Abstract
This study examines the socio-structural sexual health risks of female youth (ages 14–17) working in bar/spa venues and brothels in the Philippines, compared to their older counterparts. Aside from this study, few female sex work studies have interviewed youth under 18. On four southern Philippines islands, 770 female sex workers, ages 14–48, were recruited from bar/spa venues and brothels to participate in a socio-structural HIV prevention study. Controlling for the effects of a larger HIV prevention intervention study involving 1,484 female bar/spa workers, the minors, compared to older FSWs, had less education (AOR: 0.81, CI: 0.70–0.94), less children (AOR: 0.19, CI: 0.10–0.37), and were more likely to work in illegal brothels (AOR: 4.60, CI: 1.66–12.75) and to be high on drugs during sex (AOR: 2.26, CI: 1.39–3.67). It was less likely that anyone talked to them about HIV prevention (AOR: 0.32, CI: 0.15–0.72), but more likely they were recruited by venue owners (AOR: 5.67, 1.56–20.56) and were told by their managers to have sex without a condom (AOR: 6.80, CI: 2.06–22.39). Results suggest a need for organizational and policy level interventions to protect adolescent females from working in unsafe environments in the Philippines and to prevent youth from being recruited into high-risk situations.
Keywords: youth, trafficking, HIV, sex trade, Philippines
An estimated 20–40% of female sex workers (FSWs) enter commercial sex work as adolescents (Silverman, 2011). The U.N. Palermo Protocol (2000) and the Philippines Expanded Anti-Trafficking in Persons Act (2012) include in their definition of trafficking any individual below 18 who trades sex. Sex work and being a minor working in a bar or spa are illegal in the Philippines. Still, youth are recruited (Trinidad, 2005); over 20% of girls trafficked in Cebu, Philippines reported inability to leave their workplace by themselves (Artadi, Bjorkman, & La Ferrara, 2011). Several studies retrospectively examine underage entry of females into the sex trade (Cobbina & Oselin, 2011; Goldenberg et al., 2014), but few include actively underage sex workers nor examine their social and structural HIV risks.
Individuals entering sex work before age 18 are at higher risk for STI/HIV (Decker, McCauley, Phuengsamran, Janyam, & Silverman, 2011). Their structural HIV risks include longer captivity in brothel settings, recruitment from public settings (markets, train stations) and via public transportation, and enticement for economic reasons (Silverman, et al, 2007; 2006).
The definition of trafficking as being a minor trading sex drove the research question for this study. Social-structural variables include venue managers’ role of recruiting youth, exposing them to HIV prevention information, and promoting condom use. We theorize that minors trading sex in the southern Philippines have less socio-structural support (peer, manager, organizational) compared to older FSWs and will be at higher risk for substance use, control by managers, and less exposure to HIV prevention messages.
METHODS
Filipina female bar and spa workers were recruited from venues on four southern Philippine islands, southern Luzon, Cebu, Ilo-Ilo, and northern Mindanao. The full methods of the overall larger intervention study are described in the literature (Ang & Morisky, 2012; Morisky, Stein, Chiao, Ksobiech, & Malow, 2006). Venues included bar/clubs (e.g. beer gardens, discos, karaoke centers), spa/sauna/barber shops, brothels (casas), and other (restaurants, hotels, freelance). All venue participants were in either HIV prevention (peer and manager based) interventions or routine HIV/STI prevention care, randomized by city site. Approximately 98% of participants (n=1,484) gave informed consent; University of California, Los Angeles and the University of the Philippines Institutional Review Boards approved the study and waived the signed consent requirement to protect the identity of the individuals. Thirty-nine individuals did not participate due to unavailability; they did not differ on sociodemographic characteristics compared to individuals who participated. All study participants received the same educational counseling as all receiving care at the government-run Social Hygiene Clinics (SHCs), including referrals to organizations for further assistance.
Women/girls who attended mandatory SHC appointments for STI check-ups were surveyed face-to-face at clinics, business establishments, and residences, based on their preference. All those who had paid sex for ≥1 month were included in this analysis (n=770); 21 were dropped due to missing data: education (n=2), certain workplaces (restaurant n=5, hotel n=1), “other” responses for how they were recruited (n=3) and what their boss said to do if a client refused to use a condom (n=10).
Measures
Measures were adapted from Morisky et al (1998). Socio-demographic variables included age recoded dichotomously (14–17, 18–48), education, number of children, marital status, months worked trading sex, and self-reported STIs in the past 6 months. Venue types included bar/club/beer garden, spa/sauna/barber shop, disco, karaoke center, brothel (casa), or other. Participants answered how they were recruited; unknown was whether they entered work in the absence of force, coercion or trickery.
Behavioral measures included condom use at last sexual encounter with any sexual partner (Yes-No), an 11-item condom attitudes scale (1-strongly agree to 5-strongly disagree) validated in the southern Philippines with Cronbach’s alpha=.60, and how often they drank with patrons, were intoxicated during sex, or were high on drugs during sex.
Social-structural influences were single items (Yes-No) for whether anyone told them how to prevent HIV or how to use a condom properly; support of HIV prevention from a co-worker; manager support of condoms with clients; what manager told them to do if client refused condom; and presence of venue condom rule and condom availability.
Analytic Approach
Youth and older sex workers were compared via t-tests for continuous variables and Pearson’s Chi-square for binary outcomes. To identify individual, social, and structural factors associated with underage sex trade, multilevel logistic regression models were performed, controlling for intervention effects and individuals nested within venues. All variables that attained a significance level <10% in univariate models were considered in logistic multiple regression analyses in order of most to least significance.
RESULTS
Socio-demographics
Of 770 FSWs, 56 (7%) were aged 14–17, with the remaining aged 18–48. Overall, participants had a median of 9 years of education, 1 child, 6 months trading sex, 28% had an STI in the past 6 months, 78% reported condom use at last sexual encounter, 36% overall reported being intoxicated during sex (current usual practice), and 10% reported being high on drugs during sex (current usual practice).
Social and structural experiences
87% said someone talked to them about preventing AIDS, 87% said someone ever taught them how to use a condom properly, 72% said a co-worker ever tried to convince them to use condoms with clients, 79% said they met regularly as a group of workers with their manager, 76% said their venue had a condom rule, and 67% said condoms were available at their venue. Fifty-seven percent of youth and 67% of older female sex workers participated in the HIV prevention intervention.
Bivariate analyses
Comparisons show significant differences among age groups, with minors having the lowest median years of education (p=0.026), least number of children (p=0.001), and lowest number of months trading sex (p=0.009). Those under age 18 were less likely to be married or living with a boyfriend (p=0.001) and more likely to be on drugs during sex (p=0.001).
Multilevel logistic regression
Factors independently associated with underage sex trade activity, adjusting for education and number of children, were: working in a brothel (casa) vs. a bar/club compared to older FSWs (AOR:5.08, CI:1.70–15.15), and recruitment by a venue owner (AOR: 6.19, 1.60–23.89). For situations in which a patron refused to wear a condom, managers were nearly 8 times more likely to tell the youth to have sex without a condom with the client (AOR: 7.90, CI: 2.30–27.19). Youth were less likely to have anyone tell them about how to prevent HIV/AIDS (AOR: 0.33, CI: 0.14–0.75), and were two times more likely to be high on drugs during sex (AOR: 2.22, CI:1.46–3.37).
DISCUSSION
Findings confirm the socio-structural barriers faced by adolescents trading sex in the Philippines and reinforce the need to consider organizational and community level factors influencing risk. Access to sexual and reproductive health education has been limited among youth in the Philippines due to the strong political presence of the Catholic Church (Austria, 2004). The recent passing of the Philippines Responsible Parenthood and Reproductive Health Act, which allows for government-funded sex education in schools, reflects a changing political climate. However, given the disproportionately lower levels of education achieved by youth who exchange sex as demonstrated in this study, alternative approaches are required to reach youth at greatest risk for and currently trading sex. The current study reinforces the critical need for evidence-based HIV risk reduction interventions among adolescents already engaged in sex work and out-of-school youth at risk for entry into sex work.
Findings are consistent with previous research in the Philippines which show that family financial constraints can lead youth to drop out of school and seek income via trading sex (Artadi, Bjorkman & La Ferrara, 2011; ECPAT Philippines & Terre des Hommes Netherlands, 2004; ILO, 2004). Findings highlight the importance of income-generation alternatives for out-of-school youth at risk of or currently trading sex. Integrated economic empowerment and HIV prevention interventions show potential in reducing sexual risk while enhancing the economic stability of people engaged in sex work (Tsai et al, under review; Sherman et al, 2010; Erulkar et al., 2006). Development of evidence-based interventions that address the economic structures influencing risk in the Filipino context need further attention.
Women and girls trafficked into the sex trade may be forced to engage in substance use against their will (Gupta, Raj, Decker, Reed, & Silverman et al., 2009; ECPAT Philippines & Terre des Hommes Netherlands, 2004; ILO, 2004). In light of the higher levels of drug use during sex found among youth in this study, substance use services need to detect and target youth in the sex trade in the Philippines where crystal methamphetamine use (shabu) is especially high (Dangerous Drugs Board, 2002; Urada et al, 2013).
In this study, youth may have underreported their adolescent age (Zimmerman & Watts, 2003). Limitations include the absence of time frames for substance use and the cross-sectional design pre-empting causal inference. Other ways to measure trafficking (e.g. force or coercion), including violence, were not measured. Results suggest a need for organizational and policy level interventions to protect adolescent females from working in unsafe environments in the Philippines and to prevent youth from being recruited into high-risk situations.
TABLE 1.
Socio-demographic, Behavioral, and Socio-structural Characteristic Differences by Age Category of Female Sex Workers in the Southern Philippines
| Age Category | ||||
|---|---|---|---|---|
| Total | 14–17 | 18–48 | ||
| n=770 (%) | n=56 (%) | n=714 (%) | p | |
| Socio-Demographic | ||||
| Median years of education (IQR) | 9 (7–10) | 8 (7–9) | 9 (7–10) | 0.03 |
| Median number of children (IQR) | 1 (0–2) | 0 (0–1) | 1 (0–2) | 0.01 |
| Married or living with a boyfriend | 0.01 | |||
| Yes | 256 (33) | 6 (11) | 250 (35) | |
| No | 514 (67) | 50 (89) | 464 (65) | |
| Median months trading sex (IQR) | 6 (3–15) | 5 (2–10) | 6 (3–16) | 0.01 |
| Any STIs in past six months (self-reported) | ||||
| Yes | 216 (28) | 18 (32) | 193 (27) | 0.44 |
| No | 554 (72) | 38 (68) | 521 (73) | |
| Venue type | ||||
| Bar/club/beer garden | 189 (25) | 10 (17) | 179 (25) | 0.01 |
| Spa/sauna/barber | 230 (30) | 9 (16) | 221 (31) | |
| Disco | 92 (12) | 6 (10) | 86 (12) | |
| Karaoke center | 169 (23) | 12 (21) | 157 (22) | |
| Brothel (casa) | 56 (7) | 13 (23) | 43 (6) | |
| Other | 42 (5) | 6 (10) | 36 (5) | |
| How recruited to job | 0.10 | |||
| Answered ad | 303 (40) | 17 (30) | 286 (40) | |
| Recommended by friend | 381 (49) | 31 (55) | 350 (49) | |
| Recruited by mamasan | 45 (6) | 2 (3) | 43 (6) | |
| Recruited by venue owner | 26 (3) | 5 (8) | 21 (3) | |
| Recruited by employment agency | 15 (2) | 1 (1) | 14 (2) | |
| Behavioral | ||||
| Condom use at last sexual encounter | 0.83 | |||
| Yes | 600 (78) | 45 (80) | 557 (78) | |
| No | 169 (22) | 11 (20) | 157 (22) | |
| Condom knowledge/attitudes (> more positive) | 30.1 (15–48) | 31.2 (15–48) | 30.8 (15–48) | 0.53 |
| Frequency drinks with patrons (1-never, 4-always) | 2.4 (1–4) | 2.3 (1–4) | 2.4 (1–4) | 0.35 |
| Intoxicated during sex (current) | 0.67 | |||
| Yes | 277 (36) | 21 (38) | 257 (36) | |
| No | 493 (64) | 35 (62) | 457 (64) | |
| High on drugs during sex (current) | 0.01 | |||
| Yes | 77 (10) | 11 (19) | 64 (9) | |
| No | 693 (90) | 45 (81) | 650 (91) | |
| Socio-Structural | ||||
|
General STI prevention support Anyone talked to you about how you can prevent AIDS |
0.02 | |||
| Yes | 670 (87) | 43 (77) | 628 (88) | |
| No | 100 (13) | 13 (23) | 86 (12) | |
| Anyone ever taught you how to use a condom properly | 0.65 | |||
| Yes | 670 (87) | 48 (86) | 628 (88) | |
| No | 100 (13) | 8 (14) | 86 (12) | |
| Peer support | ||||
| Co-worker ever tried to convince you to use condoms with clients? | 0.44 | |||
| Yes | 554 (72) | 43 (77) | 514 (72) | |
| No | 216 (28) | 13 (23) | 200 (28) | |
| Manager support | ||||
| Manager response to FSW if client refuses condom | ||||
| Manager doesn’t talk about it | 362 (47) | 21 (37) | 343 (48) | referent |
| Have sex without a condom | 23 (3) | 7 (12) | 14 (2) | 0.01 |
| Refuse to have sex | 208 (27) | 9 (16) | 200 (28) | 0.46 |
| Convince him to use condoms | 185 (24) | 18 (33) | 164 (23) | 0.06 |
| Manager supports condom use with clients (1-very, 5-never) | 1.8 (1–5) | 1.7 (1–5) | 1.8 (1–5) | 0.77 |
| Group of workers meet with manager regularly | 0.02 | |||
| Yes | 608 (79) | 37 (66) | 564 (79) | |
| No | 162 (21) | 25 (44) | 143 (20) | |
| Venue policy | ||||
| Venue has a condom rule | 0.84 | |||
| Yes | 585 (76) | 43 (76) | 550 (77) | |
| No | 185 (24) | 13 (24) | 164 (23) | |
| Venue has condoms available | 0.74 | |||
| Yes | 516 (67) | 39 (70) | 478 (67) | |
| No | 254 (33) | 17 (30) | 236 (33) | |
TABLE 2.
Associations with history of sex work among female sex workers under 18 years old in the Southern Philippines, controlling for individuals nested within venues (A random-effects/multilevel logistic regression model)
| Variable | Crude OR | 95% CI | Adjusted OR |
95% CI |
|---|---|---|---|---|
| Education | 0.87* | 0.78–0.98 | 0.81** | 0.70–0.94 |
| Number of children | 0.19* | 0.10–0.36 | 0.19*** | 0.09–0.36 |
| Type of workplace venue (vs. bar/club/beer garden) | ||||
| Spa/sauna/barber | 0.72 | 0.29–1.81 | 1.35 | 0.42–4.34 |
| Disco | 1.21 | 0.43–3.45 | 1.40 | 0.41–4.84 |
| Karaoke bar | 1.43 | 0.58–3.27 | 1.48 | 0.50–4.39 |
| Brothel (casa) | 5.07* | 2.24–13.24 | 5.08** | 1.70–15.15 |
| Other (e.g. beach resort, freelancer) | 10.49* | 1.05–9.04 | 10.32** | 2.45–43.38 |
| Who recruited them to work in current venue (vs. answered ad, applied by self) | ||||
| Friend | 1.24 | 0.81–2.75 | 1.15 | 0.59–2.67 |
| Mamasan | 0.77 | 0.17–3.44 | 0.43 | 0.08–2.37 |
| Venue owner | 4.32* | 1.45–12.93 | 6.19** | 1.60–23.89 |
| Employment agency | 2.04 | 0.15–9.96 | 2.89 | 0.20–21.00 |
| Manager response to FSW if client refuses condom (vs. manager not talking about it) | ||||
| Have sex without a condom | 7.42* | 2.73–20.17 | 7.90** | 2.30–27.19 |
| Refuse to have sex | 0.72 | 0.32–1.60 | 0.87 | 0.34–2.26 |
| Convince him to use condoms | 1.83 | 0.96–3.50 | 2.13 | 0.96–4.76 |
| Anyone ever talked to FSW about how to prevent HIV/AIDS | 0.46* | 0.24–0.88 | 0.33** | 0.14–0.75 |
| High on drugs during sex | 1.89* | 1.25–2.85 | 2.22*** | 1.46–3.37 |
| Intervention group (vs. control) | 0.96 | 0.38–1.14 | 1.04 | 0.39–2.35 |
P ≤ .05
P≤.01
P≤.001
Acknowledgments
We extend appreciation to our co-investigator, the late Dr. Teodora Tiglao; research manager, Charlie Mendoza; site coordinators, Dorcas Romen, Grace Carungay, Angelica Mallari, Mildred Publico, and Grace Ong.
Funding: This work was supported by the National Institute of Allergy and Infectious Diseases [R01-AI33845], and written with support from the National Institutes of Drug Abuse [T32 DA023356, DA028692-04S1, 1K01DA036439-01].
Footnotes
The authors have no financial interests or benefits arising from the direct applications of this research.
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