Presentation led by Dr. Katherine Andrinopoulos, an Assistant Professor at Tulane University, John Hembling, M&E Specialist, and Tory M. Taylor, also an M&E Specialist.

1. Measuring Ethnic and
Sexual Identities
Lessons from two studies in Central America

2. Session Objectives
After 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

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

4. 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

5. 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

6. 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?”

7. 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

8. 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)

9. Why does it matter how we measure
ethnicity 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

10. “A dispute over ethnicity marked census-taking day in Bolivia as
the landlocked Andean nation's 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

11. “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

12. 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

13. Three categories instead of two
Self- Interviewer
Categories identification Observation
Indigenous Indigenous Indigenous
Cross-identified Indigenous Ladino
Ladino Ladino Ladino

14. 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

15. “The strength of relationship between
ethnicity and health outcomes
appears influenced by „acculturation,‟
the extent to which members of an
ethnic group have adopted the beliefs
and practices of another group.”
(Ford and Kelly, 2005)

16. 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

17. 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

18. 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

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

20. Evolution of Public Health Approach
to 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.”

21. 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)

22. 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

23. 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

24. 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

25. How to include MSM and TW as part of
the 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

26. 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

27. Questions inclusive of TW
EXAMPLES:
 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?

28. Gender Identity: Sexual
Orientation
Personal sense of
being a man or a
woman or
something different
≠ One‟s erotic and
emotional attraction
to another
• Man • Gay/Homosexual
• Woman • Bisexual
• Trans Woman • Heterosexual
• Trans Man • Others
• Others

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

30. Separating Sexual Orientation and
Gender 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 _______________

31. Representation of TW in 2008 BBSS
compared 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

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

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

34. Experiences of discrimination by a health
care provider for being MSM or a trans
woman (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

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

36. 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

37. 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.

38. Works cited
1. 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.

39. 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. Agency
for International Development and implemented by the Carolina Population
Center at the University of North Carolina at Chapel Hill in partnership with
Futures Group International, ICF Macro, John Snow, Inc., Management
Sciences for Health, and Tulane University. Views expressed in this
presentation do not necessarily reflect the views of USAID or the U.S.
Government. MEASURE Evaluation is the USAID Global Health Bureau's
primary vehicle for supporting improvements in monitoring and evaluation
in population, health and nutrition worldwide.
Visit us online at http://www.cpc.unc.edu/measure.

40. EXTRA SLIDES

41. 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.

42. NICARAGUA Biological and Behavioral
Surveillance 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

43. 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.”

44. Recruitment Chains
N=670
Seed, men
Seed, TW
Recruit, men
Recruit, TW
Mid November 2011 to
Mid February 2012

45. 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)