Health, Aging and Sexuality in Marginalized Communities: LGBT Older Adults Emerging from the Margins Karen I. Fredriksen-Goldsen, PhD University of Washington.

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Health, Aging and Sexuality in Marginalized Communities: LGBT Older Adults Emerging from the Margins Karen I. Fredriksen-Goldsen, PhD University of Washington (Funded in part by NIH/NIA, 1R01AG A2; 2R01AG A1) CCBAR Annual Meeting ▪ University of Chicago ▪ October 17, 2013

Marginalization, Health & Aging Health and Aging in Marginalized Communities HIV and Medication Adherence in China Healthy Hearts in Tulalip Native Community National Health, Aging and Sexuality: Caring and Aging with Pride Over Time

Diversity in Aging Global worldwide aging By 2050, 130 million 50 and older (U.S. Census, 2012) 42% people of color (Vincent & Velkoff, 2010) Two million LGBT adults, age 50 and older Increasing number of diverse LGBT older adults

Research Gaps Sexual orientation key gap in health research (NIH, 2012; CDC, 2011) LGBT people at-risk and underserved (Institute of Medicine, 2011) First time in Healthy People 2020 (DHHS, 2011) Rapidly changing social context, policies and laws

Closing the Gap Behavioral Risk Factor Surveillance System (BRFSS-WA) Caring and Aging with Pride: Community-based 2,560 LGBT older adults, age 50 to 95 Testing of Complex Social Network Driven Sampling Continuation: Longitudinal Study

Figure 1. Non-response: Sexual Identity Question Over Time Time Trends in Rates of “Refuse to Answer” on Sexual Orientation by Age: Washington State Behavioral Risk Factor Surveillance System (BRFSS-WA),

Responses to sexual orientation question OtherNot sure/Don’t knowRefused to answer AOR(95% CI) Non-Hispanic White1.00 (ref) African American1.28 (0.41, 3.99)2.63** (1.36, 5.11)1.67 (0.99, 2.78) Asian American1.67 (0.53, 5.33)12.50*** (8.68, 18.02)4.42*** (3.15, 6.20) American Indian or Alaskan Native 0.92 (0.32, 2.65)1.02 (0.48, 2.16)1.34 (0.79, 2.25) Hispanic0.63 (0.30, 1.35)6.43*** (4.93, 8.39)2.02*** (1.47, 2.78) Note. ref=the reference group; AOR=adjusted odds ratio; CI=confidence interval; those who self- identified as “ heterosexual or LGB ” were treated as the baseline group; the analysis controlled for age, income, education, and year of interview. *P<.05; **P<.01; ***P<.001 Kim. H.-J. & Fredriksen-Goldsen, K. I. (2013). Nonresponse to a Question on Self-Identified Sexual Orientation in a Public Health Survey and its Relationship to Race and Ethnicity. American Journal of Public Health, 103(1), doi: /AJPH NIHMSID: NIHMS Table 1. Non-response to Sexual Orientation Questions by Race and Ethnicity

AOR = Adjusted Odds Ratio. Reference Group = Heterosexuals *p <.05. **p <.01. ***p <.001 Data source: Washington State Behavioral Risk Factor Surveillance System, Fredriksen-Goldsen K. I., Kim, H.-J., Barkan, S. E., Muraco, A., & Hoy-Ellis, C. P. (2013). Health Disparities among Lesbian, Gay, and Bisexual Older Adults: Results from a Population-Based Study, American Journal of Public Health, 103(10), doi: /AJPH WomenMen Heterosexual Lesbian Bisexual Heterosexual Gay Bisexual %AOR% Disability *** * Frequent Mental Distress * ** Table 2. BRFSS-WA Health Disparities: Disability and Mental Distress by Sexual Orientation and Gender

Health Disparities: Distinct Risks Lesbians and bisexual women: CVD risk and obesity Gay and bisexual men: Poor physical health and living alone ► “LGBT” is often used in research and services yet they are distinct groups with specific needs

Multi-level context Structural levels (social exclusion, institutional heterosexism) Individual levels (micro- aggressions, discrimination, victimization) Adverse and Health- Promoting Pathways Psychosocial (distinct social relations, social support, social network, LGBT community integration) Behavioral (exercise, diet, preventative care, sexual behavior, smoking) Biological (higher cortisol levels, allostatic load) Health Physical (physical health- related quality of life, HIV, obesity, cancer, CVD, disability) Mental (mental health- related quality of life, anxiety, depression, suicidal ideation) Social Positions (intersectionality) Life course (risks and opportunities) Figure 2. Health Equity Model

Life Course Perspective Social context Cultural meaning Structural location Pre-and Post-Stonewall Silent Generation Baby-Boomer

Research Hypotheses Based on the Health Equity Development model: ► We hypothesize that when controlling for social positions, elevated degrees of discrimination, stigma and non-disclosure of sexual orientation will be significantly associated with lower levels of physical and mental health related quality of life. ► We hypothesize that the configuration of structural, psychological, and behavioral explanatory factors predicting physical and mental health related quality of life, including degrees of discrimination, stigma and non-disclosure of sexual orientation, will be dissimilar for three age groups (age 50-64, age 65-79, and age 80 and older) of LGBT midlife and older adults.

CAP Survey: Risk & Protective Factors Community Participatory Integrated Research (CPIR) Eleven community partners West, central and east regions Reach across 48 states 2,560 LGBT older adults, age 50 to 95 Response rate: 63% Service users: 28%

Table 3. Measures PHQOL & MHQOL Measured using the SF-8 Health Survey (Ware et al., 2001), which consists of two components: Physical and mental quality of life. The summary scores were standardized. Cronbach’s α for PHQOL=.888; Cronbach’s α for MHQOL=.860 Lifetime Discrimination A 16-item measure based on the Lifetime Victimization Scale (D'Augelli & Grossman, 2001) and Discrimination Scale (Consortium for Political/Social Research, 2010). The summed score range 0 to 48. Cronbach’s α =.865 Disclosure Measured using modified items from the Outness Inventory Scale (Mohr & Fassinger, 2000). The summary scores ranges 1 to 4 with higher scores indicating higher degree of disclosure. Cronbach’s α =.917 Length of being closeted The difference between age of first sexual orientation disclosure – age of first sexual orientation awareness was divided by age (D'Augelli & Grossman, 2001) Internalized stigma Assessed by a five-item scale based on the Homosexual Stigma Scale (Liu, Feng, & Rhodes, 2009). Summary scores range from 1 to 4, with higher scores indicating higher degrees of internalized stigma. Cronbach’s α =.784 Social support The 4-item social support scale (Sherbourne & Stewart, 1991). Summary scores range from 1 to 4, with higher scores indicating higher degrees of social support. Cronbach’s α =.851 Social network size How many friends, family members, colleagues, and neighbors they interact with in a typical month? The total size of social network was calculated and summarized by quartiles, with 1 indicating small social network (bottom 25%) and 4 indicating very large social network (top 25%).

Table 3. Measures (cont) Collective Integration Measured to what extent participants have positive feeling of belonging to LGBT communities. The range is 1 to 4 with higher values indicating better feeling. Lack of physical activities Assessed by whether or not participants engaged in moderate activities for at least 10 minutes at a time, such as brisk walking, bicycling, vacuuming, gardening, or anything else that causes some increase in breathing or heart rate in a usual week (CDC, 2012). Substance use Current smoking (having ever smoked 100 or more cigarettes and currently smoke every day or some days), excessive drinking (having five or more drinks on one occasion during the past 30 days), or drug use (CDC, 2011; NIAAA, 2004) Regular checkup Assessed by asking participants whether or not they had a routine checkup within the past year (CDC) Chronic conditions Participants were asked whether they had ever been told by a doctor that they had the following conditions: high blood pressure, high cholesterol, heart attack, angina, stroke, cancer, arthritis, diabetes, asthma, or HIV/AIDS. The number of chronic health conditions was summed, with a range of 0 to 10. Background characteristics Standardized measures were used to assess background characteristics, including sexual orientation (0 = bisexual, 1 = gay or lesbian), gender (0 = men, 1 = women), gender identity (0=non-transgender, 1=transgender), race/ethnicity (0 = non-Hispanic White, 1 = African Americans, 2= Hispanics, 3 = others), income (0 = above 200% of the federal poverty level [FPL], 1 = at or below 200% FPL), unemployment, education (0 = some college or more, 1 = high school or less), relationships status (0 = married or partnered, 1 = other), and residency (0=rural, 1=urban).

Table 4. Background Characteristics All SampleAge 50-64Age 65-79Age 80 +p Lesbian/Gay (vs. Bisexual)92.94%91.37%94.64%91.90%0.008 Female37.15%44.78%32.99%22.35%0.000 Transgender6.83%10.51%4.23%2.35%0.000 Race White86.50%84.22%87.14%93.70%0.006 Black3.50%4.34%3.11%1.57% Hispanic5.59%6.12%5.78%2.36% Others4.41%5.32%3.97%2.36% Poverty30.72%26.76%32.97%38.77%0.000 Unemployment56.11%34.77%70.34%86.22%0.000 High school or less7.93%6.98%8.60%9.06%0.268 Partnered/married44.32%48.19%43.45%30.95%0.000 Urban96.63%96.44%96.60%97.61%0.712 # of Chronic Conditions1.955 (.029)1.666 (.042)2.165 (.042)2.286 (.090).000

Table 5. Explanatory and Outcome Variables All SamplePHRQOLMRQOL p M(SE) or %β (SE) Explanatory Variables Lifetime Discrimination (.150)-.028 (.003)**-.034 (.003)**.001 Disclosure (.012).052 (.030)†.082 (.031)**.266 Closeted.103 (.004)-.030 (.110)-.282 (.121)*.015 Stigma (.011)-.169 (.037)**-.341 (.037)**.000 Social Support (.017).222 (.026)**.449 (.027)**.000 Collective Integration (.017).094 (.028)**.180 (.029)**.000 Network Size, Small24.44%Ref Medium25.25%.134 (.056)*.293 (.059)**.002 Large25.29%.306 (.060)**.461 (.062)**.002 Very large25.02%.276 (.059)**.580 (.059)**.000 Lack of Physical Activity15.06%-.659 (.057)**-.602 (.061)**.290 Substance Use25.05%-.084 (.047)†-.249 (.049)**.000 Regular Health Check82.32%.011 (.053).163 (.051)**.000 # of Chronic Conditions1.955 (.029)-.280 (.012)**-.180 (.013)*.00 Outcome Variables Physical Quality of Life.000 (.020)-- Mental Quality of Life.000 (.020)--

Table 6. Explanatory and Outcome Variables All SampleAge 50-64Age 65-79Age 80 + p M(SE) or % Explanatory Variables Lifetime Discrimination (.150)7.637 (.225)6.051 (.216)3.592 (.293).000 Disclosure (.012)3.611 (.016)3.430 (.019)3.123 (.047).000 Closeted.103 (.004).097 (.005).105 (.006).122 (.014).178 Stigma (.011)1.463 (.018)1.456 (.017)1.569 (.039).023 Social Support (.017)3.113 (.025)3.089 (.023)3.007 (.047).118 Collective Integration (.017)3.451 (.024)3.418 (.024)3.241 (.050).001 Network Size, Small24.44%22.95%24.28%32.99%.015 Medium25.25%24.32%25.87%26.90% Large25.29% 26.46%19.29% Very large25.02%27.44%23.39%20.81% Lack of Physical Activity15.06%13.82%14.06%25.30%.000 Substance Use25.05%31.64%21.05%12.61%.000 Regular Health Check82.32%76.18%87.09%87.90%.000 # of Chronic Conditions1.955 (.029)1.666 (.042)2.165 (.042)2.286 (.090).000 Outcome Variables Physical Quality of Life.000 (.020).059 (.029)-.004 (.030)-.250 (.060).000 Mental Quality of Life.000 (.020)-.043 (.030).054 (.030)-.057 (.051).029

Physical Quality of Life Age 50-64Age 65-79Age 80+ β(SE)β β Demographic Factors Female **(0.057)-0.362**(0.063)-0.135(0.151) Poverty **(0.073)-0.164*(0.066)-0.438**(0.157) Unemployment **(0.062)-0.121*(0.062)-0.266(0.204) Partnered 0.060(0.064)0.033(0.066)-0.310**(0.148) LGB-Related Experiences Lifetime discrimination **(0.004)-0.016**(0.004)-0.045**(0.015) Network size Medium vs. Small (0.081)0.118(0.084)0.006(0.202) Large vs. Small 0.139(0.083)0.203*(0.085)0.094(0.233) Very large vs. Small 0.059(0.082)0.194*(0.091)0.236(0.215) Health Related Conditions Lack of Physical Activity **(0.081)-0.357**(0.083)-0.546**(0.178) # of Chronic Conditions **(0.021)-0.238**(0.020)-0.192**(0.049) Table 7. Model Fitting for Physical HRQOL

Figure 3. Lifetime Discrimination and PHQOL by Age Groups Slope ComparisonsWald Testp value Between Group 1 & 2χ 2 (1) = Between Group 1 & 3χ 2 (1) = Between Group 2 & 3χ 2 (1) =

Mental Quality of Life Age 50-64Age 65-79Age 80+ β(SE)β β Demographic Factors Female-0.206**(0.057)-0.258**(0.061)-0.006(0.154) Race Black vs. White-0.006(0.134)0.224(0.168)0.661(0.502) Hispanic vs. White-0.064(0.119)-0.232*(0.115)-0.101(0.663) Others vs. White-0.154(0.121)-0.139(0.156)0.397(0.577) Poverty **(0.073)-0.188**(0.063)-0.476**(0.154) Unemployment **(0.062)-0.057(0.060)-0.164(0.185) Partnered-0.004(0.064)0.047(0.064)-0.254*(0.131) LGB-Related Experiences Lifetime discrimination-0.024**(0.004)-0.012**(0.004)-0.034*(0.014) Stigma-0.109*(0.056)-0.111(0.059)-0.120(0.128) Social Support0.317**(0.044)0.249**(0.045)0.244(0.128) Network size Medium vs. Small0.163*(0.081)0.143(0.082)0.159(0.195) Large vs. Small0.105(0.083)0.268**(0.082)0.176(0.224) Very large vs. Small0.307**(0.082)0.358**(0.088)0.456*(0.227) Collective Integration0.029(0.041)0.082*(0.040)0.070(0.139) Health Related Conditions Lack of Physical Activity-0.469**(0.081)-0.295**(0.080)-0.474**(0.181) Substance Use-0.256**(0.059)-0.142*(0.068)0.087(0.256) Regular Health Check-0.036(0.064)0.172*(0.084)0.300(0.283) # of Chronic Conditions-0.100**(0.021)-0.150**(0.019)-0.066(0.049) Table 8. Model Fitting for Mental HRQOL

Figure 4. Lifetime Discrimination and MHQOL by Age Groups Slope ComparisonsWald Testp value Between Group 1 & 2χ 2 (1) = Between Group 1 & 3χ 2 (1) = Between Group 2 & 3χ 2 (1) =

Summary of Key Findings ► Identifies potentially modifiable factors associated with physical and mental health related quality of life of LGBT mid-life and older adults. ► Lifetime discrimination, lack of physical activities and poverty are common correlates of physical and mental health quality of life of LGBT adults, midlife and older. ► Social positions, structural and psychosocial processes and health behaviors differ by age groups. ► Even among the common correlates, the degree of influence may differ by age groups. ► The degree of lifetime discrimination is lower for older age groups, while the degree of internalized stigma is higher and the degree of sexual orientation disclosure is lower for older age groups. Non-disclosure for LGBT older adults may reduce risk of discrimination. Younger age group has higher degrees of discrimination, lower stigma and more disclosure. ► Limitations of study: cross-sectional, not generalizable, participants connect to community agencies, self-report measures.

Moving Forward National Health, Aging and Sexuality Study: Caring and Aging with Pride Over Time Next phase: LGBT mid-life and older adults, over time in order to test the theoretically specified model to understand the temporal relationships that may be amenable to change through targeted interventions. Participants, 50 and older, 3 points in time

Cohorts Baby Boom Generation (born between ) Silent Generation (born before 1947) Cohort differences and changing social context Multiple birth cohort design Analysis of cohort effects from age effects

Sample Hard to reach communities Some subgroups hidden within hidden populations Goal: Obtain a demographically diverse sample of LGBT older adults Ensure coverage of the heterogeneous nature of the populations Address noncoverage, overrepresentation, and other selection biases

Physiological Response to Stress a Sexual Identity Management & Social Resources Lifetime Victimization Everyday Discrimination a Adverse Health Behaviors a Health and Quality of Life a Perceived Stress Age effect, Cohort effect, Social positions (Gender and Race/Ethnicity) Longitudinal Model

Biological Measures ► Investigate link of poor physical health via allostatic load (AL), a physiological stress-related mechanism linking the psychosocial environment to physiological dysregulations ► AL measures: waist-to-hip ratio, blood pressure, cortisol, DHEA-S, total cholesterol, HDL cholesterol, hemoglobin A1c (blood sugar), and C- reactive protein. ► Non-invasive dried blood spots (DBS) ► Hypothesis: Controlling for lifetime victimization and other confounding variables, changes in physiological response to stress and health behaviors will partially mediate the effect of change in discrimination on subsequent health and QOL

Discussion – How can we maximize the use of bio- measures in this study and obtain quality information given limited resources? Next Steps