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Measuring Ethnic and Sexual IdentitiesLessons from two studies in Central America

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Session ObjectivesAfter the presentations, participants will be able to: Give examples of ethnic and sexual identity-related questions from two recent studies Relate how these constructs were central to the research questions Highlight implications for the studies‟ findings Apply lessons learned to other research efforts

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Ethnicity and HIV Risk Factors in Guatemala:Measuring indigenous identity and its effects

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Study Overview  Indigenous Guatemalans are highly disadvantaged on many measures of health and well-being – are they also at higher risk for HIV?  Secondary analysis of the ENSMI (DHS) women‟s and men‟s datasets from 2008-09  Multivariate logistic regression for different ethnic groups on 5 factors (early sexual debut, lifetime sexual partners, HIV knowledge, HIV testing, sex worker patronage)http://www.cpc.unc.edu/measure/publications/tr-12-86

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Ethnicity in Guatemala The government of Guatemala recognizes four pueblos: Ladino, Maya, Xinca and Garífuna Around 60% of the population is ladino; the other three groups are officially designated as indigenous Mayans constitute 99% of the indigenous population Twenty-three linguistically distinct Mayan subgroups are centered in the country‟s rural western highlands

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Who is indigenous, who is ladino? Ethnicity is mutable and multidimensional, but most surveys use a single categorical variable to measure it ENSMI and the national census have long histories of obtaining data on ethnicity via „interviewer‟s observation‟ In 2008-09, an ethnic self-identity question was added:“Do you consider yourself to be indigenous, ladino, or some other ethnicity?”

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Ethnicity in the 2008-09 ENSMI Men Women 4% 3% 37% 44% 44% 47% 8% 13% Indigenous Cross-Identified* Ladino Other/No Response*Respondents who self-identified as indigenous but were identified by the interviewer as ladino

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Long histories and broad ramifications In 1950, census enumerators classified 4% of locally- identified indigenous Guatemalans as ladino; in 1964, 16% were cross-classified (Early, 1974) A 1998 study in Brazil concluded that previous studies had underestimated the country‟s racial inequality, because they relied on self-classification (Telles & Lim) Cause of death affects coroners‟ classification of US decedents‟ race in 1993: “non-racial characteristics thus shape official statistics” (Noymer et. al, 2011)

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Why does it matter how we measureethnicity in Guatemala? Different dimensions of ethnic identity might have different effects on HIV risk and other outcomes there The validity and reliability of ethnicity questions, including the two in current use, may vary Conclusions about the size and vulnerability of different groups can affect program and policy decisions The Government of Guatemala officially supports ethnic self-determination

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“A dispute over ethnicity marked census-taking day in Bolivia as the landlocked Andean nations population submitted Wednesday to its first national head count in 11 years.”Text: Carlos Valdez for the Associated Press, 2012. Photos: Página Siete, La Razon

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“After more than a century, the Census Bureau is dropping its use of the word „Negro‟ to describe black Americans in surveys”Source: Jason Howerton for the Associated Press, 2013

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Ethnicity in our analysis Should cross-identified respondents in Guatemala be considered indigenous or ladino? What matters more: ethnic self-identity or the interviewer‟s observation? Regardless of how its members were identified, the indigenous group had lower adjusted odds of sexual risk, comprehensive knowledge and HIV testing But these results obscured the profile of cross-identified respondents, a group with unique potential to explain possible measurement effects

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Three categories instead of two Self- InterviewerCategories identification ObservationIndigenous Indigenous IndigenousCross-identified Indigenous LadinoLadino Ladino Ladino

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Illustrative Adjusted Odds Ratios of HIV risk by Ethnicity WOMEN MEN Adjusted OR Adjusted OR Ever tested for HIV Indigenous Reference Reference Cross-identified 2.46 (1.93-3.13)*** 1.18 (0.64-2.16) Ladino 2.25 (1.98-3.03)*** 1.57 (0.95-2.59)* Comprehensive HIV Knowledge Indigenous Reference Reference Cross-identified 1.17 (0.95-1.43) 1.46 (0.97-2.22)* Ladino 1.63 (1.40-1.89)*** 1.58 (1.27-1.97)*** *p<0.10; **p<0.05; ***p<0.001 ^Adjusted for age, education, marital status, household wealth quintile, urban/rural residence, geographic region of residence

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“The strength of relationship betweenethnicity and health outcomesappears influenced by „acculturation,‟the extent to which members of anethnic group have adopted the beliefsand practices of another group.”(Ford and Kelly, 2005)

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Conclusions Guatemalans construct ethnic self-identities that aren‟t reliably predicted by the “interviewer‟s observation,” but both may reflect useful concepts for health research Using an ethnic self-identity measure could increase the estimated size of the indigenous population in Guatemala by as much as 13% Ethnic self-identification has clear potential to increase estimates of HIV risk in the indigenous population, because of acculturation among the cross-identified

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Conclusions (cont.) The choice of measure could also have profound implications for analyses gauging ethnic disparities on other health outcomes If the cross-identified population grows, these measurement effects would be even more substantial Researchers should consider investing in formative research for question design, and engage indigenous communities in these efforts

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Next Steps Guatemala‟s Presidential Commission against Indigenous Racism and Discrimination is holding high-level meetings to discuss the findings of the study and implications for measuring ethnicity in national studies Both categorical ethnicity measures as well as ethnic markers (language, traditional dress), will likely be included in the 2013 ENSMI Analysis of these data could identify the questions or question sets with the highest construct validity, and that best distinguish population groups on health outcomes

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Health Service Utilization among Men Who Have Sex with Men and Transgender Women in El Salvador: Using gender identity andsexual orientation as distinct constructs

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Evolution of Public Health Approachto Sexual Minorities Homosexuality classified as a mental disorder in the DSM until 1973. Specific health needs of sexual minorities largely unexplored until the HIV epidemic in mid-1980s. Increased vulnerability to HIV led to a focus on gay men as a “risk group,” increasing stigma, both for these groups and people living with HIV. Movement to focus on behavior that increased transmission risk for HIV, i.e. “MSM - men who have sex with men.”

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Diversity among Sexual Minorities MSM MSM is a population that has emerged from HIV research and practice (1992)1  Defines the population based on a high-risk sexual behavior vs. sexual orientation (homosexual, gay, bisexual, heterosexual)  Allows for inclusion of men who do not identify as gay/homosexual and have sex with other men.  Examples include: gay-identified men, heterosexual men who have sex with other men, bisexual men, male sex workers (regardless of their sexual orientation)

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Diversity among Sexual Minorities Transgender A transgender (trans) person is someone whose gender identity differs from their biological sex (assigned to them at birth) Gender: What society believes about the appropriate roles, duties, rights, responsibilities, accepted behaviors, opportunities and status of men and women, in relation to one another Gender-identity is a personal sense of being a man, woman or something different, regardless of their sexual orientation Transgender women is a common term for people born biologically male with female identification or expression

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Study Overview USAID‟s Central American Regional HIV Program requested that MEASURE conduct a study of health service utilization among MSM in San Salvador to inform HIV prevention programming

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Challenge Do we include or exclude TW from our study? Local TW groups strongly advocated to not be considered as MSM, but they wanted data about their population Did not have sufficient funding for a TW-specific study

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How to include MSM and TW as part ofthe study population? Representation in the  Measuring constructs study population: accurately:  Outreach to/input from TW  Outreach to/input from TW organizations, field team organizations, field team  Inclusive eligibility criteria  Separate gender identity and questions and sexual orientation  TW as part of interviewer measures team  Inclusion of TW seed

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Reframing study eligibility criteria 2008 Biological and behavioral surveillance study  A man who had anal sex with another man in the last 12 months 2011 Health Service Utilization study  A man or transgender woman who had anal sex (receptive or penetrative) with another man or transgender woman in the last 12 months

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Questions inclusive of TWEXAMPLES: The last time you had an HIV test, did the provider have sufficient knowledge about the health needs of men who have sex with men or transgender women? Approximately how many people know that you form sexual relationships with men or transgender women?

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Gender Identity: Sexual OrientationPersonal sense ofbeing a man or awoman orsomething different ≠ One‟s erotic and emotional attraction to another • Man • Gay/Homosexual • Woman • Bisexual • Trans Woman • Heterosexual • Trans Man • Others • Others

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EL SALVADOR Biological and BehavioralSurveillance Study 2008Sexually, how do you identify yourself? 1 = Heterosexual 2 = Bisexual Sexual Orientation 3 = Gay/Homosexual 4 = Transvestite 5 = Transsexual Gender Identity 6 = Transgender 7 = Other

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Separating Sexual Orientation andGender Identity Sexual Orientation Gender identity In terms of your sexual  What is your gender orientation, how do you identify? (read responses) identify?  Man  Gay / homosexual  Woman  Bisexual  Transgender woman  Heterosexual  Other ________________  Other _______________

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Representation of TW in 2008 BBSScompared to 2011 HSU study 2008 BBSS 2011 HSU study 91.0% 81.5% 18.5% 9.1% Percent of sample population Percent of sample population TW, n=67 MSM, n=508 TW, n=164 MSM, n=506

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Sexual orientation by gender identity MSM TWGay/homosexual Bisexual Heterosexual Gay/homosexual Bisexual Heterosexual 52.0% 81.1% 43.2% 4.7% 11.1% 7.8% Sexual orientation Sexual orientation

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Medical insurance and regular healthcare provider, by gender identity MSM (n=506) 25% 27% Trans women (n=164) 14% 10% Medical insurance Regular health care provider

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Experiences of discrimination by a healthcare provider for being MSM or a transwoman (n=669) 71% 76% 74% 69% 52% 56% 55% 55% Treated with less Received poorer Refused services ** Needed to act more respect** quality of services** masculine* MSM Trans women

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Social vulnerability by gender identity 53.4% 28.6% 24.9% 29.0% 15.6% 12.5% Homelessness** Incarceration* Sex work** MSM TW

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Abuse and maltreatment due to sexual orientation Maltreatment and abuse was defined as, hitting, punching, k icking, threats, scoldin g or humiliations 21% 21% MSM (n=506) TW (n=164)Victim of abuse of maltreatment due to sexual orientation

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Conclusions Framing of eligibility criteria, composition of field team, and diversity in seeds for RDS, can achieve a larger proportion of TW as part of MSM studies Distinguishing between gender identity and sexual orientation as separate constructs is a more accurate measurement technique, and allowed for a more nuanced understanding of the needs of each subgroup.

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Works cited1. Beyrer, C. Baral, S. van Griensve, F. et al. (2012). Global epidemiology of HIV infection in men who have sex with men. Lancet. Vol. 380: 367- 377.2. Baral SD, Poteat T, Stromdahl S, Wirtz AL, Guadamuz TE, Beyrer C. Worldwide burden of HIV in transgender women: a systematic review and meta-analysis. Lancet Infect Dis 2013,13:214-222.3. Minesterio de Salud Pulica y Asistencia Social, Universidad de Valle, y Centros para la Prevencion y Control de Enfermedades. Encuesta Centroamericana de Vigilancia de Compartamiento Sexual y Prevalencia de VIH/ITS en Poblaciones Vulnerables, El Salvador. In; 2009.4. Joing United Nations Programme on HIV/AIDS; Country Fact Sheet, El Salvador, 2009.

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Special thanks to USAID Guatemala and the USAID Central America Regional HIV/AIDS Program for providing the support that made this work possible!MEASURE Evaluation is a MEASURE project funded by the U.S. Agencyfor International Development and implemented by the Carolina PopulationCenter at the University of North Carolina at Chapel Hill in partnership withFutures Group International, ICF Macro, John Snow, Inc., ManagementSciences for Health, and Tulane University. Views expressed in thispresentation do not necessarily reflect the views of USAID or the U.S.Government. MEASURE Evaluation is the USAID Global Health Bureausprimary vehicle for supporting improvements in monitoring and evaluationin population, health and nutrition worldwide.Visit us online at http://www.cpc.unc.edu/measure.

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EXTRA SLIDES

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Increased Risk for HIV among MSM & TW Disproportionate burden of HIV among men who have sex with men (MSM) and transgender women (TW) in both generalized and concentrated epidemic settings. Globally, the prevalence of HIV among MSM is estimated to be between 14-18%1 , and 19.1% among TW2. In San Salvador HIV prevalence among MSM is estimated at 10.8% among MSM and 9.7%% among TW3, but is only 0.8% for general population of El Salvador5.

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NICARAGUA Biological and BehavioralSurveillance Study 2009-2010 Among men who have sex with men there are those who self- identify as gay, bisexual, heterosexual, transvestite, transsexual, transgender. How do you self-identify? 1 = Heterosexual 2 = Bisexual Sexual Orientation 3 = Gay 4 = Homosexual 5 = Transvestite 6 = Transsexual Gender Identity 7 = Transgender 8 = Other

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Respondent-Driven Sampling10 A variant of chain referral sampling, wherein peers recruit peers. Designed to reach “hidden” populations that are socially networked. A coupon system is used to link recruits/recruiters, and secondary incentives. Initiated by purposively selected members of the target population, “seeds.” Reduces biases associated with chain-referral methods by limiting the number of coupons per participant, and achieving long recruitment chains that allows the sample to reach “equilibrium.”

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Recruitment ChainsN=670 Seed, men Seed, TW Recruit, men Recruit, TWMid November 2011 toMid February 2012

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Gender Identity & Sexual Orientation % (IC 95%) Gender Identity Male 81.5 (76.9-85.7) Trans female/Female 18.5 (14.3-23.1) Sexual Orientation Man - Gay / Homosexual 37.9 (32.1-43.4) Man - Bisexual / Heterosexual 43.7 (38.0-50.7) Trans woman - Heterosexual 14.3 (10.5-18.1) Trans woman - Gay / Bisexual 4.1 (2.0-6.0)