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A Profile of North Carolina Lesbian, Gay, and Bisexual Health Disparities, 2011 Derrick D. Matthews, PhD, MPH, and Joseph G. L. Lee, MPH, CPH
The unavailability of data from probabilitybased samples has been among the greatest impediments to identifying and addressing health disparities for lesbian, gay, and bisexual (LGB; or sexual minority) populations.1---3 The earliest studies restricted sampling of gay men and lesbians to psychiatric institutions and served to pathologize sexual minorities.4 Later efforts purposively sampled communities, providing more nuanced profiles of LGB health that proved instrumental in early identification of health disparities.5,6 Additionally, LGB and transgender communities themselves organized health data collection efforts even before the HIV/AIDS epidemic to document determinants of their health disparities, including barriers to health care, patterns of health behavior, and experiences of discrimination.7,8 Yet, notwithstanding the richness of these data, all nonprobability samples suffer from limitations of external validity.9 Concerns about the representativeness of data render studies using nonprobability sampling less influential in informing state and federal policy. Convenience samples have helped provide a burgeoning understanding of health disparities affecting LGB populations in the United States, alongside reports from the few states that have included sexual orientation in routine state surveillance.2 However, probability-based data about sexual minorities come primarily from surveys in a few states, including California,10 Massachusetts,11 New Mexico,12 Oregon,13 Vermont,14 and Washington,15 limiting the generalizability of results from these states to other parts of the country. Data on the health of sexual minorities may be particularly critical in the Southeastern United States, as this region generally bears a disproportionate burden of poorer health than do other parts of the country.16 Of additional concern is that many Southeastern states have failed to incorporate sexual minorities into existing laws (e.g., employment nondiscrimination) or have adopted new anti-LGB policies
Objectives. We investigated the health profile of lesbian, gay, and bisexual (LGB) adults in North Carolina, the first state in the South to include a measure of sexual orientation identity in a probability-based statewide health survey. Methods. Using data from 9876 respondents in the 2011 North Carolina Behavioral Risk Factor Surveillance Survey, we compared sexual minorities to heterosexuals on a variety of health indicators. Results. LGB respondents were younger and more likely to be reached by cell phone. Many examined indicators were not different by sexual orientation. Significant results, however, were consistent with findings from state population surveys in other regions of the country, including disparities in mental health and, among women, smoking. Conclusions. Reporting LGB identity in North Carolina is associated with poorer health. The concentration of anti-LGB policies in the South warrants ongoing monitoring of LGB health disparities in North Carolina and in other Southeastern states for potential effects on the health and well-being of LGB populations. (Am J Public Health. 2014;104:e98–e105. doi:10.2105/AJPH.2013. 301751)
(e.g., prohibiting legal recognition of same-sex relationships), both of which may create and exacerbate unhealthful social environments for LGB populations, even as evidence of the health impact of local and state policies on LGB health grows.17---20 Differences in policy context by region and state relevant to LGB and transgender people are shown in Figure 1. This context may yield health profiles different from New England and the Pacific Northwest, areas that currently have a greater number of policies in place that support LGB and transgender rights. Nevertheless, a substantial number of LGB people live across the South.21,22 The Southeastern state of North Carolina is estimated to be home to more than 212 000 LGB people,23 and the 2010 US Census shows same-sex couples living in all of North Carolina’s 100 counties.24 In 2011, North Carolina became the first state in the South to include a sexual orientation identity question on its statewide Behavioral Risk Factor Surveillance Survey (BRFSS). We examined the profile of health disparities of the LGB population living in North Carolina across domains derived from Healthy People 2020 objectives. Specifically, we a priori selected available BRFSS indicators from which previous
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research had identified LGB disparities responsible for substantial morbidity and mortality, related risk factors for poor health, and factors that have public health policy relevance. We categorized these indicators across 6 domains: health status, chronic disease risk behavior, injury prevention, screening behavior, health care access, and social context (i.e., variables that reflect the social environment that can influence health or health behavior) to present a health profile of LGB North Carolinians.
METHODS The North Carolina BRFSS is part of a national health surveillance system and is conducted jointly by North Carolina and the Centers for Disease Control and Prevention (CDC).25 This anonymous questionnaire is intended to provide data at the state level about a variety of health behaviors and health outcomes. In 2011 North Carolina began sampling cell phone---only households in addition to landline households to increase representation of the state’s population; cell phone use is associated with sociodemographic characteristics, health status, health behavior, and BRFSS
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14
12
10
Index of LGBT Policy Context
8
6
4
2
0
-2
PA DE NH MD NY RI ME NJ CT DC MA VT
AK ID MT WY OR WA
AL LA MS OK SC GA NC VA AR FL TN WV
UT TX AZ NV NM HI CA CO
-6
MI OH KS NE SD KY MO ND IN WI IL IA MN
-4
Midwest
Northeast
Northwest
Southeast
Southwest
Adoption
Employment
Hate crime
Housing
Marriage
Medical decision-making
Schools
FIGURE 1—Lesbian, gay, bisexual, and transgender (LGBT)-specific policies across the United States by region: May 2013.
nonresponse.26---28 Using the weighting method known as “raking” accompanied this change to more accurately reflect the state’s population with respect to age, gender, race/ethnicity, education, and marital status.29 The 2011 North Carolina BRFSS questionnaire contains 3 sections: CDC core modules, optional CDC modules that North Carolina elected to include, and state-added questions unique to North Carolina. All households were asked questions from the CDC core modules and were assigned to 1 of 3 survey completion
patterns to guide which of the remaining optional CDC modules and state-added questions they would answer. Landline households were assigned to 1 of 2 patterns, and cell phone---only households were assigned to the third. The final weighted response rate for the 2011 North Carolina BRFSS was 50% and resulted in 11 500 household responses.30
Measures North Carolina BRFSS interviewers determined and recorded respondent gender on the
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basis of voice and asked only if they were unsure. All other data were self-reported and, unless otherwise noted, were assessed with a single item. For respondents of non-Hispanic ethnicity who reported membership in more than 1 racial group, we assessed race using the answer to the question, “Which one of these groups would you say best represents your race?” Because eligibility for many social services in North Carolina is a function of the federal poverty guideline (FPG), we categorized the sample according to this threshold.
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However, BRFSS income categories do not directly correspond with the FPG. Following Conron et al.,11 we recoded income to the midpoint value for each category or for those who reported income of $75,000 or more to the 80th percentile of annual family income in 2011 ($115 866).31 We used the 2011 Health and Human Services family size---specific thresholds for poverty and self-reported household size to trichotomize income into 3 categories: £ 100% FPG, 101%---300% FPG, and greater than 300% FPG. In 2011, FPG was $10 890 for a family of 1 and $22 350 for a family of 4. We assessed depressive disorder and chronic disease status with items that respondents answered if they had ever been told they had the specific health condition by a doctor, nurse, or other health professional. We followed CDC guidelines for calculating body mass index (BMI; defined as weight in kilograms divided by the square of height in meters) using self-reported height and weight and used predetermined cutoff points of 25 and 30 to categorize respondents as overweight or obese, respectively.32 We defined current smoking as reporting having smoked at least 100 cigarettes in one’s life and also currently smoking every day or some days. We defined former smoking as having ever smoked 100 cigarettes and currently smoking not at all. We defined binge drinking as men having had 5 or more drinks on 1 occasion, or women having 4 or more drinks on 1 occasion in the past 30 days. We assessed total fruit and vegetable consumption by summing the responses to items that asked, “During the past month, how many times per day did you eat . . .” for the following: fruit juice, fruit, beans, dark green vegetables, orange-colored vegetables, and other vegetables. Sexual orientation identity was asked of all North Carolina BRFSS respondents and assessed with the following item: “Do you consider yourself to be (1) heterosexual or straight, (2) homosexual, gay, or lesbian, (3) bisexual, (4) or something else.” In total, 57 men and 58 women identified as homosexual, gay, or lesbian; 18 men and 28 women identified as bisexual. To maximize statistical power in the sample we combined all these responses into 1 sexual minority group. We excluded those who selected “something else”
(n = 27), reported they did not know or were not sure (an unprompted response category; n = 111), actively refused to answer the question (n = 310), or simply had no data available (presumably having terminated the survey before reaching the question; n = 1226) from our study sample. The analytic sample size was 9876. However, we assessed 2 items in a subset of respondents. Firearm ownership, assessed because of its association with unintentional injury and suicide deaths,33,34 was asked only of landline households (n = 8741). Opposition to an increase in the North Carolina cigarette tax, assessed because tobacco tax amount is negatively associated with tobacco use,35 was asked of half of landline households and all cell phone---only households (n = 4614).
Analysis We estimated proportions of selected sociodemographic characteristics by sexual orientation. We also used logistic regression to examine the relationship between sexual orientation and outcome variables, and we have presented age-adjusted odds ratios (AORs) and 95% confidence intervals (CIs). We did not adjust for other covariates because of the limited sample size of sexual minorities and the exploratory nature of the analysis. We used heterosexuals as the reference group for comparisons. We stratified all analyses by gender. The North Carolina State Center for Health Statistics calculated several sampling weights designed to adjust the sample to reflect the state population; multiple weights are necessary, as all modules were not asked of all households per the previously described survey completion patterns. Our analyses used the appropriate sampling weight to accommodate North Carolina BRFSS survey design. Missing values on sociodemographic variables ranged from 0.30% for education to 17.84% for income. We opted not to use multiple imputation. For income, however, we have presented missing income as a distinct category.36 Although the amount of missing data on sexual orientation and outcomes of interest was relatively low, we recognized that sexual orientation and other study variables were likely not missing completely at random,37 so we had Taylor series variance estimation in all analyses proceed under this
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assumption (i.e., the NOMCAR option in SAS). This preserved the North Carolina BRFSS sampling structure and allowed accurate parameter estimation in the event that missing data for any variable were associated with sampling strategy. We conducted 2-tailed statistical tests of association with an a priori a of 0.05. We conducted all analyses using survey procedures with SAS, version 9.3 (SAS Institute, Inc., Cary, NC).
RESULTS Table 1 presents the demographic characteristics of the study sample. About 2% of the weighted sample identified as a sexual minority (2.03%; 95% CI = 1.58, 2.50). Sexual minorities were younger than were their heterosexual counterparts, and sexual minority women were less likely than were heterosexual women to be living at less than 300% FPG. Sexual minorities were also more likely to have been recruited into the North Carolina BRFSS through the cell phone---sampling frame than were heterosexuals. On the basis of the unweighted data, 14.91% of sexual minorities and 7.32% of heterosexuals were members of cell phone---only households (P < .001). There was no significant difference in race/ethnicity, educational attainment, or employment status between sexual minorities and heterosexuals. Table 2 presents the relationship between sexual orientation and our outcomes of interest. We made all comparisons against a heterosexual reference group of the same gender. Mental health was consistently poorer for sexual minorities; both men (AOR = 2.62; 95% CI = 1.22, 5.62) and women (AOR = 2.60; 95% CI = 1.40, 4.82) were more likely to report experiencing 5 or more days of bad mental health in the past 30 days. Additionally, sexual minority men (AOR = 3.57; 95% CI = 1.76, 7.24) and women (AOR = 3.00; 95% CI = 1.58, 5.70) were more likely to have been diagnosed with any depressive disorder. Sexual minority women were less likely to have been diagnosed with angina or heart disease (AOR = 0.19; 95% CI = 0.04, 0.87). Sexual minority men were less likely to have ever smoked 100 cigarettes (AOR = 0.42; 95% CI = 0.22, 0.81), although sexual minority women were more likely to have done so (AOR = 2.92; 95% CI = 1.54, 5.54). Sexual
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TABLE 1—Demographic Characteristics by Gender and Sexual Orientation Identity: North Carolina Behavioral Risk Factor Surveillance System, 2011 Men
Women
Gay or Bisexual, No. (%)
Heterosexual, No. (%)
Lesbian or Bisexual, No. (%)
Heterosexual, No. (%)
Total
75 (2.27)
3605 (97.73)
86 (1.82)
6110 (98.17)
Age, y 18–34
15 (45.02)
439 (29.35)
17 (40.58)
655 (25.68)
35–44
10 (20.93)
485 (18.33)
23 (22.49)
806 (17.93)
45–54
21 (18.55)
680 (19.99)
23 (23.25)
1136 (19.40)
55–64
11 (7.52)
821 (16.17)
17 (10.72)
1355 (16.75)
‡ 65
18 (7.98)
1155 (16.16)
6 (2.96)
2089 (20.25)
White, non-Hispanic
58 (68.73)
2831 (70.65)
68 (77.67)
4593 (71.30)
Black, non-Hispanic Hispanic or Latino
10 (18.37) 3 (10.90)
445 (17.49) 163 (7.98)
9 (14.09) 2 (1.73)
1001 (20.69) 259 (5.24)
Other racial group
3 (2.00)
138 (3.88)
5 (6.51)
204 (2.76)
£ high school or GED
18 (32.03)
1442 (46.88)
25 (35.87)
2401 (40.93)
Some college or technical school
20 (42.62)
849 (29.36)
18 (30.26)
1659 (33.93)
College graduate
37 (25.36)
1303 (23.76)
43 (33.87)
2040 (25.14)
35 (52.44) 8 (14.09)
1850 (61.35) 272 (10.79)
55 (61.99) 10 (8.95)
2458 (46.96) 415 (9.29)
Characteristic
Race/ethnicity
Education
Employment status Employed Unemployed Unable to work Not in work forcea
6 (5.32)
266 (6.24)
6 (8.50)
568 (7.96)
26 (28.14)
1212 (21.61)
15 (20.57)
2646 (35.79)
Income £ 100% FPG
4 (5.93)
256 (8.53)
9 (6.57)
621 (11.17)
101%–300% FPG
25 (25.75)
1266 (27.72)
21 (15.87)
2224 (31.90)
> 300% FPG
39 (48.18)
1656 (51.37)
45 (59.39)
2113 (39.48)
7 (21.40)
427 (13.54)
11 (19.44)
1152 (17.45)
Missing income data
Note. FPG = federal poverty guideline; GED = general equivalency diploma. Numbers are unweighted counts. Percentages reflect weighted proportions. Percentages may not add to 100% because of rounding. The sample size was n = 9876. a Includes homemakers, retirees, and students.
minority women were also more likely to be either a current smoker (AOR = 2.01; 95% CI = 1.09, 4.09) or a former smoker (OR = 2.11; 95% CI = 1.09, 4.09). Sexual minority men were less likely to have never received an HIV test in their lifetime (AOR = 0.33; 95% CI = 0.13, 0.80). Sexual orientation was also associated with several elements of social context that could influence health and health behavior. Sexual minority women were more likely to report having been always or usually stressed about having enough money for their rent or mortgage (AOR = 2.31; 95% CI = 1.15, 4.64). Sexual minority women were also more likely to oppose an increase to the North Carolina
cigarette tax (AOR = 2.32; 95% CI = 1.09, 4.97). Sexual minority men were less likely than were their heterosexual counterparts to keep a firearm in the home (AOR = 0.27; 95% CI = 0.10, 0.74), although both this item and opposition to increasing the cigarette tax were assessed only among a subsample of households.
DISCUSSION Although North Carolina is the first Southeastern state to include sexual orientation identity on its BRFSS, many of our results were consistent with other studies of adult LGB
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populations. For example, we found that LGB adults in North Carolina experienced poorer mental health.11,15,38 We also found that sexual minority women were more likely to have ever been a smoker, to be a former smoker, or to be a current smoker.39 We were, however, surprised not to observe differences in health care access between LGB and heterosexual populations. The lack of policies to protect sexual minorities from employment discrimination as well as an inability to enroll same-sex partners on health insurance plans throughout much of the state might have suggested the presence of disparities in health care access.2 In Massachusetts, there was no difference observed between gay or lesbian and heterosexual adults either, although bisexual men and women were significantly less likely to have health insurance or a usual source of care11; our null finding may stem from the inability to observe bisexual respondents as a distinct group. Similarly, we were surprised to find that sexual minority men were less likely to have ever been a smoker than were their heterosexual counterparts. Unexpectedly, sexual minority women were more likely to experience worry or stress about paying rent or mortgage, even though they were less likely to be living below 300% FPG. This finding may be related to the adverse mental health sexual minority women experience. It may also reflect any number of unmeasured factors, particularly surrounding legal relationship recognition and associated consequences for income as mediated through the increased cost of health insurance benefits, income tax, and a variety of federal benefits.40 A combination of this income-related stress, and a greater likelihood of being a current smoker, may also be partially responsible for sexual minority women being opposed to any increase in the North Carolina cigarette tax. Finally, because of the small number of sexual minorities, we strongly caution against placing too much certainty into any 1 specific result; additional years of BRFSS data will be needed to confirm these findings and allow control of known confounders. Rather, we have presented these results to illustrate that as a whole, sexual orientation is a characteristic on which health disparities are patterned in North Carolina. That the disparities we did identify were primarily related to smoking and mental health outcomes points to the robustness of
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TABLE 2—Selected Health Characteristics by Gender and Sexual Orientation Identity: North Carolina Behavioral Risk Factor Surveillance System, 2011 Men Characteristic
Gay or Bisexual, No. (%)
Heterosexual, No. (%)
Women AORa (95% CI)
Lesbian or Bisexual, No. (%)
Heterosexual, No. (%)
AORa (95% CI)
Health status General Fair or poor
11 (15.02)
782 (18.93)
0.99 (0.35, 2.82)
16 (21.66)
1380 (20.22)
1.44 (0.65, 3.21)
18 (22.35)
669 (15.73)
1.96 (0.80, 4.80)
16 (15.67)
1414 (22.24)
0.79 (0.37, 1.70)
‡ 5 d bad mental health, past 30 d
19 (34.90)
496 (15.94)
2.62 (1.22, 5.62)
33 (47.92)
1261 (23.98)
2.60 (1.40, 4.82)
Any depressive disorder
26 (31.95)
471 (12.26)
3.57 (1.76, 7.24)
31 (41.68)
1349 (21.40)
3.00 (1.58, 5.70)
20 (29.58)
948 (20.98)
2.00 (0.88, 4.55)
26 (33.39)
1820 (25.00)
2.01 (0.96, 4.23)
Angina or heart disease Hypertension
5 (1.98) 27 (23.23)
296 (5.43) 1532 (33.69)
0.61 (0.21, 1.80) 0.87 (0.41, 1.81)
2 (0.42) 24 (21.96)
338 (4.10) 2526 (33.18)
0.19 (0.04, 0.87) 1.00 (0.43, 2.33)
High cholesterol
23 (36.84)
1503 (41.22)
1.07 (0.43, 2.65)
23 (23.79)
2457 (38.64)
0.67 (0.34, 1.32)
Diabetes
13 (7.39)
539 (11.38)
0.98 (0.51, 1.91)
5 (4.30)
816 (11.33)
0.55 (0.17, 1.82)
Asthma
5 (9.93)
339 (10.83)
0.79 (0.22, 2.80)
21 (27.69)
865 (15.71)
1.94 (0.96, 3.92)
Overweight or obese
48 (68.29)
2559 (71.16)
0.98 (0.47, 2.06)
45 (51.83)
3347 (60.46)
0.74 (0.39, 1.40)
Obese
14 (15.65)
990 (29.07)
0.47 (0.18, 1.20)
25 (32.47)
1599 (30.69)
1.08 (0.55, 2.13)
‡ 5 d bad physical health, past 30 d Mental health
Any disability limitations Chronic disability
Chronic disease risk behavior Tobacco Smoked ‡ 100 cigarettes in entire life
39 (31.70)
2085 (55.78)
0.42 (0.22, 0.81)
48 (62.89)
2509 (39.06)
2.92 (1.54, 5.54)
Current smoker
12 (13.81)
663 (23.57)
0.44 (0.16, 1.16)
27 (33.66)
1005 (18.59)
2.01 (1.04, 3.87)
Former smoker
27 (17.89)
1420 (32.19)
0.62 (0.31, 1.24)
21 (29.23)
1503 (20.46)
2.11 (1.09, 4.09)
15 (14.83)
552 (21.33)
0.50 (0.21, 1.20)
11 (17.68)
357 (9.00)
1.60 (0.65, 3.94)
Binge drinking, past 30 d Physical activity and nutrition No physical activity, past 30 d
17 (21.02)
869 (24.05)
0.88 (0.38, 2.02)
19 (24.81)
1804 (29.67)
0.89 (0.43, 1.88)
< 5 fruits or vegetables/d, past 30 d
60 (79.26)
3208 (89.66)
0.45 (0.20, 1.03)
72 (87.18)
4960 (82.76)
1.45 (0.68, 3.14)
4 (13.19) 13 (20.22)
363 (12.84) 1700 (49.28)
0.87 (0.27, 2.84) 0.27 (0.10, 0.74)
9 (9.53) 28 (46.57)
275 (5.14) 2077 (34.86)
1.68 (0.54, 5.24) 1.71 (0.85, 3.47)
Injury prevention Do not always use seatbelt Keep firearms in or around homeb Screening tests No HIV, lifetime
17 (31.27)
2372 (61.19)
0.33 (0.13, 0.80)
34 (39.10)
4010 (58.25)
0.69 (0.33, 1.48)
No blood cholesterol, lifetime
7 (25.73)
367 (20.04)
0.85 (0.27, 2.67)
16 (32.54)
455 (13.76)
2.01 (0.99, 4.08)
No routine checkup, past year
23 (38.31)
860 (32.27)
0.94 (0.40, 2.18)
20 (29.62)
1054 (21.34)
1.24 (0.61, 2.52)
No health care coverage No usual source of care
14 (30.36) 15 (32.71)
469 (21.19) 686 (33.17)
1.23 (0.48, 3.12) 0.62 (0.23, 1.67)
10 (13.55) 13 (15.68)
746 (17.72) 639 (16.77)
0.54 (0.22, 1.32) 0.61 (0.25, 1.47)
Cost prevented access, past year
12 (26.37)
421 (15.11)
1.77 (0.73, 4.29)
20 (26.32)
983 (21.31)
1.08 (0.51, 2.28)
Always or usually stressed about having money for rent or mortgage
8 (14.90)
411 (15.47)
0.90 (0.30, 2.72)
21 (39.44)
887 (19.82)
2.31 (1.15, 4.64)
Always or usually stressed about having money for nutritious meals
9 (10.64)
275 (9.67)
1.00 (0.36, 2.77)
9 (11.44)
613 (11.38)
0.91 (0.30, 2.75)
13 (33.71)
679 (38.36)
0.96 (0.39, 2.38)
21 (54.54)
829 (30.22)
2.32 (1.09, 4.97)
Health care access
Social context
Oppose $1 increase of North Carolina cigarette taxc
Note. AOR = adjusted odds ratio; CI = confidence interval. Numbers are unweighted counts. Percentages reflect weighted proportions. The sample size was n = 9876. a AORs use heterosexuals as the reference group and are adjusted for age. b Asked of all landline households (n = 8741). c Asked of half of landline households and all cell phone–only households (n = 4614).
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these findings in this and other samples.10,11,15 Elevated rates of smoking may be attributable to a variety of LGB-specific factors, ranging from internalized homophobia41 to targeted advertising on the part of tobacco companies.42 Differences in mental health outcomes may be owing, in part, to state policies and an environment that stigmatizes or renders invisible sexual minority lives, creating psychosocial stress in the process. As shown in Figure 1, these may be particularly problematic in the Southeastern United States. There were many variables for which we did not find a difference. The lack of statistical significance may simply reflect our small sample size, rather than true health parity between LGB and heterosexual populations. Nevertheless, consistently failing to observe health disparities when expected may offer clues on characteristics that protect sexual minorities from poor health.21,43,44
on if sexual orientation is defined by identity or behavior.38,46 Lastly, North Carolina’s BRFSS survey does not assess gender identity or gender expression; transgender populations remain invisible in these analyses. However, this study has several important strengths, including its use of a commonly used measure of sexual orientation identity in a large probability sample. Unlike past iterations of the BRFSS in other states, North Carolina did not exclude individuals older than 65 years from being asked about their sexual orientation.11,12 Despite limitations, this study provides important information on a population with distinct health disparities that has largely remained invisible in research within the South. Furthermore, to our knowledge this is the first exploration into differences in firearm ownership by sexual orientation.
Implications and Future Research Strengths and Limitations This study has a number of important limitations. First, with a single year of data, the inferences drawn are limited by a small, younger sample of the North Carolina LGB population. This small sample prevented us from controlling for other variables that may confound the relationship between sexual orientation and our outcomes, such as time spent in North Carolina. The sample size also prohibited the disaggregation of gays and lesbians from bisexuals, so our analysis cannot examine an important source of heterogeneity among sexual minorities.45,46 Second, although the sexual orientation identity question has been demonstrated as feasible to include in population health surveys in other states,12,47 as a stateadded question that is not included in the core demographic section it is among the last questions asked in the North Carolina BRFSS and thus not answered by anyone who terminated survey participation early. However, post hoc bivariate analyses revealed that those who did actively refuse to answer (n = 310) were more likely to have less education, be of Hispanic ethnicity, be older, or be women (data not shown), which is generally consistent with other state BRFSS surveys.37 Third, the North Carolina BRFSS only assessed the identity dimension of sexual orientation, and evidence from other surveillance studies illustrates that the constellation of health disparities changes depending
In 2012 North Carolina adopted a constitutional ban on same-sex marriage.48 These 2011 data are the only state-level probability sample we have about the health of sexual minorities in North Carolina before the amendment’s enactment, although they have limitations. Additional waves of the BRFSS, as well as comparisons to states with policies that are more LGB-affirming, may help to elucidate the impact this ban has on LGB populations in North Carolina, although previous research leads us to expect it will prove harmful to the health and well-being of sexual minorities.17,19 Many theories of health disparities and health behavior suggest the importance of state and local policies in the creation of healthful environments.49---51 These likely include health-promoting policies that do not currently exist in North Carolina, such as workplace nondiscrimination. Growing evidence of health disparities for sexual minorities has implications for state policies that can exacerbate such disparities. Furthermore, there may be a relationship between more immediate mental health status and distal chronic disease outcomes as mediated through maladaptive coping behaviors that warrants additional study.52,53 However, some North Carolina policies may serve to promote the health of sexual minorities. The state’s School Violence Prevention Act, which aims to protect students from bullying, including that based on real or perceived sexual
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orientation or gender identity, was passed in 2009.54,55 A study by the Gay, Lesbian, and Straight Education Network found that sexual minority students in schools operating under these enumerated policies have better outcomes, such as experiencing lower levels of victimization, than do students in schools without them.56 Although the benefit of recently enacted school policy may not be observable for the adult cohorts in the BRFSS, we call upon North Carolina to continue its leadership in the South by including sexual orientation in its Youth Risk Behavior Survey so that we can understand the health of the state’s young sexual minorities and develop appropriate interventions and policies to help them thrive throughout the life course. There are also technical implications for state health surveillance systems. Because the refusal rate of the sexual orientation question was low, as expected,12 we strongly encourage future iterations of the BRFSS to place sexual orientation among the other demographic variables rather than at the end. Data were missing for approximately 10% of respondents—a substantial proportion considering the already small number of sexual minorities in the sample. Finally, we recommend that other probability-based samples follow the example of the BRFSS and include cell phones in their sampling frame, as sexual minorities were more likely than were heterosexuals to be reached through this method.
Conclusions A community-organized statewide purposive sample in the early 1980s provided some of the first evidence of key health disparities for gays and lesbians across North Carolina. This 1985 North Carolina Lesbian and Gay Health Project study found substantial issues surrounding the sensitivity of health care service providers as well as elevated rates of chronic disease, sexually transmitted infections, mental health morbidity, and substance abuse.7 Twenty-eight years after North Carolina’s first survey of gay and lesbian health, we find similar patterns of health disparities in the BRFSS, a representative state health surveillance survey. We conclude, as did the North Carolina Lesbian and Gay Health Project, that “these issues warrant careful attention and creative responses.”7(p45) Such attention has
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been largely, though not entirely,54,57---60 absent in North Carolina and the South. Although these data from North Carolina provide the first, to our knowledge, statewide profile of LGB health disparities in the South using BRFSS data, it is clear that additional prioritization is needed across this region of the country by funders, health care providers, and policymakers to eliminate disparities by sexual orientation. j
About the Authors At the time of this study, Derrick D. Matthews and Joseph G. L. Lee were with the Department of Health Behavior, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. Correspondence should be sent to Derrick D. Matthews, Department of Behavioral and Community Health Sciences, Graduate School of Public Health, University of Pittsburgh, A223 Crabtree Hall, 130 DeSoto Street, Pittsburgh, PA 15261 (e-mail: [email protected]). Reprints can be ordered at http://www.ajph.org by clicking the “Reprints” link. This article was accepted October 21, 2013.
Contributors D. D. Matthews conducted the data analysis. Both authors conceptualized the study design and wrote the article.
Acknowledgments This study was partially supported by the National Institute of Mental Health (award T32MH094174). We thank the residents of North Carolina for their time completing the Behavioral Risk Factor Surveillance System (BRFSS) questionnaire. We also thank Sally Herndon, North Carolina Tobacco Prevention and Control branch head, and other dedicated public health professionals working on communicable disease prevention for their efforts and leadership ensuring sexual orientation was assessed in the North Carolina BRFSS. Thanks to Harry Herrick at the North Carolina State Center for Health Statistics for technical assistance with the data and to David Jolly for comments on earlier versions of the article.
Human Participant Protection This study did not require approval from an institutional review board because data were publically available and collected anonymously from a public health surveillance system in which respondents provided voluntary consent. We obtained a data use agreement with the North Carolina State Center for Health Statistics to use North Carolina Behavioral Risk Factor Surveillance System data.
References 1. Sell RL, Becker JB. Sexual orientation data collection and progress toward Healthy People 2010. Am J Public Health. 2001;91(6):876---882. 2. Institute of Medicine. The Health of Lesbian, Gay, Bisexual, and Transgender People: Building a Foundation for Better Understanding. Washington, DC: National Academies Press; 2011.
3. Mayer KH, Bradford JB, Makadon HJ, Stall R, Goldhammer H, Landers S. Sexual and gender minority health: what we know and what needs to be done. Am J Public Health. 2008;98(6):989---995.
20. Hatzenbuehler ML, Wieringa NF, Keyes KM. Community-level determinants of tobacco use disparities in lesbian, gay, and bisexual youth: results from a population-based study. Arch Pediatr Adolesc Med. 2011;165(6):527---532.
4. Loughery J. The Other Side of Silence—Men’s Lives and Gay Identities: A Twentieth Century History. New York, NY: Henry Holt; 1998.
21. Gates GJ, Ost J. The Gay and Lesbian Atlas. Washington, DC: Urban Institute Press; 2004.
5. Hooker E. The adjustment of the male overt homosexual. J Proj Tech. 1957;21(1):18---31.
22. Howard J. Men Like That: A Southern Queer History. Chicago, IL: University of Chicago Press; 1999.
6. Skinner WF. The prevalence and demographic predictors of illicit and licit drug use among lesbians and gay men. Am J Public Health. 1994;84(8):1307---1310.
23. Gates G. Same-Sex Couples and the Gay, Lesbian, Bisexual Population: New Estimates From the American Community Survey. Los Angeles, CA: Williams Institute; 2006.
7. Jolly DH. The North Carolina Lesbian and Gay Health Survey: Summary Report. Durham, NC: North Carolina Lesbian and Gay Health Project; 1985.
24. US Census Bureau. Unmarried-partner households by sex of partners, North Carolina counties. 2010. Available at: http://www.socialexplorer.com/pub/ reportdata/HtmlResults.aspx?reportid=R10490276. Accessed May 3, 2013.
8. Lekus IK. Health care, the AIDS crisis, and the politics of community: the North Carolina Lesbian and Gay Health Project, 1982---1996. In: Black AM, ed. Modern American Queer History. Philadelphia, PA: Temple University Press; 2001:227---252. 9. Sell RL, Petrulio C. Sampling homosexuals, bisexuals, gays, and lesbians for public health research: a review of the literature from 1990 to 1992. J Homosex. 1996;30(4):31---47. 10. Gruskin EP, Greenwood GL, Matevia M, Pollack LM, Bye LL. Disparities in smoking between the lesbian, gay, and bisexual population and the general population in California. Am J Public Health. 2007;97(8):1496--1502. 11. Conron KJ, Mimiaga MJ, Landers SJ. A populationbased study of sexual orientation identity and gender differences in adult health. Am J Public Health. 2010;100 (10):1953---1960. 12. VanKim NA, Padilla JL, Lee JG, Goldstein AO. Adding sexual orientation questions to statewide public health surveillance: New Mexico’s experience. Am J Public Health. 2010;100(12):2392---2396. 13. Hatzenbuehler ML, Pachankis JE, Wolff J. Religious climate and health risk behaviors in sexual minority youths: a population-based study. Am J Public Health. 2012;102(4):657---663. 14. Bontempo DE, d’Augelli AR. Effects of at-school victimization and sexual orientation on lesbian, gay, or bisexual youths’ health risk behavior. J Adolesc Health. 2002;30(5):364---374. 15. Fredriksen-Goldsen KI, Kim H-J, Barkan SE, Muraco A, Hoy-Ellis CP. Health disparities among lesbian, gay, and bisexual older adults: results from a populationbased study. Am J Public Health. 2013;103(10):1802--1809. 16. United Health Foundation. America’s Health Rankings. Minnetonka, MN; 2012. 17. Hatzenbuehler ML, Keyes KM, Hasin DS. State-level policies and psychiatric morbidity in lesbian, gay, and bisexual populations. Am J Public Health. 2009;99(12): 2275---2281. 18. Hatzenbuehler ML, Keyes KM, McLaughlin KA. The protective effects of social/contextual factors on psychiatric morbidity in LGB populations. Int J Epidemiol. 2011;40(4):1071---1080. 19. Hatzenbuehler ML, McLaughlin KA, Keyes KM, Hasin DS. The impact of institutional discrimination on psychiatric disorders in lesbian, gay, and bisexual populations: a prospective study. Am J Public Health. 2010;100(3):452---459.
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25. Centers for Disease Control and Prevention. Behavioral Risk Factor Surveillance System. 2013. Available at: http://www.cdc.gov/brfss/about/brfss_today. htm. Accessed May 7, 2013. 26. Battaglia MP, Frankel MR, Link MW. Improving standard poststratification techniques for random-digitdialing telephone surveys. Survey Res Methods. 2008; 2:11---19. 27. Rao RS, Link MW, Battaglia MP, Frankel MR, Giambo P, Mokdad AH. Assessing representativeness in RDD surveys: coverage and nonresponse in the Behavioral Risk Factor Surveillance System. In: American Statistical Association, eds. 2005 ASA Proceedings: Papers Presented at the Annual Meeting of the American Statistical Association; Minneapolis, Minnesota, August 7---11. [CD-ROM]. Alexandria, VA; 2005. 28. Link MW, Battaglia MP, Frankel MR, Osborn L, Mokdad AH. Reaching the US cell phone generation: comparison of cell phone survey results with an ongoing landline telephone survey. Public Opin Q. 2007;71(5): 814---839. 29. Pierannunzi C, Town M, Garvin W, Shaw FE, Balluz L. Methodologic changes in the Behavioral Risk Factor Surveillance System in 2011 and potential effects on prevalence estimates. MMWR Morb Mortal Wkly Rep. 2012;61(22):410---413. 30. Centers for Disease Control and Prevention. BRFSS combined landline and cell phone weighted response rates by state, 2011. 2013. Available at: http://www.cdc. gov/brfss/annual_data/2011/response_rates_11.htm. Accessed May 7, 2013. 31. US Census Bureau. Table F-1: Income limits for each fifth and top 5 percent of families (all races): 1947 to 2011. 2013. Available at: http://www.census.gov/hhes/ www/income/data/historical/families. Accessed April 1, 2013. 32. Centers for Disease Control and Prevention. About BMI for adults. 2013. Available at: http://www.cdc.gov/ healthyweight/assessing/bmi/adult_bmi/index.html. Accessed May 7, 2013. 33. Kung HC, Pearson JL, Wei R. Substance use, firearm availability, depressive symptoms, and mental health service utilization among White and African American suicide decedents aged 15 to 64 years. Ann Epidemiol. 2005;15(8):614---621. 34. Wiebe DJ. Firearms in US homes as a risk factor for unintentional gunshot fatality. Accid Anal Prev. 2003;35 (5):711---716.
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35. Chaloupka FJ, Straif K, Leon ME. Effectiveness of tax and price policies in tobacco control. Tob Control. 2011;20(3):235---238. 36. Kim S, Egerter S, Cubbin C, Takahashi ER, Braveman P. Potential implications of missing income data in population-based surveys: an example from a postpartum survey in California. Public Health Rep. 2007;122(6):753---763. 37. Kim HJ, Fredriksen-Goldsen KI. Nonresponse to a question on self-identified sexual orientation in a public health survey and its relationship to race and ethnicity. Am J Public Health. 2013;103(1):67---69. 38. Bostwick WB, Boyd CJ, Hughes TL, McCabe SE. Dimensions of sexual orientation and the prevalence of mood and anxiety disorders in the United States. Am J Public Health. 2009;100(3):468---475. 39. Lee JGL, Griffin GK, Melvin CL. Tobacco use among sexual minorities in the USA, 1987 to May 2007: a systematic review. Tob Control. 2009;18(4):275---282. 40. Badgett M. The economic value of marriage for same-sex couples. Drake Law Rev. 2010;58(4):1081--1116. 41. Blosnich J, Lee JG, Horn K. A systematic review of the aetiology of tobacco disparities for sexual minorities. Tob Control. 2013;22(2):66---73. 42. Stevens P, Carlson LM, Hinman JM. An analysis of tobacco industry marketing to lesbian, gay, bisexual, and transgender (LGBT) populations: strategies for mainstream tobacco control and prevention. Health Promot Pract. 2004;5(3, suppl):129S---134S. 43. Herrick AL, Lim SH, Wei C, et al. Resilience as an untapped resource in behavioral intervention design for gay men. AIDS Behav. 2011;15(suppl 1):S25---S29.
issues and research evidence. Psychol Bull. 2003;129 (5):674---697. 53. Hatzenbuehler ML, Nolen-Hoeksema S, Erickson SJ. Minority stress predictors of HIV risk behavior, substance use, and depressive symptoms: results from a prospective study of bereaved gay men. Health Psychol. 2008;27 (4):455---462. 54. Glazier R. The case for a comprehensive, effective, and realistic anti-bullying policy in North Carolina’s schools. N C Med J. 2008;69(6):495---497. 55. School Violence Prevention Act. S.B. 526, 2009 Gen. Assemb., Reg. Sess. (N.C. 2009). 56. Kosciw JG, Diaz EM, Greytak EA. The 2007 National School Climate Survey: The Experiences of Lesbian, Gay, Bisexual, and Transgender Youth in Our Nation’s Schools. New York, NY: Gay, Lesbian and Straight Education Network; 2008. 57. Halperin EC. Why a special issue of the North Carolina Medical Journal on gay and lesbian medicine? N C Med J. 1997;58(2):90---91. 58. Halperin EC. The North Carolina Medical Journal finds itself in the vanguard of progressive medical journalism or, the deputy editor finds his fifteen minutes of fame. N C Med J. 1999;60(3):138---139. 59. Rhodes SD, McCoy TP, Wilkin AM, Wolfson M. Behavioral risk disparities in a random sample of selfidentifying gay and non-gay male university students. J Homosex. 2009;56(8):1083---1100. 60. Rhodes SD, McCoy TP, Hergenrather KC, et al. Prevalence estimates of health risk behaviors of immigrant Latino men who have sex with men. J Rural Health. 2012;28(1):73---83.
44. Wexler LM, DiFluvio G, Burke TK. Resilience and marginalized youth: making a case for personal and collective meaning-making as part of resilience research in public health. Soc Sci Med. 2009;69(4):565---570. 45. McCabe SE, Hughes TL, Bostwick W, Boyd CJ. Assessment of difference in dimensions of sexual orientation: implications for substance use research in a college-age population. J Stud Alcohol. 2005;66(5): 620---629. 46. Matthews DD, Blosnich JR, Farmer GW, Adams BJ. Operational definitions of sexual orientation and estimates of adolescent health risk behaviors. LGBT Health. 2014;1(1):42---49. 47. Dilley JA, Simmons KW, Boysun MJ, Pizacani BA, Stark MJ. Demonstrating the importance and feasibility of including sexual orientation in public health surveys: health disparities in the Pacific Northwest. Am J Public Health. 2010;100(3):460---467. 48. State of North Carolina. Article XIV Sec. 6. Marriage: North Carolina Constitution; 2012. 49. Bronfenbrenner U. The Ecology of Human Development: Experiments by Nature and Design. Cambridge, MA: Harvard University Press; 1979. 50. McLeroy KR, Bibeau D, Steckler A, Glanz K. An ecological perspective on health promotion programs. Health Educ Behav. 1988;15(4):351---377. 51. Cockerham WC. Health lifestyle theory and the convergence of agency and structure. J Health Soc Behav. 2005;46(1):51---67. 52. Meyer IH. Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: conceptual
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A Profile of North Carolina Lesbian, Gay, and Bisexual Health Disparities, 2011 Derrick D. Matthews, PhD, MPH, and Joseph G. L. Lee, MPH, CPH
The unavailability of data from probabilitybased samples has been among the greatest impediments to identifying and addressing health disparities for lesbian, gay, and bisexual (LGB; or sexual minority) populations.1---3 The earliest studies restricted sampling of gay men and lesbians to psychiatric institutions and served to pathologize sexual minorities.4 Later efforts purposively sampled communities, providing more nuanced profiles of LGB health that proved instrumental in early identification of health disparities.5,6 Additionally, LGB and transgender communities themselves organized health data collection efforts even before the HIV/AIDS epidemic to document determinants of their health disparities, including barriers to health care, patterns of health behavior, and experiences of discrimination.7,8 Yet, notwithstanding the richness of these data, all nonprobability samples suffer from limitations of external validity.9 Concerns about the representativeness of data render studies using nonprobability sampling less influential in informing state and federal policy. Convenience samples have helped provide a burgeoning understanding of health disparities affecting LGB populations in the United States, alongside reports from the few states that have included sexual orientation in routine state surveillance.2 However, probability-based data about sexual minorities come primarily from surveys in a few states, including California,10 Massachusetts,11 New Mexico,12 Oregon,13 Vermont,14 and Washington,15 limiting the generalizability of results from these states to other parts of the country. Data on the health of sexual minorities may be particularly critical in the Southeastern United States, as this region generally bears a disproportionate burden of poorer health than do other parts of the country.16 Of additional concern is that many Southeastern states have failed to incorporate sexual minorities into existing laws (e.g., employment nondiscrimination) or have adopted new anti-LGB policies
Objectives. We investigated the health profile of lesbian, gay, and bisexual (LGB) adults in North Carolina, the first state in the South to include a measure of sexual orientation identity in a probability-based statewide health survey. Methods. Using data from 9876 respondents in the 2011 North Carolina Behavioral Risk Factor Surveillance Survey, we compared sexual minorities to heterosexuals on a variety of health indicators. Results. LGB respondents were younger and more likely to be reached by cell phone. Many examined indicators were not different by sexual orientation. Significant results, however, were consistent with findings from state population surveys in other regions of the country, including disparities in mental health and, among women, smoking. Conclusions. Reporting LGB identity in North Carolina is associated with poorer health. The concentration of anti-LGB policies in the South warrants ongoing monitoring of LGB health disparities in North Carolina and in other Southeastern states for potential effects on the health and well-being of LGB populations. (Am J Public Health. 2014;104:e98–e105. doi:10.2105/AJPH.2013. 301751)
(e.g., prohibiting legal recognition of same-sex relationships), both of which may create and exacerbate unhealthful social environments for LGB populations, even as evidence of the health impact of local and state policies on LGB health grows.17---20 Differences in policy context by region and state relevant to LGB and transgender people are shown in Figure 1. This context may yield health profiles different from New England and the Pacific Northwest, areas that currently have a greater number of policies in place that support LGB and transgender rights. Nevertheless, a substantial number of LGB people live across the South.21,22 The Southeastern state of North Carolina is estimated to be home to more than 212 000 LGB people,23 and the 2010 US Census shows same-sex couples living in all of North Carolina’s 100 counties.24 In 2011, North Carolina became the first state in the South to include a sexual orientation identity question on its statewide Behavioral Risk Factor Surveillance Survey (BRFSS). We examined the profile of health disparities of the LGB population living in North Carolina across domains derived from Healthy People 2020 objectives. Specifically, we a priori selected available BRFSS indicators from which previous
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research had identified LGB disparities responsible for substantial morbidity and mortality, related risk factors for poor health, and factors that have public health policy relevance. We categorized these indicators across 6 domains: health status, chronic disease risk behavior, injury prevention, screening behavior, health care access, and social context (i.e., variables that reflect the social environment that can influence health or health behavior) to present a health profile of LGB North Carolinians.
METHODS The North Carolina BRFSS is part of a national health surveillance system and is conducted jointly by North Carolina and the Centers for Disease Control and Prevention (CDC).25 This anonymous questionnaire is intended to provide data at the state level about a variety of health behaviors and health outcomes. In 2011 North Carolina began sampling cell phone---only households in addition to landline households to increase representation of the state’s population; cell phone use is associated with sociodemographic characteristics, health status, health behavior, and BRFSS
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14
12
10
Index of LGBT Policy Context
8
6
4
2
0
-2
PA DE NH MD NY RI ME NJ CT DC MA VT
AK ID MT WY OR WA
AL LA MS OK SC GA NC VA AR FL TN WV
UT TX AZ NV NM HI CA CO
-6
MI OH KS NE SD KY MO ND IN WI IL IA MN
-4
Midwest
Northeast
Northwest
Southeast
Southwest
Adoption
Employment
Hate crime
Housing
Marriage
Medical decision-making
Schools
FIGURE 1—Lesbian, gay, bisexual, and transgender (LGBT)-specific policies across the United States by region: May 2013.
nonresponse.26---28 Using the weighting method known as “raking” accompanied this change to more accurately reflect the state’s population with respect to age, gender, race/ethnicity, education, and marital status.29 The 2011 North Carolina BRFSS questionnaire contains 3 sections: CDC core modules, optional CDC modules that North Carolina elected to include, and state-added questions unique to North Carolina. All households were asked questions from the CDC core modules and were assigned to 1 of 3 survey completion
patterns to guide which of the remaining optional CDC modules and state-added questions they would answer. Landline households were assigned to 1 of 2 patterns, and cell phone---only households were assigned to the third. The final weighted response rate for the 2011 North Carolina BRFSS was 50% and resulted in 11 500 household responses.30
Measures North Carolina BRFSS interviewers determined and recorded respondent gender on the
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basis of voice and asked only if they were unsure. All other data were self-reported and, unless otherwise noted, were assessed with a single item. For respondents of non-Hispanic ethnicity who reported membership in more than 1 racial group, we assessed race using the answer to the question, “Which one of these groups would you say best represents your race?” Because eligibility for many social services in North Carolina is a function of the federal poverty guideline (FPG), we categorized the sample according to this threshold.
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However, BRFSS income categories do not directly correspond with the FPG. Following Conron et al.,11 we recoded income to the midpoint value for each category or for those who reported income of $75,000 or more to the 80th percentile of annual family income in 2011 ($115 866).31 We used the 2011 Health and Human Services family size---specific thresholds for poverty and self-reported household size to trichotomize income into 3 categories: £ 100% FPG, 101%---300% FPG, and greater than 300% FPG. In 2011, FPG was $10 890 for a family of 1 and $22 350 for a family of 4. We assessed depressive disorder and chronic disease status with items that respondents answered if they had ever been told they had the specific health condition by a doctor, nurse, or other health professional. We followed CDC guidelines for calculating body mass index (BMI; defined as weight in kilograms divided by the square of height in meters) using self-reported height and weight and used predetermined cutoff points of 25 and 30 to categorize respondents as overweight or obese, respectively.32 We defined current smoking as reporting having smoked at least 100 cigarettes in one’s life and also currently smoking every day or some days. We defined former smoking as having ever smoked 100 cigarettes and currently smoking not at all. We defined binge drinking as men having had 5 or more drinks on 1 occasion, or women having 4 or more drinks on 1 occasion in the past 30 days. We assessed total fruit and vegetable consumption by summing the responses to items that asked, “During the past month, how many times per day did you eat . . .” for the following: fruit juice, fruit, beans, dark green vegetables, orange-colored vegetables, and other vegetables. Sexual orientation identity was asked of all North Carolina BRFSS respondents and assessed with the following item: “Do you consider yourself to be (1) heterosexual or straight, (2) homosexual, gay, or lesbian, (3) bisexual, (4) or something else.” In total, 57 men and 58 women identified as homosexual, gay, or lesbian; 18 men and 28 women identified as bisexual. To maximize statistical power in the sample we combined all these responses into 1 sexual minority group. We excluded those who selected “something else”
(n = 27), reported they did not know or were not sure (an unprompted response category; n = 111), actively refused to answer the question (n = 310), or simply had no data available (presumably having terminated the survey before reaching the question; n = 1226) from our study sample. The analytic sample size was 9876. However, we assessed 2 items in a subset of respondents. Firearm ownership, assessed because of its association with unintentional injury and suicide deaths,33,34 was asked only of landline households (n = 8741). Opposition to an increase in the North Carolina cigarette tax, assessed because tobacco tax amount is negatively associated with tobacco use,35 was asked of half of landline households and all cell phone---only households (n = 4614).
Analysis We estimated proportions of selected sociodemographic characteristics by sexual orientation. We also used logistic regression to examine the relationship between sexual orientation and outcome variables, and we have presented age-adjusted odds ratios (AORs) and 95% confidence intervals (CIs). We did not adjust for other covariates because of the limited sample size of sexual minorities and the exploratory nature of the analysis. We used heterosexuals as the reference group for comparisons. We stratified all analyses by gender. The North Carolina State Center for Health Statistics calculated several sampling weights designed to adjust the sample to reflect the state population; multiple weights are necessary, as all modules were not asked of all households per the previously described survey completion patterns. Our analyses used the appropriate sampling weight to accommodate North Carolina BRFSS survey design. Missing values on sociodemographic variables ranged from 0.30% for education to 17.84% for income. We opted not to use multiple imputation. For income, however, we have presented missing income as a distinct category.36 Although the amount of missing data on sexual orientation and outcomes of interest was relatively low, we recognized that sexual orientation and other study variables were likely not missing completely at random,37 so we had Taylor series variance estimation in all analyses proceed under this
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assumption (i.e., the NOMCAR option in SAS). This preserved the North Carolina BRFSS sampling structure and allowed accurate parameter estimation in the event that missing data for any variable were associated with sampling strategy. We conducted 2-tailed statistical tests of association with an a priori a of 0.05. We conducted all analyses using survey procedures with SAS, version 9.3 (SAS Institute, Inc., Cary, NC).
RESULTS Table 1 presents the demographic characteristics of the study sample. About 2% of the weighted sample identified as a sexual minority (2.03%; 95% CI = 1.58, 2.50). Sexual minorities were younger than were their heterosexual counterparts, and sexual minority women were less likely than were heterosexual women to be living at less than 300% FPG. Sexual minorities were also more likely to have been recruited into the North Carolina BRFSS through the cell phone---sampling frame than were heterosexuals. On the basis of the unweighted data, 14.91% of sexual minorities and 7.32% of heterosexuals were members of cell phone---only households (P < .001). There was no significant difference in race/ethnicity, educational attainment, or employment status between sexual minorities and heterosexuals. Table 2 presents the relationship between sexual orientation and our outcomes of interest. We made all comparisons against a heterosexual reference group of the same gender. Mental health was consistently poorer for sexual minorities; both men (AOR = 2.62; 95% CI = 1.22, 5.62) and women (AOR = 2.60; 95% CI = 1.40, 4.82) were more likely to report experiencing 5 or more days of bad mental health in the past 30 days. Additionally, sexual minority men (AOR = 3.57; 95% CI = 1.76, 7.24) and women (AOR = 3.00; 95% CI = 1.58, 5.70) were more likely to have been diagnosed with any depressive disorder. Sexual minority women were less likely to have been diagnosed with angina or heart disease (AOR = 0.19; 95% CI = 0.04, 0.87). Sexual minority men were less likely to have ever smoked 100 cigarettes (AOR = 0.42; 95% CI = 0.22, 0.81), although sexual minority women were more likely to have done so (AOR = 2.92; 95% CI = 1.54, 5.54). Sexual
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TABLE 1—Demographic Characteristics by Gender and Sexual Orientation Identity: North Carolina Behavioral Risk Factor Surveillance System, 2011 Men
Women
Gay or Bisexual, No. (%)
Heterosexual, No. (%)
Lesbian or Bisexual, No. (%)
Heterosexual, No. (%)
Total
75 (2.27)
3605 (97.73)
86 (1.82)
6110 (98.17)
Age, y 18–34
15 (45.02)
439 (29.35)
17 (40.58)
655 (25.68)
35–44
10 (20.93)
485 (18.33)
23 (22.49)
806 (17.93)
45–54
21 (18.55)
680 (19.99)
23 (23.25)
1136 (19.40)
55–64
11 (7.52)
821 (16.17)
17 (10.72)
1355 (16.75)
‡ 65
18 (7.98)
1155 (16.16)
6 (2.96)
2089 (20.25)
White, non-Hispanic
58 (68.73)
2831 (70.65)
68 (77.67)
4593 (71.30)
Black, non-Hispanic Hispanic or Latino
10 (18.37) 3 (10.90)
445 (17.49) 163 (7.98)
9 (14.09) 2 (1.73)
1001 (20.69) 259 (5.24)
Other racial group
3 (2.00)
138 (3.88)
5 (6.51)
204 (2.76)
£ high school or GED
18 (32.03)
1442 (46.88)
25 (35.87)
2401 (40.93)
Some college or technical school
20 (42.62)
849 (29.36)
18 (30.26)
1659 (33.93)
College graduate
37 (25.36)
1303 (23.76)
43 (33.87)
2040 (25.14)
35 (52.44) 8 (14.09)
1850 (61.35) 272 (10.79)
55 (61.99) 10 (8.95)
2458 (46.96) 415 (9.29)
Characteristic
Race/ethnicity
Education
Employment status Employed Unemployed Unable to work Not in work forcea
6 (5.32)
266 (6.24)
6 (8.50)
568 (7.96)
26 (28.14)
1212 (21.61)
15 (20.57)
2646 (35.79)
Income £ 100% FPG
4 (5.93)
256 (8.53)
9 (6.57)
621 (11.17)
101%–300% FPG
25 (25.75)
1266 (27.72)
21 (15.87)
2224 (31.90)
> 300% FPG
39 (48.18)
1656 (51.37)
45 (59.39)
2113 (39.48)
7 (21.40)
427 (13.54)
11 (19.44)
1152 (17.45)
Missing income data
Note. FPG = federal poverty guideline; GED = general equivalency diploma. Numbers are unweighted counts. Percentages reflect weighted proportions. Percentages may not add to 100% because of rounding. The sample size was n = 9876. a Includes homemakers, retirees, and students.
minority women were also more likely to be either a current smoker (AOR = 2.01; 95% CI = 1.09, 4.09) or a former smoker (OR = 2.11; 95% CI = 1.09, 4.09). Sexual minority men were less likely to have never received an HIV test in their lifetime (AOR = 0.33; 95% CI = 0.13, 0.80). Sexual orientation was also associated with several elements of social context that could influence health and health behavior. Sexual minority women were more likely to report having been always or usually stressed about having enough money for their rent or mortgage (AOR = 2.31; 95% CI = 1.15, 4.64). Sexual minority women were also more likely to oppose an increase to the North Carolina
cigarette tax (AOR = 2.32; 95% CI = 1.09, 4.97). Sexual minority men were less likely than were their heterosexual counterparts to keep a firearm in the home (AOR = 0.27; 95% CI = 0.10, 0.74), although both this item and opposition to increasing the cigarette tax were assessed only among a subsample of households.
DISCUSSION Although North Carolina is the first Southeastern state to include sexual orientation identity on its BRFSS, many of our results were consistent with other studies of adult LGB
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populations. For example, we found that LGB adults in North Carolina experienced poorer mental health.11,15,38 We also found that sexual minority women were more likely to have ever been a smoker, to be a former smoker, or to be a current smoker.39 We were, however, surprised not to observe differences in health care access between LGB and heterosexual populations. The lack of policies to protect sexual minorities from employment discrimination as well as an inability to enroll same-sex partners on health insurance plans throughout much of the state might have suggested the presence of disparities in health care access.2 In Massachusetts, there was no difference observed between gay or lesbian and heterosexual adults either, although bisexual men and women were significantly less likely to have health insurance or a usual source of care11; our null finding may stem from the inability to observe bisexual respondents as a distinct group. Similarly, we were surprised to find that sexual minority men were less likely to have ever been a smoker than were their heterosexual counterparts. Unexpectedly, sexual minority women were more likely to experience worry or stress about paying rent or mortgage, even though they were less likely to be living below 300% FPG. This finding may be related to the adverse mental health sexual minority women experience. It may also reflect any number of unmeasured factors, particularly surrounding legal relationship recognition and associated consequences for income as mediated through the increased cost of health insurance benefits, income tax, and a variety of federal benefits.40 A combination of this income-related stress, and a greater likelihood of being a current smoker, may also be partially responsible for sexual minority women being opposed to any increase in the North Carolina cigarette tax. Finally, because of the small number of sexual minorities, we strongly caution against placing too much certainty into any 1 specific result; additional years of BRFSS data will be needed to confirm these findings and allow control of known confounders. Rather, we have presented these results to illustrate that as a whole, sexual orientation is a characteristic on which health disparities are patterned in North Carolina. That the disparities we did identify were primarily related to smoking and mental health outcomes points to the robustness of
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TABLE 2—Selected Health Characteristics by Gender and Sexual Orientation Identity: North Carolina Behavioral Risk Factor Surveillance System, 2011 Men Characteristic
Gay or Bisexual, No. (%)
Heterosexual, No. (%)
Women AORa (95% CI)
Lesbian or Bisexual, No. (%)
Heterosexual, No. (%)
AORa (95% CI)
Health status General Fair or poor
11 (15.02)
782 (18.93)
0.99 (0.35, 2.82)
16 (21.66)
1380 (20.22)
1.44 (0.65, 3.21)
18 (22.35)
669 (15.73)
1.96 (0.80, 4.80)
16 (15.67)
1414 (22.24)
0.79 (0.37, 1.70)
‡ 5 d bad mental health, past 30 d
19 (34.90)
496 (15.94)
2.62 (1.22, 5.62)
33 (47.92)
1261 (23.98)
2.60 (1.40, 4.82)
Any depressive disorder
26 (31.95)
471 (12.26)
3.57 (1.76, 7.24)
31 (41.68)
1349 (21.40)
3.00 (1.58, 5.70)
20 (29.58)
948 (20.98)
2.00 (0.88, 4.55)
26 (33.39)
1820 (25.00)
2.01 (0.96, 4.23)
Angina or heart disease Hypertension
5 (1.98) 27 (23.23)
296 (5.43) 1532 (33.69)
0.61 (0.21, 1.80) 0.87 (0.41, 1.81)
2 (0.42) 24 (21.96)
338 (4.10) 2526 (33.18)
0.19 (0.04, 0.87) 1.00 (0.43, 2.33)
High cholesterol
23 (36.84)
1503 (41.22)
1.07 (0.43, 2.65)
23 (23.79)
2457 (38.64)
0.67 (0.34, 1.32)
Diabetes
13 (7.39)
539 (11.38)
0.98 (0.51, 1.91)
5 (4.30)
816 (11.33)
0.55 (0.17, 1.82)
Asthma
5 (9.93)
339 (10.83)
0.79 (0.22, 2.80)
21 (27.69)
865 (15.71)
1.94 (0.96, 3.92)
Overweight or obese
48 (68.29)
2559 (71.16)
0.98 (0.47, 2.06)
45 (51.83)
3347 (60.46)
0.74 (0.39, 1.40)
Obese
14 (15.65)
990 (29.07)
0.47 (0.18, 1.20)
25 (32.47)
1599 (30.69)
1.08 (0.55, 2.13)
‡ 5 d bad physical health, past 30 d Mental health
Any disability limitations Chronic disability
Chronic disease risk behavior Tobacco Smoked ‡ 100 cigarettes in entire life
39 (31.70)
2085 (55.78)
0.42 (0.22, 0.81)
48 (62.89)
2509 (39.06)
2.92 (1.54, 5.54)
Current smoker
12 (13.81)
663 (23.57)
0.44 (0.16, 1.16)
27 (33.66)
1005 (18.59)
2.01 (1.04, 3.87)
Former smoker
27 (17.89)
1420 (32.19)
0.62 (0.31, 1.24)
21 (29.23)
1503 (20.46)
2.11 (1.09, 4.09)
15 (14.83)
552 (21.33)
0.50 (0.21, 1.20)
11 (17.68)
357 (9.00)
1.60 (0.65, 3.94)
Binge drinking, past 30 d Physical activity and nutrition No physical activity, past 30 d
17 (21.02)
869 (24.05)
0.88 (0.38, 2.02)
19 (24.81)
1804 (29.67)
0.89 (0.43, 1.88)
< 5 fruits or vegetables/d, past 30 d
60 (79.26)
3208 (89.66)
0.45 (0.20, 1.03)
72 (87.18)
4960 (82.76)
1.45 (0.68, 3.14)
4 (13.19) 13 (20.22)
363 (12.84) 1700 (49.28)
0.87 (0.27, 2.84) 0.27 (0.10, 0.74)
9 (9.53) 28 (46.57)
275 (5.14) 2077 (34.86)
1.68 (0.54, 5.24) 1.71 (0.85, 3.47)
Injury prevention Do not always use seatbelt Keep firearms in or around homeb Screening tests No HIV, lifetime
17 (31.27)
2372 (61.19)
0.33 (0.13, 0.80)
34 (39.10)
4010 (58.25)
0.69 (0.33, 1.48)
No blood cholesterol, lifetime
7 (25.73)
367 (20.04)
0.85 (0.27, 2.67)
16 (32.54)
455 (13.76)
2.01 (0.99, 4.08)
No routine checkup, past year
23 (38.31)
860 (32.27)
0.94 (0.40, 2.18)
20 (29.62)
1054 (21.34)
1.24 (0.61, 2.52)
No health care coverage No usual source of care
14 (30.36) 15 (32.71)
469 (21.19) 686 (33.17)
1.23 (0.48, 3.12) 0.62 (0.23, 1.67)
10 (13.55) 13 (15.68)
746 (17.72) 639 (16.77)
0.54 (0.22, 1.32) 0.61 (0.25, 1.47)
Cost prevented access, past year
12 (26.37)
421 (15.11)
1.77 (0.73, 4.29)
20 (26.32)
983 (21.31)
1.08 (0.51, 2.28)
Always or usually stressed about having money for rent or mortgage
8 (14.90)
411 (15.47)
0.90 (0.30, 2.72)
21 (39.44)
887 (19.82)
2.31 (1.15, 4.64)
Always or usually stressed about having money for nutritious meals
9 (10.64)
275 (9.67)
1.00 (0.36, 2.77)
9 (11.44)
613 (11.38)
0.91 (0.30, 2.75)
13 (33.71)
679 (38.36)
0.96 (0.39, 2.38)
21 (54.54)
829 (30.22)
2.32 (1.09, 4.97)
Health care access
Social context
Oppose $1 increase of North Carolina cigarette taxc
Note. AOR = adjusted odds ratio; CI = confidence interval. Numbers are unweighted counts. Percentages reflect weighted proportions. The sample size was n = 9876. a AORs use heterosexuals as the reference group and are adjusted for age. b Asked of all landline households (n = 8741). c Asked of half of landline households and all cell phone–only households (n = 4614).
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these findings in this and other samples.10,11,15 Elevated rates of smoking may be attributable to a variety of LGB-specific factors, ranging from internalized homophobia41 to targeted advertising on the part of tobacco companies.42 Differences in mental health outcomes may be owing, in part, to state policies and an environment that stigmatizes or renders invisible sexual minority lives, creating psychosocial stress in the process. As shown in Figure 1, these may be particularly problematic in the Southeastern United States. There were many variables for which we did not find a difference. The lack of statistical significance may simply reflect our small sample size, rather than true health parity between LGB and heterosexual populations. Nevertheless, consistently failing to observe health disparities when expected may offer clues on characteristics that protect sexual minorities from poor health.21,43,44
on if sexual orientation is defined by identity or behavior.38,46 Lastly, North Carolina’s BRFSS survey does not assess gender identity or gender expression; transgender populations remain invisible in these analyses. However, this study has several important strengths, including its use of a commonly used measure of sexual orientation identity in a large probability sample. Unlike past iterations of the BRFSS in other states, North Carolina did not exclude individuals older than 65 years from being asked about their sexual orientation.11,12 Despite limitations, this study provides important information on a population with distinct health disparities that has largely remained invisible in research within the South. Furthermore, to our knowledge this is the first exploration into differences in firearm ownership by sexual orientation.
Implications and Future Research Strengths and Limitations This study has a number of important limitations. First, with a single year of data, the inferences drawn are limited by a small, younger sample of the North Carolina LGB population. This small sample prevented us from controlling for other variables that may confound the relationship between sexual orientation and our outcomes, such as time spent in North Carolina. The sample size also prohibited the disaggregation of gays and lesbians from bisexuals, so our analysis cannot examine an important source of heterogeneity among sexual minorities.45,46 Second, although the sexual orientation identity question has been demonstrated as feasible to include in population health surveys in other states,12,47 as a stateadded question that is not included in the core demographic section it is among the last questions asked in the North Carolina BRFSS and thus not answered by anyone who terminated survey participation early. However, post hoc bivariate analyses revealed that those who did actively refuse to answer (n = 310) were more likely to have less education, be of Hispanic ethnicity, be older, or be women (data not shown), which is generally consistent with other state BRFSS surveys.37 Third, the North Carolina BRFSS only assessed the identity dimension of sexual orientation, and evidence from other surveillance studies illustrates that the constellation of health disparities changes depending
In 2012 North Carolina adopted a constitutional ban on same-sex marriage.48 These 2011 data are the only state-level probability sample we have about the health of sexual minorities in North Carolina before the amendment’s enactment, although they have limitations. Additional waves of the BRFSS, as well as comparisons to states with policies that are more LGB-affirming, may help to elucidate the impact this ban has on LGB populations in North Carolina, although previous research leads us to expect it will prove harmful to the health and well-being of sexual minorities.17,19 Many theories of health disparities and health behavior suggest the importance of state and local policies in the creation of healthful environments.49---51 These likely include health-promoting policies that do not currently exist in North Carolina, such as workplace nondiscrimination. Growing evidence of health disparities for sexual minorities has implications for state policies that can exacerbate such disparities. Furthermore, there may be a relationship between more immediate mental health status and distal chronic disease outcomes as mediated through maladaptive coping behaviors that warrants additional study.52,53 However, some North Carolina policies may serve to promote the health of sexual minorities. The state’s School Violence Prevention Act, which aims to protect students from bullying, including that based on real or perceived sexual
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orientation or gender identity, was passed in 2009.54,55 A study by the Gay, Lesbian, and Straight Education Network found that sexual minority students in schools operating under these enumerated policies have better outcomes, such as experiencing lower levels of victimization, than do students in schools without them.56 Although the benefit of recently enacted school policy may not be observable for the adult cohorts in the BRFSS, we call upon North Carolina to continue its leadership in the South by including sexual orientation in its Youth Risk Behavior Survey so that we can understand the health of the state’s young sexual minorities and develop appropriate interventions and policies to help them thrive throughout the life course. There are also technical implications for state health surveillance systems. Because the refusal rate of the sexual orientation question was low, as expected,12 we strongly encourage future iterations of the BRFSS to place sexual orientation among the other demographic variables rather than at the end. Data were missing for approximately 10% of respondents—a substantial proportion considering the already small number of sexual minorities in the sample. Finally, we recommend that other probability-based samples follow the example of the BRFSS and include cell phones in their sampling frame, as sexual minorities were more likely than were heterosexuals to be reached through this method.
Conclusions A community-organized statewide purposive sample in the early 1980s provided some of the first evidence of key health disparities for gays and lesbians across North Carolina. This 1985 North Carolina Lesbian and Gay Health Project study found substantial issues surrounding the sensitivity of health care service providers as well as elevated rates of chronic disease, sexually transmitted infections, mental health morbidity, and substance abuse.7 Twenty-eight years after North Carolina’s first survey of gay and lesbian health, we find similar patterns of health disparities in the BRFSS, a representative state health surveillance survey. We conclude, as did the North Carolina Lesbian and Gay Health Project, that “these issues warrant careful attention and creative responses.”7(p45) Such attention has
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been largely, though not entirely,54,57---60 absent in North Carolina and the South. Although these data from North Carolina provide the first, to our knowledge, statewide profile of LGB health disparities in the South using BRFSS data, it is clear that additional prioritization is needed across this region of the country by funders, health care providers, and policymakers to eliminate disparities by sexual orientation. j
About the Authors At the time of this study, Derrick D. Matthews and Joseph G. L. Lee were with the Department of Health Behavior, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. Correspondence should be sent to Derrick D. Matthews, Department of Behavioral and Community Health Sciences, Graduate School of Public Health, University of Pittsburgh, A223 Crabtree Hall, 130 DeSoto Street, Pittsburgh, PA 15261 (e-mail: [email protected]). Reprints can be ordered at http://www.ajph.org by clicking the “Reprints” link. This article was accepted October 21, 2013.
Contributors D. D. Matthews conducted the data analysis. Both authors conceptualized the study design and wrote the article.
Acknowledgments This study was partially supported by the National Institute of Mental Health (award T32MH094174). We thank the residents of North Carolina for their time completing the Behavioral Risk Factor Surveillance System (BRFSS) questionnaire. We also thank Sally Herndon, North Carolina Tobacco Prevention and Control branch head, and other dedicated public health professionals working on communicable disease prevention for their efforts and leadership ensuring sexual orientation was assessed in the North Carolina BRFSS. Thanks to Harry Herrick at the North Carolina State Center for Health Statistics for technical assistance with the data and to David Jolly for comments on earlier versions of the article.
Human Participant Protection This study did not require approval from an institutional review board because data were publically available and collected anonymously from a public health surveillance system in which respondents provided voluntary consent. We obtained a data use agreement with the North Carolina State Center for Health Statistics to use North Carolina Behavioral Risk Factor Surveillance System data.
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