transactional Sex in the Past 12 Months: Latin America, 2012
| Multivariable Model |
||
| Characteristics | OR (95% CI) | AOR (95% CI) |
| Country-level predictors | ||
| Unemployment (n = 24 051) | 1.07 (1.00, 1.15) | 1.07 (1.00, 1.14) |
| Legal protection against employment discrimination (n = 24 051) | 1.27 (0.97, 1.68) | 1.08 (0.85, 1.36) |
| Individual-level predictors | ||
| Age per year (n = 24 051) | 0.94 (0.93, 0.94) | 0.94 (0.93, 0.95) |
| Urban vs rural (n = 24 051) | 0.75 (0.60, 0.94) | 0.92 (0.63, 1.35) |
| Sexual orientation (n = 23 868) | ||
| Homosexual or gay (Ref) | 1.00 | 1.00 |
| Bisexual | 1.30 (1.15, 1.46) | 1.51 (1.26, 1.80) |
| Heterosexual | 0.88 (0.45, 1.73) | 1.09 (0.33, 3.60) |
| Unsure | 0.97 (0.72, 1.32) | 0.97 (0.61, 1.54) |
| Currently dating or in a relationship (n = 23 885) | 1.20 (1.09, 1.33) | 1.19 (1.02, 1.38) |
| University or more education (n = 23 094) | 0.50 (0.45, 0.56) | 0.67 (0.56, 0.80) |
| Income (n = 23 191) | ||
| No income (Ref) | 1.00 | 1.00 |
| Low income or class | 1.19 (0.97, 1.47) | 1.50 (1.10, 2.06) |
| Middle income or class | 0.73 (0.62, 0.86) | 1.05 (0.81, 1.36) |
| High income or class | 0.49 (0.38, 0.63) | 0.78 (0.53, 1.14) |
| Had physical examination in past year (n = 23 954) | 1.02 (0.92, 1.13) | 1.11 (0.94, 1.31) |
| Ever tested for HIV (n = 23 617) | 1.00 (0.89, 1.12) | 1.21 (1.00, 1.47) |
| Diagnosed with STI in the past year (n = 23 222) | 1.67 (1.48, 1.89) | 1.33 (1.11, 1.59) |
| Ever diagnosed with HIV (n = 23 455) | 1.36 (1.16, 1.60) | 1.33 (1.04, 1.69) |
| Any unprotected anal intercourse (n = 17 710) | 1.65 (1.46, 1.85) | 1.30 (1.11, 1.53) |
| Hard drug use during sexual intercourse (n = 20 429) | 2.76 (2.45, 3.12) | 2.32 (1.94, 2.77) |
| Alcohol dependencya (n = 21 730) | 1.60 (1.41, 1.81) | 1.12 (0.94, 1.35) |
| Depressionb (n = 21 767) | 1.22 (1.09, 1.37) | 0.80 (0.68, 0.95) |
| Sexual compulsivityc (n = 21 006) | 2.18 (1.93, 2.46) | 1.77 (1.49, 2.11) |
| Interpersonal predictors | ||
| Childhood sexual abuse (n = 21 291) | 2.23 (1.98, 2.52) | 1.75 (1.48, 2.06) |
| Intimate partner violence in past 5 y (n = 21 338) | 2.28 (2.05, 2.53) | 1.68 (1.45, 1.95) |
Note. AOR = adjusted odds ratio; CI = confidence interval; OR = odds ratio; STI = sexually transmitted infection. n represents the number of individuals included in our bivariate analysis; numbers change because of attrition.
Measured with the 4-item CAGE questionnaire,26 with a score of ≥ 2 indicating problematic alcohol use.
Measured with the Center for Epidemiological Studies Depression Scale 10,24 with a score of ≥ 10 suggesting clinical depression.
Measured with the Sexual Compulsivity Scale27 with a score of ≥ 24 suggesting high sexual compulsivity.
Low income compared with no income was significantly associated with increased odds of engagement in transactional sex (AOR = 1.50; 95% CI = 1.10, 2.06; P = .01). Other sociodemographic factors that were significantly associated with engagement in transactional sex in the multivariable model included younger age (AOR = 0.94; 95% CI = 0.93, 0.95; P < .001) and less than university education (AOR = 0.67; 95% CI = 0.56, 0.80; P < .001). Bisexual orientation (vs homosexual or gay, AOR = 1.51; 95% CI = 1.26, 1.80; P < .001) and currently dating or being in a relationship (AOR = 1.19; 95% CI = 1.02, 1.38; P = .03) were significantly associated with increased odds of engagement in transactional sex.
A self-reported HIV infection (AOR = 1.33; 95% CI = 1.04, 1.69; P = .02) and diagnosis of an STI in the past year (AOR = 1.33; 95% CI = 1.11, 1.59; P = .002) were each associated with increased odds of engagement in transactional sex in the multivariable model. A history of having an HIV test was significantly associated with increased odds of transactional sex (AOR = 1.21; 95% CI = 1.00, 1.47; P = .048). Sexual risk behaviors, including any unprotected anal intercourse in the past 3 months (AOR = 1.30; 95% CI = 1.11, 1.53; P = .001) and hard drug use during sexual intercourse (AOR = 2.32; 95% CI = 1.94, 2.77; P < .001) were associated with increased odds of engaging in transactional sex.
Psychosocial variables that were associated with increased odds of engagement in transactional sex included sexual compulsivity (AOR = 1.77; 95% CI = 1.48, 2.11; P < .001), an experience of physical, psychological, or sexual IPV in the past 5 years (AOR = 1.68; 95% CI = 1.45, 1.95; P < .001), and a history of CSA (AOR = 1.75; 95% CI = 1.48, 2.06; P < .001). Additionally, depression was associated with reduced odds of engagement in transactional sex (AOR = 0.80; 95% CI = 0.68, 0.95; P = .01). Sensitivity analyses treating depression, alcohol use, and sexual compulsivity as continuous variables did not qualitatively change results.
DISCUSSION
This is the first study to our knowledge to assess multilevel factors associated with engagement in transactional sex among MSM in Latin America. Overall, 7.2% of MSM using a social and sexual partner-seeking Web site in 17 Latin American countries reported being paid for sex practices in the past 12 months, ranging from 2.3% in Panama to 11.6% in Bolivia. A lower percentage of MSM reported engagement in transactional sex than has been previously shown in other cohorts, which may be because members of this site needed to be computer literate and usually paid a membership fee. Studies in El Salvador and Ecuador reported prevalence of transactional sex at 23.0%3 and 18.4%,4 respectively. Both used respondent-driven sampling, which could oversample higher-risk individuals if the seeds are higher risk or if there was a higher prevalence of engagement in transactional sex among seeds selected. Our sample may have oversampled individuals with higher socioeconomic status because of our Internet-based recruitment method, which may result in differences if previous samples have focused on individuals with lower socioeconomic status.
Previous studies have shown that reasons for MSM engaging in transactional sex are varied and include economic pressures as well as pleasure and excitement, especially in regions where MSM’s behavior is highly stigmatized.6,13,14 Respondents in countries with higher unemployment rates had increased odds of engaging in transactional sex. Country-level unemployment as a driver of transactional sex may be understood according to the political economy theory of health. Unequal resource allocation, in the form of economic opportunities, may result in individuals being driven into sex work because of economic need.
Among MSM, economic motivations have been shown to be associated with engagement in transactional sex.31 Our results indicate that in Latin America unemployment is associated with an increase in transactional sex among MSM. Latin America has experienced a significant recent increase in urban-to-rural migration,23 and urbanization may be higher in Latin America than in any other region of the world.32 A lack of economic opportunity in increasingly populous cities coupled with an increased market for transactional sex may be a strong structural driver for MSM to engage in transactional sex.
We did not collect information on current employment status; transactional sex may have been the primary or sole source of income for these men or may have been supplementary income. Regardless, these results provide support for the assertion that structural-level economic factors play a role in the HIV epidemic among MSM in Latin America. Future work should consider the role of economic opportunity and disadvantage among MSM for the development of economic interventions that may help reduce vulnerability to HIV.
Numerous psychosocial factors were associated with engagement in transactional sex, including a history of CSA, IPV (psychological, physical, or sexual) in the past 5 years, and sexual compulsivity. The majority of participants who reported engagement in transactional sex reported a history of CSA, which was at a higher rate than was that of MSM who did not report transactional sex. High rates of CSA, which has been shown to be associated with HIV, have been reported among both sex workers and MSM.33,34 In the United States, Latino MSM have been shown to have higher rates of CSA than do non-Latino MSM.35 A history of CSA is associated with adverse mental health sequelae, including depression and substance use, which can lead to increased sexual risk and HIV aquisition.15,36 The high prevalence of CSA among men who engage in transactional sex may therefore result in increased vulnerability to HIV.
We also noted an increased prevalence of IPV among men who engaged in transactional sex. Sex workers experience a high burden of partner violence, from both commercial and noncommercial partners, and among female sex workers IPV has been shown to increase vulnerability to HIV.16 These factors may also overlap and in growing combination result in greater risk behavior. HIV prevention programs should consider the role of these psychosocial factors in this population, and appropriate linkage to mental health care is an essential component of a comprehensive HIV prevention program.
Psychosocial factors can increase vulnerability to HIV through several mechanisms, including increased sexual risk taking and reduced condom negotiation. Participants who had engaged in transactional sex were more likely to have had sexual intercourse without a condom in the past 3 months and were more likely to use hard drugs during sexual intercourse.
We did not collect information on whether partners in the past 3 months were commercial or noncommercial, so we were not able to compare condom use patterns between commercial and noncommercial partners. However, unprotected anal intercourse was common, which increases vulnerability to HIV regardless of whether partners are commercial or noncommercial. Furthermore, the increased prevalence of drug use during sexual intercourse among men who engage in transactional sex could reduce the ability to negotiate condom use and increase risky sexual behavior.37,38
Participants who reported engagement in transactional sex had a higher self-reported HIV prevalence (11.2% vs 8.5%), which remained significant after adjusting for multiple other factors. However, participants who reported engagement in transactional sex had more frequently been tested for HIV, so it is possible that this finding reflects differential HIV testing practices. Previous studies in Latin America have reported an HIV prevalence among men who identify as sex workers ranging from 11.0% in Argentina to more than 20.0% in Peru, Uruguay, and Mexico.6,9,10,39–41 In Peru, HIV prevalence was 15.3% among men who reported exchanging sexual intercourse for money, 24.5% among those who identified as being a sex worker, and 13.9% among all MSM in the study.5 We did not differentiate between occasional engagement in transactional sex and regular sex work, which could explain the overall HIV prevalence we noted that was lower than was that of previous work. Future research should consider HIV prevention strategies among men who engage in transactional sex and their sexual partners, including both paying partners and intimate partners.
Limitations
Our results must be considered in the context of several limitations. This study had a convenience sample of respondents to an e-mail sent via a social and sexual partner-seeking Web site for MSM. The response rate was consistent with other multicountry studies using online sampling.42 However, to our knowledge, this study has the largest sample of MSM from this region ever surveyed. Because it is not possible to assess how respondents and nonrespondents differed, we cannot assess whether there were systematic differences between those who responded and those who chose not to. Although a fair amount of attrition occurred among our participants, similar work using large-scale Internet-based methodology had comparable rates of attrition.42
Although we attempted to minimize repeat responses from the same individuals by not allowing more than 1 response from a particular Internet provider address, it is possible that there may have been duplicate submissions. Previous work has shown that repeat submissions do occur in Internet-based sexual health research, but this happens much more frequently when there are incentives for completing the survey.43 We did not provide any incentives, and we believe repeat submissions were minimized.
We classified income into 4 categories (no income, low, medium, and high) to improve comparability of income level across diverse countries. However, this measure may have been imprecise and may not have fully captured socioeconomic status. Finally, we were unable to classify the frequency with which participants engaged in transactional sex, whether they identified as a sex worker, and whether they exchanged sexual intercourse for money, drugs, or other goods. There may be important differences between these groups that we did not detect. Despite these limitations, to our knowledge this is the first analysis assessing factors that influence engagement in transactional sex among MSM in Latin America.
Conclusions
Documenting the prevalence of engagement in transactional sex and assessing multilevel factors associated with this is important for understanding the scope of transactional sex among MSM and for understanding how best to develop interventions among this population. Country-level development, in terms of job availability, may affect the need for MSM to engage in transactional sex, which in turn may increase vulnerability to HIV. More research is needed to better understand the multifaceted and multilevel factors associated with engagement in transactional sex among MSM in Latin America. A better understanding of these factors will allow the development of more effective HIV prevention programs that address both behavioral and structural risk factors.
Acknowledgments
This work was supported by the National Institute of Allergy and Infectious Disease (National Research Service Award [NRSA] grant T32 AI007535 to C. E. O.); the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NRSA grant T32 HD049339 to A. P. B.); and the National Institute on Drug Abuse, National Institutes of Health (awards R21DA035113 and R21DA033720 to M. J. M., K. B. B., and K. H. M.).
Note. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The sponsors did not have a role in designing and conducting the study; collection, management, analysis, and interpretation of the data; or preparation, review, and approval of the article.
Human Participant Protection
This study was approved by the institutional review board of the Fenway Institute.
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