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. Author manuscript; available in PMC: 2015 Oct 28.
Published in final edited form as: AIDS Care. 2015 Mar 19;27(8):1031–1036. doi: 10.1080/09540121.2015.1020750

Laboratory-confirmed HIV and sexually transmitted infection seropositivity and risk behavior among sexually active transgender patients at an adolescent and young adult urban community health center

Sari L Reisner a,b,*, Ralph Vetters c, Jaclyn M White b,d, Elijah L Cohen b, M LeClerc e, Shayne Zaslow b, Sarah Wolfrum b, Matthew J Mimiaga a,b,f
PMCID: PMC4624263  NIHMSID: NIHMS731729  PMID: 25790139

Abstract

The sexual health of transgender adolescents and young adults who present for health care in urban community health centers is understudied. A retrospective review of electronic health record (EHR) data was conducted from 180 transgender patients aged 12–29 years seen for one or more health-care visits between 2001 and 2010 at an urban community health center serving youth in Boston, MA. Analyses were restricted to 145 sexually active transgender youth (87.3% of the sample). Laboratory-confirmed HIV and sexually transmitted infections (STIs) seroprevalence, demographics, sexual risk behavior, and structural and psychosocial risk indicators were extracted from the EHR. Analyses were descriptively focused for HIV and STIs. Stratified multivariable logistic regression models were fit for male-to-female (MTF) and female-to-male (FTM) patients separately to examine factors associated with any unprotected anal and/or vaginal sex (UAVS). The mean age was 20.0 (SD = 2.9); 21.7% people of color, 46.9% white (non-Hispanic), 21.4% race/ethnicity unknown; 43.4% MTF, and 56.6% FTM; and 68.3% were on cross-sex hormones. Prevalence of STIs: 4.8% HIV, 2.8% herpes simplex virus, 2.8% syphilis, 2.1% chlamydia, 2.1% gonorrhea, 2.8% hepatitis C, 1.4% human papilloma virus. Only gonorrhea prevalence significantly differed by gender identity (MTF 2.1% vs. 0.0% FTM; p = 0.046). Nearly half (47.6%) of the sample engaged in UAVS (52.4% MTF, 43.9% FTM, p = 0.311). FTM more frequently had a primary sex partner compared to MTF (48.8% vs. 25.4%; p = 0.004); MTF more frequently had a casual sex partner than FTM (69.8% vs. 42.7% p = 0.001). In multivariable models, MTF youth who were younger in age, white non-Hispanic, and reported a primary sex partner had increased odds of UAVS; whereas, FTM youth reporting a casual sex partner and current alcohol use had increased odds of UAVS (all p < 0.05). Factors associated with sexual risk differ for MTF and FTM youth. Partner type appears pivotal to understanding sexual risk in transgender adolescents and young adults. HIV and STI prevention efforts, including early intervention efforts, are needed in community-based settings serving transgender youth that attend to sex-specific (biological) and gender-related (social) pathways.

Keywords: transgender, youth, HIV, STI

Introduction

According to the Centers for Disease Control and Prevention (CDC), youth (aged 13–24 years) comprised 17% of the US population in 2010, but accounted for an estimated 26% (12,200) of all new HIV infections (47,500) nationally (CDC, 2014). Youth also made up roughly 50% of all incident sexually transmitted infections (STIs) in the USA in 2008, with 51% of these occurring in young women and 49% in young men (CDC, 2013). Transgender individuals, or people who have a gender identity or gender expression different than their assigned sex at birth, appear to be disproportionately burdened by HIV and STIs (CDC, 2007, 2011), although HIV and STI incidence data are scarce (Nuttbrock et al., 2014). Young people on the male-to-female (MTF) spectrum – those assigned a male sex at birth who identify as women, transgender women, or other diverse transfeminine gender identities – have been shown to be highly vulnerable to acquisition and transmission of HIV infection with HIV seroprevalence as high as one in four in this community (Herbst, Jacobs, McKleroy, Neumann, & Crepaz, 2008). Few existing data exist on female-to-male (FTM) spectrum people (Reisner, White, Mayer, & Mimiaga, 2014), and even more rare are studies in FTM youth, individuals assigned a female sex at birth who identify as men, transgender men, FTM, or another diverse trans masculine gender identity.

Mental health (Herbst et al., 2008; Pengpid, Peltzer, & Skaal, 2013), substance use (Sevelius, Reznick, Hart, & Schwarcz, 2009), partner type (primary vs. casual; Brown & Vanable, 2007; Macaluso, Demand, Artz, & Hook, 2000; Operario, Nemoto, Iwamoto, & Moore, 2011), and sex work (Reisner et al., 2014; Yadav et al., 2005) are associated with sexual risk behaviors in the general population and in adult transgender populations, particularly among MTF spectrum samples. High prevalence of these risk factors has been documented in MTF transgender youth (Garofalo, Deleon, Osmer, Doll, & Harper, 2006; Grossman & D'Augelli, 2007). However, only partner type (primary male partnerships) and sex work have been shown to be associated with sexual risk in MTF spectrum people (Wilson, Garofalo, Harris, & Belzer, 2010; Wilson et al., 2009). CDC HIV and STI surveillance data define youth as 12–24 years; however, we conceptualize youth as including not only adolescents but also emerging adults ages 12–29 years. No published scientific reports – that we are aware of – are available comparing HIV, STIs, and sexual risk behaviors between MTF spectrum and FTM spectrum adolescents and emerging adults. Data that examine structural and psychosocial risk factors that may drive HIV, STIs, and sexual risk differentially for MTF and FTM youth are also lacking. Given the lack of inclusive US health surveillance efforts on the health of transgender individuals (Conron, Landers, Reisner, & Sell, 2014), electronic health record (EHR) data have been identified as an important source of health-related information (Cahill & Makadon, 2014; Deutsch et al., 2013). For this study, EHR data were used to examine the prevalence of laboratory-confirmed HIV and STIs among young transgender youth accessing services at an urban adolescent and young adult community health center serving those ages 12–29 years old, and to explore sexual behavior, and structural and psychosocial factors to inform the development of future interventions in clinical settings among this group.

Method

Study design, participants, and procedures

This study conducted a retrospective review of EHR data from 180 transgender patients ages 12–29 years seen consecutively for one or more health-care visits between 2001 and 2010 at an urban community health center serving adolescents and young adults in Boston, MA. Of transgender patients seen, 14 (7.8%) did not have data in their medical records indicating sexual activity status and were excluded from the data analytic sample. Among the 166 youth who had data on sexual activity, 145 were sexually active (n = 63 MTF, n = 82 FTM). The proportion of MTF (88.7%) and FTM (86.3%) youths who were sexually active did not significantly differ (χ2 = 0.21, df = 1, p = 0.64). Analyses were restricted to 145 sexually active patients (87.3% of the original sample) and data were treated as a cross-sectional sample.

Measures

Extracted from the EHR and included in this analysis were demographic variables including: age (continuous in years calculated from date of first visit) and race/ ethnicity (white non-Hispanic, people of color, unknown race/ethnicity). Additional binary (yes/no) variables were: (1) HIV and STI seroprevalence: laboratory-confirmed HIV, herpes simplex virus (HSV), syphilis, gonorrhea, chlamydia, hepatitis C, and/or human papilloma virus (HPV); (2) sexual risk behavior: condomless anal and/or vaginal sex; and (3) socio-structural and psychosocial risk indicators: cross-sex hormones for gender affirmation; sex partner type (having a current, primary sex partner; having a casual sex partner); having ever engaged in sex work; Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV-TR; APA, 2000) diagnosed depression; DSM-IV-TR diagnosed anxiety; current alcohol use; current marijuana use; and unstably housed (i.e., homeless, not stably housed, couch surfing with friends as noted in the provider social history of the EHR).

Data analysis

Data analysis was conducted using SAS v9.3. Univariate statistics were used to examine the distribution of variables (mean, standard deviation, and proportion). Data for HIV and STIs were descriptively focused with bivariates given small cell sizes, rather than fitting multivariable adjusted models. MTF and FTM youth were compared. The t-tests (pooled; equal variances were tested for and the null hypothesis of non-equal variances was not supported for any of the variables) were used to assess mean differences; chi-square tests were used to examine any differences in expected and observed proportions by gender identity spectrum (sparse data where cell sizes were <5 utilized Fisher's exact tests to obtain exact p-values and still reported chi-square test statistics). Stratified multivariable logistic regression models were fit for MTF and FTM youth separately to examine factors associated with sexual risk behavior (any condomless anal and/or vaginal sex yes/ no). A stratified approach was implemented for analyses because: (1) the risks for MTF and FTM youth are conceptualized as distinct and thus models restricted to MTF and FTM youth separately are aligned with such a theoretical viewpoint; (2) stratified models allow data from this study to be compared to other similar studies which have been restricted to MTF youth (Garofalo et al., 2006). Model building commenced with examining bivariate models for statistical significance. Then, factors significant at the p < 0.05 level were entered into a multivariable model, and independent associations were examined using the stepwise backward elimination method (Afifi, May, & Clark, 2003). This technique begins with all the variables in the equation and proceeds by eliminating the least useful variables one at a time using the computed F-to-remove statistic (Afifi et al., 2003).

Results

As shown in Table 1, the mean sample age was 20.0 (SD = 2.9); 21.7% people of color (non-white and/or Hispanic), 46.9% white (non-Hispanic), 21.4% race/ethnicity unknown. The sample was comprised of 43.4% MTF and 56.6% FTM. Overall, 68.3% were on cross-sex hormones. Prevalence of STIs is reported in Table 1. Only gonorrhea prevalence significantly differed by gender identity (p = 0.046).

Table 1.

Demographics, sexual health, and psychosocial risk factors among sexually active transgender adolescents and young adults (n = 145): comparing MTF (n = 63) and FTM (n = 82) youth.

Bivariate comparisons MTF vs. FTM
MTF n = 63 FTM n = 82 Total sample n = 145 t-test (df) p-value*
Age in years
 Mean (SD) 19.4 (3.2) 20.5 (2.6) 20.0 (2.9) 2.37 (143) 0.019
 Range 14–29 15–28 14–29
n (%) n (%) n (%) χ2 (df) p-value
 White (non-Hispanic) 18 (28.6) 50 (61.0) 68 (46.9) 23.24 (2) <0.0001
 People of color 33 (52.4) 13 (15.8) 46 (31.7)
 Unknown 12 (19.0) 19 (23.2) 31 (21.4)
Gender affirmation
 Cross-sex hormones 45 71.4 54 65.9 99 68.3 0.51 (1) 0.475
STIs
 HIV infection 5 7.9 2 2.4 7 4.8 2.34 (1) 0.126
 HSV 3 2.1 1 1.2 4 2.8 1.67 (1) 0.197
 Syphilis 3 4.8 1 1.2 4 2.8 1.67 (1) 0.197
 Chlamydia 2 3.2 1 1.2 3 2.1 0.67 (1) 0.412
 Gonorrhea 3 2.1 0 0.0 3 2.1 3.99 (1) 0.046
 Hepatitis C 2 3.2 2 2.4 4 2.8 0.07 (1) 0.789
 HPV 2 3.2 0 0.0 2 1.4 2.64 (1) 0.104
 HPV vaccination 7 11.1 26 31.7 33 22.8 8.60 (1) 0.003
Unprotected anal and/or vaginal sex (UAVS)
 Yes 33 52.4 36 43.9 69 47.6 1.03 (1) 0.311
 No 30 47.6 46 56.1 76 52.4
Socio-structural and psychosocial risk factors
 Primary sexual partner 16 25.4 40 48.8 56 38.6 8.22 (1) 0.004
 Casual sexual partner 44 69.8 35 42.7 79 54.5 10.60 (1) 0.001
 Sex work 21 33.3 1 1.2 22 15.2 28.55 (1) <0.0001
 Depression 27 42.9 45 54.9 72 49.7 2.06 (1) 0.151
 Anxiety
 Current alcohol use 32 50.8 48 58.5 80 55.2 0.86 (1) 0.353
 Current marijuana use 25 39.7 27 32.9 52 35.9 0.71 (1) 0.401
 Unstably/marginally housed 16 25.4 11 13.4 27 18.6 3.38 (1) 0.066
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Bold indicates statistical significance (p < 0.05).

*

Reported p-values are from Fisher's exact tests where cell sizes are small (less than 5).

Several STI risk factors differed by gender identity. FTM more often had a primary sex partner compared to MTF (p = 0.004); MTF more frequently had a casual sex partner than FTM (p = 0.001). MTF more often engaged in sex work than FTM (p < 0.0001).

Nearly half (47.6%) of the sample engaged in condomless vaginal and/or anal sex. The proportion did not differ by gender identity (52.4% MTF, 43.9% FTM, p = 0.311). In a multivariable logistic regression model (Table 2), MTF youth who were younger (OR = 0.75; 95% CI = 0.61, 0.92) and reported a primary sex partner had increased odds of condomless vaginal and/or anal sex. MTF of color (OR = 0.18; 95% CI = 0.04, 0.75) and unknown race/ethnicity (OR = 0.14; 95% CI = 0.02, 0.94) had decreased odds of condomless vaginal and/or anal sex compared to white (non-Hispanic) young people in this model. A parallel multivariable logistic regression model specific to FTM youth (Table 2) found those having a casual sex partner (OR = 3.38; 95% CI = 1.27, 9.03) and current alcohol use (OR = 3.06; 95% CI = 1.12, 8.35) had increased odds of condomless vaginal and/or anal sex.

Table 2.

Stratified analyses of sexual risk behavior in sexually active transgender adolescents and young adults (n = 145): bivariate and multivariable logistic regression models in MTF and FTM youth.

MTF FTM
Bivariate models Multivariable model Bivariate models Multivariable model
OR (95% CI) p-value OR (95% CI) p-value OR (95% CI) p-value OR (95% CI) p-value
Age in years (continuous) 0.81 (0.67, 0.97) 0.021 0.75 (0.61, 0.92) 0.006 0.89 (0.75, 1.06) 0.207 – –
White (non-Hispanic) 1.00 1.00 – 1.00 – –
People of color 0.32 (0.09, 1.11) 0.072 0.18 (0.04, 0.75) 0.018 1.18 (0.35, 4.04) 0.788 – –
Unknown 0.28 (0.06, 1.29) 0.101 0.14 (0.02, 0.94) 0.043 1.24 (0.43, 3.59) 0.688
No hormones 1.00 – – 1.00 – –
Hormones 0.61 (0.20, 1.85) 0.382 – – 0.55 (0.22, 1.39) 0.206 – –
No depression 1.00 – – 1.00 – –
Depression 1.63 (0.59, 4.46) 0.345 – – 1.28 (0.53, 3.09) 0.578 – –
No anxiety 1.00 – – 1.00 – –
Anxiety 1.57 (0.54, 4.61) 0.410 – – 1.81 (0.65, 5.00) 0.253 – –
No primary sex partner 1.00 1.00 – 1.00 – –
Primary sex partner 3.71 (1.04, 13.22) 0.043 6.76 (1.55, 29.53) 0.011 0.49 (0.20, 1.19) 0.112 – –
No casual sex partner 1.00 – – 1.00 1.00
Casual sex partner 0.39 (0.12, 1.20) 0.099 – – 2.58 (1.05, 6.36) 0.039 3.38 (1.27, 9.03) 0.015
No sex work 1.00 – – – – – –
Sex work 0.75 (0.26, 2.15) 0.593 – – – – – –
No current alcohol use 1.00 – – 1.00 1.00
Alcohol use current 1.06 (0.40, 2.86) 0.904 – – 2.27 (0.91, 5.67) 0.079 3.06 (1.12, 8.35) 0.029
No current marijuana use 1.00 – – 1.00 – –
Marijuana use current 1.67 (0.60, 4.63) 0.328 – – 1.29 (0.51, 3.26) 0.588 – –
Stably housed 1.00 – – 1.00 – –
Unstably/marginally 1.23 (0.39, 3.86) 0.720 – – 1.64 (0.46, 5.88) 0.448 – –
housed
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Bold indicates statistical significance (p < 0.05).

Note: Multivariable models fit using backward selection. MTF model initially included age, race/ethnicity, hormones, depression, anxiety, primary sex partner, casual sex partner, sex work, alcohol use current, marijuana use current, unstably/marginally housed. FTM model included the same variables except for sex work, given small cell size (e.g., 1 case).

Discussion

This study examined laboratory-confirmed prevalence of HIV and other STIs in transgender patients presenting for care at an urban adolescent and young adult community health center. HIV and STI prevalence did not differ significantly by gender identity, with the exception of gonorrhea prevalence, which was significantly higher in MTF than FTM youth. This elevated gonorrhea prevalence in MTF vs. FTM youth is consistent with CDC epidemiologic data reporting sex differences in gonorrhea as higher prevalence of gonorrhea is seen in non-transgender females relative to non-transgender male youth at the US population level (CDC, 2012). Findings from this study support sex-specific pathways to biological STI transmission. Gender-specific pathways were also found to be relevant for youth in this study as relationship indicators and factors associated with sexual risk in varying types of sexual partnerships were found to differ between MTF and FTM youth. Specifically, partner type (primary vs. casual) appears central to understanding sexual risk in MTF and FTM youth as having a primary partner was associated with sexual risk taking (i.e., condomless anal/vaginal sex) in MTF youth, whereas having a casual partner was associated with sexual risk among FTM youth. MTF youth also more frequently had casual sex partners and engaged in sex work, while FTM youth more often had a primary sex partner. Demographic and behavioral risk factors were also found to be differentially associated with sexual risk in MTF versus FTM youth, as sexual risk taking was associated with being young and white (non-Hispanic) in FTM youth, while current alcohol use was associated with sexual risk in FTM youth. Given that casual partnerships and sex work can place individuals as risk of acquiring HIV and other STIs (Baral et al., 2013; Hoffman, 2014; Operario, Soma, & Underhill, 2008; Sanchez et al., 2006), prevention efforts, including early intervention programs, that are attentive to both sex-specific (biological) and gender-specific (social) pathways to HIV and STI risk are warranted in community-based settings serving transgender youth. This study is not without limitations. First, the primary reason youth presented for care was not captured (i.e., primary care, mental health, HIV, and STI testing specifically). The chart review method utilized meant that incomplete documentation, missing charts, unrecorded information, and difficult interpretation of the information contained in the documents (e.g., due to sexual risk or STI jargon and acronyms reported in provider notes) may have produced unintended bias (Dworkin, 1987; Gearing, Mian, Barber, & Ickowicz, 2006; Hess, 2004; Krowchuk, Moore, & Richardson, 1995). Variance in the quality of information recorded by the medical professionals in shared EHR fields (e.g., social history) may have weakened the integrity of the data (Pan, Fergusson, Schweitzer, & Hebert, 2005). In addition, gender affirmation by sexual partners – having one's gender identity affirmed or validated – has been shown to play a significant role in the sexual risk behavior of adult MTF, particularly transgender women of color (Melendez & Pinto, 2007; Sevelius, 2013). Prior research with adult MTF adult women suggests that sexual risk may be most likely with sexual partners who affirm their gender, particularly in the context of a primary male partner (Bockting, Robinson, & Rosser, 1998; Melendez & Pinto, 2007; Nemoto, Operario, Keatley, & Villegas, 2004; Operario et al., 2011). Gender affirmation has also been shown to be an important determinant of adult FTM adult men's sexual health including sexual risk behaviors with non-transgender MSM (Reisner, Perkovich, & Mimiaga, 2010; Sevelius, 2009). Given the chart review nature of this study, it was not possible to measure gender affirmation processes, which represents a limitation of this research and direction for future study. Limitations notwithstanding, this study provides new information on the relationship between risk factors and sexual risk behaviors in transgender youth, specifically in the differences between MTF and FTM youth. Partner type is a fluid concept and “primary partner” is not equal to monogamy both in terms of how study data were extracted from medical records and in terms of youth practice and behavior.

Findings suggest that factors associated with the sexual risk behavior of MTF and FTM adolescents and young adults differ. As previously demonstrated in MTF samples (Operario et al., 2011; Wilson et al., 2009; Wilson et al., 2010), partner type appears to be a key aspect of sexual risk among transgender youth in this clinic sample. Findings should be taken into account in clinical practice with transgender youth, including assessment of sexual histories with these patients. Clinicians should ensure that transgender youth receive health care, including HIV and STI screening prevention (e.g., preexposure prophylaxis), with their specific, differing needs, and risk profiles in mind – including attention to sex-specific (biological risks) and gender-specific (socially patterned) factors. More research is needed to examine further differences in sexual risk behaviors and HIV and STI acquisition between MTF and FTM youth. Future research should take into account the current study's cross-sectional findings regarding differing behaviors and the levels of risk associated with these behaviors. Longitudinal data in this area are needed to understand and attend to the dynamic pathways and mechanisms, including gender affirmation, associated with HIV and STI risk in transgender youth by partner type across adolescent and young adult development.

Acknowledgments

Funding: This work was supported by The Fenway Institute at Fenway Health. Dr Reisner and Dr Mimiaga's time was partially supported by National Institute of Mental Health (NIMH) [R01MH094323]. Ms White's time was supported by [Award Number T32MH020031], [Award Number P30MH062294] from NIMH.

Footnotes

Disclosure statement: No potential conflict of interest was reported by the authors.

References

  1. Afifi A, May S, Clark VA. Computer-aided multivariate analysis: Fourth edition. 4th. Boca Raton, FL: Chapman & Hall/CRC; 2003. [Google Scholar]
  2. APA. Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (4th ed) (DSM-IV-TR) Washington, DC: Author; 2000. [Google Scholar]
  3. Baral SD, Poteat T, Strömdahl S, Wirtz AL, Guadamuz TE, Beyrer C. Worldwide burden of HIV in transgender women: A systematic review and meta-analysis. The Lancet Infectious Diseases. 2013;13:214–222. doi: 10.1016/S1473-3099(12)70315-8. [DOI] [PubMed] [Google Scholar]
  4. Bockting WO, Robinson BE, Rosser BRS. Transgender HIV prevention: A qualitative needs assessment. AIDS Care. 1998;10:505–525. doi: 10.1080/09540129850124028. [DOI] [PubMed] [Google Scholar]
  5. Brown JL, Vanable PA. Alcohol use, partner type, and risky sexual behavior among college students: Findings from an event-level study. Addictive Behaviors. 2007;32:2940–2952. doi: 10.1016/j.addbeh.2007.06.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Cahill S, Makadon H. Sexual orientation and gender identity data collection in clinical settings and in electronic health records: A key to ending LGBT health disparities. LGBT Health. 2014;1(1):34–41. doi: 10.1089/lgbt.2013.0001. [DOI] [PubMed] [Google Scholar]
  7. CDC. HIV/AIDS and transgender people. 2007 Retrieved from http://www.cdc.gov/lgbthealth/pdf/fs-transgender-06192007.pdf.
  8. CDC. HIV infection among transgender people. 2011 Retrieved from http://www.cdc.gov/hiv/transgender/pdf/transgender.pdf.
  9. CDC. STDs in adolescents and young adults. 2012 sexually transmitted diseases surveillance. 2012 Retrieved January 13, 2014, from, http://www.cdc.gov/std/stats12/adol.htm.
  10. CDC. Incidence, prevalence, and cost of sexually transmitted infections in the United States. 2013 Retrieved from http://www.cdc.gov/std/stats/sti-estimates-fact-sheet-feb-2013.pdf.
  11. CDC. HIV among youth. 2014 Apr 7; Retrieved from http://www.cdc.gov/hiv/risk/age/youth/
  12. Conron KJ, Landers SJ, Reisner SL, Sell RL. Sex and gender in the US health surveillance system: A call to action. American Journal of Public Health. 2014;104:970–976. doi: 10.2105/AJPH.2013.301831. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Deutsch MB, Green J, Keatley J, Mayer G, Hastings J, Hall AM. Electronic medical records and the transgender patient: Recommendations from the world professional association for transgender health EMR working group. Journal of the American Medical Informatics Association. 2013;20(4):700–703. doi: 10.1136/amiajnl-2012-001472. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Dworkin RJ. Hidden bias in the use of archival data. Evaluation & the Health Professions. 1987;10:173–185. doi: 10.1177/016327878701000202. [DOI] [PubMed] [Google Scholar]
  15. Garofalo R, Deleon J, Osmer E, Doll M, Harper GW. Overlooked, misunderstood and at-risk: Exploring the lives and HIV risk of ethnic minority male-to-female transgender youth. Journal of Adolescent Health. 2006;38:230–236. doi: 10.1016/j.jadohealth.2005.03.023. [DOI] [PubMed] [Google Scholar]
  16. Gearing RE, Mian IA, Barber J, Ickowicz A. A methodology for conducting retrospective chart review research in child and adolescent psychiatry. Journal of the Canadian Academy of Child and Adolescent Psychiatry. 2006;15(3):126–134. [PMC free article] [PubMed] [Google Scholar]
  17. Grossman AH, D'Augelli AR. Transgender youth and life-threatening behaviors. Suicide & Life-threatening Behavior. 2007;37:527–537. doi: 10.1521/suli.2007.37.5.527. [DOI] [PubMed] [Google Scholar]
  18. Herbst JH, Jacobs ED, McKleroy VS, Neumann MS, Crepaz N. Estimating HIV prevalence and risk behaviors of transgender persons in the United States: A systematic review. AIDS and Behavior. 2008;12(1):1–17. doi: 10.1007/s10461-007-9299-3. [DOI] [PubMed] [Google Scholar]
  19. Hess DR. Retrospective studies and chart reviews. Respiratory Care. 2004;49:1171–1174. [PubMed] [Google Scholar]
  20. Hoffman BR. The interaction of drug use, sex work, and HIV among transgender women. Substance Use & Misuse. 2014;49:1049–1053. doi: 10.3109/10826084.2013.855787. [DOI] [PubMed] [Google Scholar]
  21. Krowchuk HV, Moore ML, Richardson L. Using health care records as sources of data for research. Journal of Nursing Measurement. 1995;3(1):3–12. [PubMed] [Google Scholar]
  22. Macaluso M, Demand MJ, Artz LM, Hook EW., III Partner type and condom use. AIDS. 2000;14:537–546. doi: 10.1097/00002030-200003310-00009. [DOI] [PubMed] [Google Scholar]
  23. Melendez RM, Pinto R. ‘It's really a hard life’: Love, gender and HIV risk among male-to-female transgender persons. Culture, Health & Sexuality. 2007;9:233–245. doi: 10.1080/13691050601065909. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Nemoto T, Operario D, Keatley J, Villegas D. Social context of HIV risk behaviours among male-to-female transgenders of colour. AIDS Care. 2004;16:724–735. doi: 10.1080/09540120412331269567. [DOI] [PubMed] [Google Scholar]
  25. Nuttbrock L, Bockting W, Rosenblum A, Hwahng S, Mason M, Macri M, Becker J. Gender abuse and incident HIV/STI among transgender women in New York City: Buffering effect of involvement in a transgender community. AIDS Behavior. 2014 doi: 10.1007/s10461-014-0977-7. Advance online publication. [DOI] [PubMed] [Google Scholar]
  26. Operario D, Nemoto T, Iwamoto M, Moore T. Unprotected sexual behavior and HIV risk in the context of primary partnerships for transgender women. AIDS and Behavior. 2011;15:674–682. doi: 10.1007/s10461-010-9795-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Operario D, Soma T, Underhill K. Sex work and HIV status among transgender women: Systematic review and meta-analysis. JAIDS: Journal of Acquired Immune Deficiency Syndromes. 2008;48(1):97–103. doi: 10.1097/QAI.0b013e31816e3971. [DOI] [PubMed] [Google Scholar]
  28. Pan L, Fergusson D, Schweitzer I, Hebert PC. Ensuring high accuracy of data abstracted from patient charts: The use of a standardized medical record as a training tool. Journal of Clinical Epidemiology. 2005;58:918–923. doi: 10.1016/j.jclinepi.2005.02.004. [DOI] [PubMed] [Google Scholar]
  29. Pengpid S, Peltzer K, Skaal L. Mental health and HIV sexual risk behavior among university of Limpopo students. South African Journal of Psychiatry. 2013;19(2):25–30. doi: 10.7196/SAJP.415. [DOI] [Google Scholar]
  30. Reisner SL, Perkovich B, Mimiaga MJ. A mixed methods study of the sexual health needs of New England transmen who have sex with nontransgender men. AIDS Patient Care and STDs. 2010;24:501–513. doi: 10.1089/apc.2010.0059. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Reisner SL, White JM, Mayer KH, Mimiaga MJ. Sexual risk behaviors and the psychosocial health concerns of female-to-male transgender men screening for STDs at an urban community health center. AIDS Care. 2014;26:857–864. doi: 10.1080/09540121.2013.855701. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Sanchez T, Finlayson T, Drake A, Behel S, Cribbin M, DiNenno E, et al. Lansky A. Human immunodeficiency virus (HIV) risk, prevention, and testing behaviors – United States, national HIV behavioral surveillance system: Men who have sex men, November 2003–April 2005. MMWR Surveill Summ. 2006;55(6):1–16. [PubMed] [Google Scholar]
  33. Sevelius JM. There's no pamphlet for the kind of sex I have: HIV-related risk factors and protective behaviors among transgender men who have sex with non-transgen-der men. Journal of the Association of Nurses in AIDS Care. 2009;20:398–410. doi: 10.1016/j.jana.2006.06.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Sevelius JM. Gender affirmation: A framework for conceptualizing risk behavior among transgender women of color. Sex Roles. 2013;68:675–689. doi: 10.1007/s11199-012-0216-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Sevelius JM, Reznick OG, Hart SL, Schwarcz S. Informing interventions: The importance of contextual factors in the prediction of sexual risk behaviors among transgender women. AIDS Education and Prevention. 2009;21(2):113–127. doi: 10.1521/aeap.2009.21.2.113. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Wilson EC, Garofalo R, Harris DR, Belzer M. Sexual risk taking among transgender male-to-female youths with different partner types. American Journal of Public Health. 2010;100:1500–1505. doi: 10.2105/AJPH.2009.160051. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Wilson EC, Garofalo R, Harris RD, Herrick A, Martinez M, Martinez J, Belzer M. Transgender female youth and sex work: HIV risk and a comparison of life factors related to engagement in sex work. AIDS and Behavior. 2009;13:902–913. doi: 10.1007/s10461-008-9508-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Yadav G, Saskin R, Ngugi E, Kimani J, Keli F, Fonck K, et al. Bwayo JJ. Associations of sexual risk taking among Kenyan female sex workers after enrollment in an HIV-1 prevention trial. Journal of Acquired Immune Deficiency Syndromes. 2005;38:329–334. [PubMed] [Google Scholar]

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