Introduction
Female sex workers (FSWs) are highly vulnerable to HIV and other sexually transmitted infections (STIs), particularly in low- to middle-income countries.1 In a review of HIV in Mexico, del Rio and Sepulveda2 concluded that from 1980 to 2000, HIV seroprevalence among FSWs was less than 1%. However, more recent estimates in Tijuana and Ciudad (Cd.) Juarez yielded HIV prevalences ranging from 6% among non-injecting FSWs to 12% in FSW-IDUs.3 In contrast to HIV, STI prevalence among FSWs in Mexico has been high for decades. In the late 1990s, the prevalences of active syphilis, chlamydia, and gonorrhea among FSWs in Mexico City were 23.7, 12.8 and 11.6%, respectively;4 the prevalence of HSV-2 was 60%.5 Among FSW-IDUs residing in Tijuana or Cd. Juarez, 50% had at least one active STI, compared to 25% among non-IDU FSWs.3
The present study used a social ecological framework to explore the prevalence of HIV and other STIs and their correlates among 1 092 FSWs in 13 sites across Mexico. The Social Ecological Model describes five levels of influence on behavior, including individual (e.g., education), interpersonal (e.g., substance use with clients), institutional (e.g., work venue), community (e.g., poverty, access to health care), and policy (e.g., policing).6Given recent emphasis in prevention research on the “risk environment”,7 which includes all levels of influence described in our conceptual model, we hypothesized that site-specific, community-level, municipal characteristics might explain variations in HIV/STI prevalence independent of individual-, interpersonal-, institutional, and policy-level factors. We also hypothesized that settings with fewer resources and less-educated populations would have FSWs who were riskier. The availability in Mexico of two government-monitored indices, the Human Development Score (which comprises life expectancy, education, income, and other factors) and the Marginalization Index (an indicator of decreased access to basic public services and greater poverty), provided us with ready-made potential predictor variables related to the risk environments of the sites studied. If correlations could be found, the findings could help rationalize the allocation of limited resources for HIV/STI prevention and treatment.
Materials and methods
Data for this analysis were obtained from baseline interviews and HIV/STI screenings of 1092 FSWs enrolled in the Mujer Segura implementation study.8 This hybrid type-2 study simultaneously tested the efficacy of the Mujer Segura safer-sex intervention and a train-the-trainer implementation strategy at multiple sites.9 The protocol was reviewed and approved by the Institutional Review Boards of the University of California, San Diego; Universidad Autónoma de Ciudad Juárez, which provided training to staff; and the Mexican Foundation for Family Planning (Mexfam), which operates the clinics at which the study was carried out. All participants provided written informed consent.
Study sites
The study was carried out from 2011 to 2015 at 13 community-based clinics operated by Mexfam, which is a non-profit, non-governmental organization, headquartered in Mexico City, that operates sexual and reproductive health programs in 22 states in Mexico. An initial list of 23 sites was drawn up that met minimum capacity criteria and reflected a broad geographic distribution.8 Sites were intentionally chosen to represent a cross-section of clinic sizes (large versus small) and locations (urban versus rural). From the initial list, 12 sites were randomly selected for participation. A thirteenth site was added after the publication of the protocol description.
Eligibility criteria
Eligibility criteria from the original efficacy trial were retained.8 Participants had to be biologically female; be at least 18 years of age; be able to speak Spanish (which cannot be assumed in some of Mexico’s more rural, indigenous areas); have no plans to move out of the area for at least 6 months; self-identify as a female sex worker; report having traded sex for drugs, money, shelter, or other material benefit within the previous two months; have had unprotected vaginal or anal sex with a client at least once during the previous two months; have no previous HIV-positive test result; agree to be tested for HIV and STIs at baseline and at six-month follow-up; agree to accept free STI treatment at baseline (to distinguish prevalent from incident cases at follow-up); and be willing to provide informed consent.
Recruitment
At each site, outreach workers employed by Mexfam adopted a time-location sampling approach,10 whereby they compiled a map of sex work venues (e.g., bars, brothels, shooting galleries, street corners) in red light districts and other areas with high concentrations of FSWs. Women who appeared to be engaged in sex work were approached and engaged in conversation to assess study interest and eligibility. Among FSWs who met eligibility criteria, less than 1% refused to participate in the study.
Data collection
Participants were reimbursed the equivalent of $30 U.S. for completing an interviewer-administered, computerized questionnaire and brief counseling session. Sociodemographic and personal questions included age, educational attainment in years, and birthplace. Sexual risk behaviors included numbers of clients and of unprotected sex acts with clients during the previous four months. Drug use behaviors included lifetime and recent consumption and injection of various drugs. Alcohol use was assessed with the AUDIT-C, which reliability identifies drinkers who are hazardous or “at risk”.11 Data on the demographic, social, and economic characteristics of the municipalities hosting the participating clinics were derived from reports published by the Mexican National Institute for Statistics and Geography (INEGI).12
Assessment of HIV and STIs
Participating sex workers were screened for HIV using the Advanced Quality Rapid Anti-HIV (1 and 2) test. Reactive samples were shipped to the San Diego County Health Department Laboratory and tested using HIV-1, 2 serum antibody enzyme immunoassay (EIA) and indirect fluorescent antibody (IFA) tests. FSWs were also screened for syphilis, chlamydia, and gonorrhea. Syphilis serology included a rapid diagnostic screening for the qualitative detection of antibodies to Treponema pallidum in blood. All reactive samples were shipped to the San Diego County lab and subjected to the rapid plasma reagin (RPR) test and the T. pallidum particle agglutination assay (TPPA). Urine samples were collected using the Gen-Probe Aptima Combo 2W Assay for C. trachomatis and N. gonorrhoeae. HIV/STI test results were provided to participants by nurses within two weeks of testing. Those testing HIV-positive were referred to their municipal clinic for free medical care, while those who tested positive for another STI were treated at the study site. HIV reporting is mandatory throughout Mexico, and requirements are consistent across states. The reporting requirement was explained in the consent form along with possible adverse consequences (e.g., loss of license to practice sex work).
Statistical analyses
Due to the small number of HIV+ cases, we chose combined HIV/STI status (i.e., any of the measured STIs including HIV) as our binary dependent variable. Logistic regressions via generalized estimating equations were performed to identify site and participant characteristics related to HIV/STI prevalence. Since this is a multisite study, the data are heterogeneous, inducing intra-site correlation. Site was used as a cluster variable with an exchangeable correlation structure, where the correlation between any two observations within any particular site was assumed to be the same. Our model building approach involved conducting univariate analyses of all variables that were both conceptually relevant and important in the literature. Variables that yielded a significance <= 0.10 in the univariate analyses were considered for the multivariable model based on both conceptual and statistical relevance. The alpha for entrance into the multivariate model was chosen based on measurement error and potential lack of power considerations. To obtain the most parsimonious multivariate model, goodness of fit was conducted by comparing values of the quasi-likelihood under the Independence Model Information Criterion (QIC) and by ruling out interactions and multicollinearity. All the variables in the final multivariate model are significant at the 5% significance level while accounting for other variables in the model. Because site was not used as a fixed covariate, it does not appear in the final multivariate model.
Results
Site characteristics and participant risk profiles
Sites were spread across eight Mexican states (table I ). The average population of the metropolitan areas hosting the participating clinics was 426 608 (range 14 751-1 495 189). Residents’ average annual per capita income was 10 218 U.S. (range 4 045-15 117).Types of venue for sex work varied widely between sites, which ranged from urban (Mexico City, Guadalajara) to rural (Naranjos, Tlapa). The legal status of sex work varied from tolerated (Mexico City), to municipally sanctioned with specially constructed facilities (Tuxtla), to illegal (Ciudad Neza).Table II presents demographic, sex risk, and drug and alcohol risk variables for each study site.
Site | State | Total population | UNDP Town size classification | Human development (HD) index (0-1) | Level of HD (per UNDP) | HD index rank* | Annual per capita income (US$) | Degree of marginalization | M Index (0-100) | M Index Rank* | Years of education | |||||||||||
01 Revolución | Delegación Cuauhtémoc | 531 831 | Urban large | 0.8921 | High | 23 | 15 117 | Medium low | 4.6 | 13 | 11.32 | |||||||||||
02 Ciudad Neza | México | 1 110 565 | Metropolitan | 0.8621 | High | 103 | 10 137 | Medium low | 8.9 | 114 | 9.5 | |||||||||||
03 Huajuapan | Oaxaca | 69 839 | Mixed | 0.8248 | High | 333 | 6 781 | Low | 17.12 | 547 | 8.58 | |||||||||||
04 Iguala | Guerrero | 140 363 | Urban large | 0.8343 | High | 261 | 8 346 | Low | 18.17 | 78 | 9.07 | |||||||||||
05 Ixtaltepec | Oaxaca | 14 751 | Mixed | 0.8097 | High | 497 | 8 118 | Medium | 21.73 | 517 | 7.29 | |||||||||||
06 Naranjos | Veracruz | 27 548 | Urban medium | 0.8453 | High | 189 | 9 106 | Low | 15.53 | 197 | 8.76 | |||||||||||
07 Guadalajara | Jalisco | 1 495 189 | Metropolitan | 0.8882 | High | 34 | 14 281 | Medium low | 5.25 | 125 | 9.99 | |||||||||||
08 San Luis de la Paz | Guanajuato | 115 656 | Mixed | 0.7418 | Medium | 1 487 | 5 721 | Medium | 25.34 | 16 | 6.76 | |||||||||||
09 San Luis Potosí | San Luis Potosí | 772 604 | Urban large | 0.9011 | High | 14 | 16 758 | Medium low | 7.02 | 58 | 10.33 | |||||||||||
10 Tlapa | Guerrero | 81 4194 | Urban medium | 0.7174 | Medium | 1 788 | 4 045 | High | 33.63 | 54 | 6.74 | |||||||||||
11 Veracruz | Veracruz | 552 156 | Urban large | 0.8848 | High | 41 | 14 859 | Medium low | 9.12 | 209 | 9.79 | |||||||||||
12 Tepeji del Río | Hidalgo | 80 612 | Mixed | 0.8295 | High | 289 | 9 063 | Low | 15.98 | 66 | 8.22 | |||||||||||
13 Tuxtla | Chiapas | 553 374 | Urban large | 0.855 | High | 140 | 10 502 | Medium low | 12.48 | 118 | 10.03 | |||||||||||
Mean: | 426 608.23 | Mean: | 10 218 |
*Out of 2 546 municipalities in Mexico
UNDP: United Nations Development Programme
Town Size Classifications: Metropolitan: over 50% of the population living in cities of over one million inhabitants
Urban Large: over 50% of the population lives in towns between 100 thousand and less than one million inhabitants
Urban Medium: more than 50% of the population lives in towns between 15 000 and less than 100 000 inhabitants
Semi-urban: more than 50% of the population lives in towns from 2 500 to less than 15 thousand inhabitants
Rural: over 50% of the population lives in towns with less than 2 500 inhabitants
Mixed: The population is distributed in the above categories without a percentage greater than or equal to 50% population
Source: Sistema Nacional de Información Municipal12
Site | Age Mean (SD) | Years of education completed Mean (SD) | Married or common law N (%) | Has children N (%) | Age when first traded sex Mean (SD) | Years spent as a sex worker Mean (SD) | Number of male clients *Mean (SD) | % sex acts w/o condom‡Mean (SD) | Ever used heroin N (%) | Ever used meth N (%) | Ever used cocaine N (%) | AUDIT hazardous drinking N (%) | Used alcohol with client‡ N (%) | |||||||||||||
01 | 39.9 (11.7) | 6.5 (3.4) | 19 (26.8) | 67 (94.4) | 28.5 (10.6) | 11.7 (10.1) | 164.8 (179.7) | 30 (20) | 2 (2.8) | 1 (1.4) | 17 (23.9) | 22 (31.0) | 18 (25.4) | |||||||||||||
02 | 34.5 (9.0) | 7.9 (2.4) | 21 (25.9) | 78 (96.3) | 29.2 (8.0) | 5.3 (5.4) | 66.7 (87.9) | 60 (30) | 4 (4.9) | 3 (3.7) | 23 (28.4) | 74 (91.4) | 75 (92.6) | |||||||||||||
03 | 30.5 (7.8) | 7.3 (3.2) | 25 (29.4) | 75 (88.2) | 26.4 (7.1) | 4.2 (4.5) | 115.6 (118.7) | 50 (30) | 2 (2.4) | 8 (9.4) | 31 (36.5) | 69 (81.2) | 62 (72.9) | |||||||||||||
04 | 30.5 (7.7) | 5.8 (3.1) | 21 (25.9) | 75 (93.8) | 25.2 (6.6) | 5.3 (5.8) | 252.8 (209.5) | 50 (30) | 2 (2.5) | 0 (0) | 39 (48.8) | 77 (96.3) | 76 (95.0) | |||||||||||||
05 | 35.1 (8.2) | 6.6 (3.4) | 15 (18.5) | 75 (92.6) | 27.5 (7.7) | 7.6 (7.6) | 167 (229.1) | 40 (30) | 0 (0) | 0 (0) | 18 (22.2) | 72 (88.9) | 40 (49.4) | |||||||||||||
06 | 32.6 (8.9) | 6.9 (2.9) | 21 (24.4) | 76 (88.4) | 27.5 (8.5) | 5.0 (4.9) | 56.4 (107) | 60 (30) | 0 (0) | 1 (1.6) | 16 (18.6) | 80 (93.0) | 74 (86.1) | |||||||||||||
07 | 34.5 (10.0) | 6.3 (3.4) | 29 (33.0) | 84 (95.5) | 28.7 (9.9) | 5.9 (6.7) | 337.6 (235.9) | 30 (20) | 5 (5.7) | 9 (10.2) | 24 (27.3) | 43 (48.9) | 33 (37.5) | |||||||||||||
08 | 30.6 (8.9) | 7.2 (3.4) | 36 (40.0) | 70 (77.8) | 23.3 (6.4) | 7.2 (6.3) | 421.3 (135.2) | 50 (20) | 0 (0) | 0 (0) | 4 (4.4) | 66 (73.3) | 48 (53.3) | |||||||||||||
09 | 32.9 (10.1) | 8.0 (3.7) | 22 (26.2) | 74 (88.1) | 27.0 (8.7) | 5.9 (7.2) | 408.1 (302.9) | 20 (20) | 0 (0) | 1 (1.2) | 16 (19.1) | 40 (47.6) | 13 (15.5) | |||||||||||||
10 | 29.2 (8.7) | 5.8 (3.6) | 14 (16.1) | 72 (82.8) | 25.0 (7.6) | 4.2 (4.7) | 151.3 (191.6) | 40 (20) | 3 (3.5) | 1 (1.2) | 29 (33.3) | 80 (92.0) | 77 (88.5) | |||||||||||||
11 | 28.3 (8.3) | 8.6 (2.7) | 21 (25.0) | 52 (61.9) | 21.5 (5.1) | 6.7 (7.0) | 480 (232.7) | 60 (30) | 1 (1.2) | 0 (0) | 5 (6.0) | 53 (63.1)) | 38 (45.2) | |||||||||||||
12 | 33.4 (9.6) | 8.2 (2.5) | 25 (28.4) | 78 (88.6) | 27.6 (8.4) | 5.9 (6.4) | 115.9 (176.3) | 60 (30) | 0 (0) | 7 (8.0) | 8 (9.1) | 80 (90.9) | 81 (92.1) | |||||||||||||
13 | 36.8 (10.4) | 6.2 (4.0) | 29 (33.3) | 79 (90.8) | 28.5 (7.3) | 8.3 (7.0) | 518.1 (289.8) | 30 (20) | 0 (0) | 1 (1.2) | 14 (16.1) | 48 (55.2) | 28 (32.2) | |||||||||||||
Overall | 32.9 (9.7) | 7.0 (3.3) | 298 (27.3) | 955 (87.5) | 26.6 (8.2) | 6.3 (6.8) | 252.7 (255.8) | 40 (30) | 19 (1.7) | 32 (2.9) | 244 (22.3) | 804 (73.6) | 663 (60.7) |
*in the previous six months
‡in the previous month
Site Key (names of Mexfam clinics): 01 Revolución, 02 Ciudad Neza, 03 Huajuapan, 04 Iguala, 05 Ixtaltepec, 06 Naranjos, 07 Guadalajara, 08 San Luis de la Paz, 09 San Luis Potosí, 10 Tlapa, 11 Veracruz, 12 Tepeji del Río, 13 Tuxtla
Percentages may reflect denominators smaller than the N value given in the column head. These discrepancies are due to missing data
Variations in HIV/STI prevalence
The overall prevalence of HIV among the total sample was 0.4%, ranging from zero to 1.4% at the 13 sites (table III). The prevalence of other STIs varied widely: syphilis, 7.8% (range 0 to 17.2%); chlamydia, 15.3% (range 5.7 to 32.2%); gonorrhea, 2.9% (range 0 to 13.8); and any STI, 23% (range 9.9 to 46%).
Site | N | HIV (%) | Gonorrhea (%) | Chlamydia (%) | Syphilis titer (%) | Any syphilis (%) | HIV or any STI | |||||||
01 Revolución | 71 | 1 (1.4) | 2 (2.9) | 9 (12.9) | 3 (4.3) | 10 (14.3) | 20 (29.0) | |||||||
02 Ciudad Neza | 81 | 0 (0) | 2 (2.5) | 7 (8.6) | 1 (1.2) | 4 (4.9) | 12 (14.1) | |||||||
03 Huajuapan | 85 | 0 (0) | 0 (0) | 14 (16.5) | 1 (1.2) | 4 (4.7) | 18 (21.2) | |||||||
04 Iguala | 80 | 0 (0) | 5 (6.3) | 24 (30) | 3 (3.8) | 5 (6.3) | 27 (33.8) | |||||||
05 Ixtaltepec | 81 | 1 (1.2) | 4 (4.9) | 10 (12.3) | 1 (1.2) | 11 (13.6) | 22 (27.2) | |||||||
06 Naranjos | 86 | 0 (0) | 0 (0) | 19 (22.1) | 1 (1.2) | 6 (7) | 25 (29.1) | |||||||
07 Guadalajara | 88 | 1 (1.1) | 0 (0) | 7 (8) | 3 (3.5) | 13 (15.1) | 18 (20.7) | |||||||
08 San Luis de la Paz | 90 | 0 (0) | 2 (2.2 | 10 (11.1) | 0 (0) | 0 (0) | 12 (13.3) | |||||||
09 San Luis Potosí | 84 | 1 (1.2) | 3 (3.6) | 9 (10.7) | 6 (7.2) | 13 (15.7) | 21 (25.3) | |||||||
10 Tlapa | 87 | 0 (0) | 12 (13.8) | 28 (32.2) | 8 (9.2) | 15 (17.2) | 40 (46.0) | |||||||
11 Veracruz | 84 | 0 (0) | 0 (0) | 7 (8.6) | 0 (0) | 1 (1.2) | 8 (9.9) | |||||||
12 Tepeji del Río | 88 | 0 (0) | 0 (0) | 18 (20.5) | 0 (0) | 0 (0) | 18 (20.5) | |||||||
13 Tuxtla | 87 | 0 (0) | 1 (1.1) | 5 (5.7) | 0 (0) | 3 (3.4) | 9 (10.3) | |||||||
Totals | 1 092 | 4 (0.4) | 31 (2.9) | 167 (15.3) | 27 (2.5) | 85 (7.8) | 250 (23.0) |
Univariate associations with HIV/STI
Univariate analyses suggest that municipalities with high Human Development Scores had a 33% decrease in the odds of combined HIV/STI prevalence compared to those with medium scores (OR= 0.67; 95%CI: 0.47, 0.96, p=.0032). Furthermore, the odds of prevalent HIV/STIs increased by 30% for every 1-standard deviation increase in the municipal Marginalization Index (OR= 1.3; 95%CI: 1.28, 1.50, p= .0003). Also, having fewer years of education was associated with HIV/STI prevalence (OR= 0.90; 95%CI: 0.86, 0.94, p= .000). FSWs who reported that their spouse had been diagnosed or treated for an STI in the past 6 months were 2.6 times more likely to have ever tested positive for an STI or HIV (OR= 2.61; 95%CI: 1.22, 5.60, p= .014). FSWs who could afford to buy condoms had a lower odds of an STI or HIV (OR= 0.65; 95%CI: 0.49, 0.88, p= .005) as did FSWs who reported that most or all clients were from elsewhere than Mexico (OR= 0.56; 95%CI: 0.33, 0.95, p= 0.03). Among drug use factors, only cocaine use in the past month (OR= 1.74; 95%CI: 1.01, 2.99, p= .047) and binge drinking (OR= 1.38; 95%CI: 1.02, 1.87 p= .036) were significantly associated with having an STI or HIV.
Factors independently associated with HIV/STI prevalence
A final multivariate model (table IV) suggested that after controlling for site-specific variability in municipal characteristics, higher rates of STI/HIV infection were related to lower education, having a spouse who has been diagnosed or treated for an STI in the past six months, not being able to afford a condom, and having foreign clients.
Predictor | Odds ratio estimate | Standard error | Lower wald 95%CI for OR | Upper wald 95%CI for OR | P-value | |||||
Years of education | 0.9009 | 0.0249 | 0.8535 | 0.9510 | 0.0002 | |||||
Spouse has been diagnosed or treated for an STI past six months | 2.9700 | 1.2271 | 1.3215 | 6.6750 | 0.0084 | |||||
Can afford to buy her own condoms | 0.6852 | 0.1013 | 0.5129 | 0.9154 | 0.0105 | |||||
Most or all clients are from elsewhere than Mexico | 1.9092 | 0.5101 | 1.1309 | 3.2232 | 0.0155 |
CI: confidence interval. OR: odds ratio
Controls for intra-site correlation by using site as a cluster variable with exchangeable corrletion structure in a GEE algorithm
Discussion
The prevalence of HIV among the participants was low at all of the study sites, and prevalence of other STIs varied widely, ranging from 9.9 to 46%. Similarly, self-reported sex risk varied widely, with rates of unprotected sex ranging from 20 to 60% between sites. While illicit drug use was low overall, alcohol abuse was common with 73% overall meeting criteria for hazardous drinking. Neither drug nor alcohol use correlated with STI prevalence in univariate analyses. In univariate analyses, a high Human Development Score decreased the odds of combined HIV/STI prevalence, but this variable was not significant in multivariate analyses. The Human Development Scores are broadly representative of each state and may not reflect the micro-environments inhabited by individual sex workers. Therefore, future research should focus on individual markers of economic status.
The prevalence of HIV among the sample of 1 092 FSWs was 0.4%. When combined with previous estimates,3,13,14 data from the present study suggest that FSWs from the 13 study sites had about 5.7 times (0.40/.07%) the risk of HIV compared to women from the general population, but they have only 0.06 times the risk of HIV compared to FSWs in Mexico’s northern border region, providing further evidence that sub-epidemics of HIV are occurring in specific regions and subpopulations in Mexico, particularly in border cities where migration patterns, drug trafficking routes, and sexual tourism contribute to higher risk behaviors among FSWs.15
Overall 23% of FSWs had either HIV or another STI. While this is comparable to STI rates observed historically among FSWs in Mexico,4 it is high relative to the general population (e.g., 2.3% prevalence of syphilis among women in the general population in 2007),16 suggesting high sex risk and thus the potential for an escalation of the HIV epidemic among FSWs in larger areas of Mexico. However, compared to FSWs in Tijuana and Cd. Juárez,17 FSWs in the present study were at about half the risk (.48 times) of gonorrhea, similar in chlamydia risk (1.18 times), and at lower risk for active syphilis titers (.18 times).
The final multivariate model suggested that, after controlling for variability in municipal characteristics, a greater risk of STI/HIV infection was related to four factors: lower education, having a spouse who has been diagnosed or treated for an STI in the past six months, not being able to afford a condom, and having clients who were from outside of Mexico. These results suggest a number of targets for interventions. Poverty and low education among FSWs have been identified previously as risk factors for negative health outcomes, Hence, HIV/STI prevention interventions could include structural components such as microloans and small business training.18
Providing more free condoms is an obvious and relatively inexpensive structural intervention. However, even FSWs who receive free condoms might be induced not to use them by offers from clients of higher fees for unprotected sex. This disincentive to condom use could be counteracted by cash transfers that are dependent on FSWs’ remaining free of sexually transmitted infections.19
The need for couples-based interventions is highlighted by our finding that having a spouse who has been diagnosed or treated for an STI in the past six months is related to increased risk for HIV/STIs. A number of investigators have tested couples-based interventions that, suitably adapted, could be effective for FSWs in Mexico.20
Finally, the correlation between having foreign-born male clients and being at elevated risk for HIV/STIs is of unclear significance. It is unclear whether the foreign-born clients reported in this study were primarily tourists, resident or transient migrants, or some combination. Sex tourism21 is not a likely explanation for the presence of foreign-born male clients, since the sites were predominantly located in cities or towns in the interior of Mexico that are not well known for their tourist trades. If the foreign-born clients were predominantly migrants, then the literature that indicates higher HIV risk among migrant men22 might shed some light on our finding. Future studies should examine this question in greater detail.
A limitation of this study stems from our sampling design, which involved recruiting women in high-risk areas and venues through time location sampling. This type of sampling can introduce bias by omitting unidentified areas and venues, and by excluding FSWs who do not visit these areas and venues, or refuse to be screened.10 The sample also consisted of volunteers in a sexual risk reduction intervention and thus may not be representative of the broader population of FSWs in each study site. Also, the $30 US compensation for participation in the interview and intervention could have affected the representativeness of the sample; most likely it resulted in greater motivation to participate. Although the low overall HIV prevalence could reflect the success of ongoing HIV/STI surveillance and prevention efforts, our cross-sectional data prevent us from assessing whether overall HIV/STI prevalence is decreasing among FSWs in these cities. Site-specific prevalence estimates may be unstable due to relatively small samples at each site and the fact that entry criteria included reporting high-risk behavior.
This study contributes to our understanding of the HIV epidemic in Mexico by adopting a multi-level approach to identifying correlates of HIV/STI prevalence that includes community-level municipal characteristics that have been largely ignored in previous research. Also, unlike previous work,23 this multi-site study involved a national sample of FSWs that included both urban and rural regions of Mexico. Our data suggest that interventions are advisable to mitigate the risks associated with FSW lifestyles. Evidence-based behavioral interventions for HIV prevention have been shown to be highly cost-effective and to potentially save public health resources in LMIC such as Mexico.24