Sexual Identity, Adverse Life Experiences, and Cardiovascular Health in Women

Abstract

Background:

Adverse life experiences (ALE; e.g., discrimination and sexual abuse) may contribute to cardiovascular disease (CVD) risk in sexual minority women (SMW), but few studies have tested whether ALE explain the association of sexual identity with cardiovascular health (CVH) markers in women.

Objective:

To examine sexual identity differences in CVH among women and the role of ALE.

Methods:

In the Epidemiologic Study of Risk in Women (ESTHER), we used multinomial logistic regression to assess sexual identity differences [SMW vs. heterosexual women (reference group)] in CVH markers (ideal vs. poor; intermediate vs. poor) using the American Heart Association’s Life’s Simple 7 and the total score. Next, we tested whether the association of sexual identity with the total CVH score was attenuated by traditional CVD risk factors or ALE.

Results:

The sample consisted of 867 women (395 heterosexual, 472 SMW). SMW were more likely to have experienced discrimination (p<0.001) and lifetime sexual abuse (p<0.001) than heterosexual women. SMW were also less likely to meet ideal CVH criteria for current tobacco use (AOR 0.43, 95% CI = 0.24–0.73) or intermediate CVH criteria for body mass index (AOR 0.60, 95% CI = 0.40–0.92). SMW had a lower cumulative CVH score (B(SE)= −0.35(0.14), p<0.01) than heterosexual women. This difference was not explained by traditional CVD risk factors or ALE.

Conclusions:

Smoking, body mass index, and fasting glucose accounted for much of the CVH disparity due to sexual identity, but those differences were not explained by ALE. Health behavior interventions tailored to SMW should be considered.

Introduction

Cardiovascular disease (CVD) is the leading cause of death and disability among women globally.¹ Modifiable risk factors (e.g., tobacco use, physical inactivity, obesity, hypertension, hyperlipidemia, diabetes) contribute to risk for CVD, including myocardial infarction and stroke.² Therefore, efforts to mitigate the global burden of CVD have emphasized modification of behavioral and biological risk factors. In 2010, the American Heart Association (AHA) established Life’s Simple 7, which set national goals for the promotion of ideal cardiovascular health (CVH) across the lifespan.³ Life’s Simple 7 focuses on achieving ideal criteria across three health behaviors (non-smoking, meeting physical activity recommendations, and diet intake consistent with evidence-based guidelines) and four biological factors (body mass index [BMI] <25 kg/m², untreated total cholesterol <200 mg/dL, untreated blood pressure <120/<80 mm Hg, and fasting blood glucose <100 mg/dL). A growing body of research indicates that meeting Life’s Simple 7 criteria is associated with lower incident CVD^4,5 and mortality.⁶ Despite the recognized benefits of maintaining optimal CVH, less than two percent of Americans meet criteria for ideal CVH for all seven metrics.⁶

Although significant racial/ethnic disparities in CVH are well-documented,^7,8 fewer studies have examined differences due to sexual identity.⁹ In 2011, the National Academy of Medicine released a landmark report on the health of lesbian, gay, bisexual, and transgender (LGBT) populations that identified priority research areas for sexual minority health, including CVD.¹⁰ Several studies indicate that sexual minority women (SMW; e.g., lesbian, bisexual women) in particular display higher rates of risk factors for poor CVH including tobacco use,¹¹ obesity,^12,13 and hyperglycemia.^12,14

Adverse life experiences (e.g. discrimination, abuse) are posited to contribute to CVD risk in SMW.^15,16 However, with a few exceptions,^17–19 research in this area is lacking. In the general population there is mounting evidence linking discrimination to higher rates of hypertension, coronary artery calcification,^20,21 and incident CVD.²² Similarly, trauma exposure (e.g., sexual and physical abuse) is independently associated with a higher prevalence of obesity, diabetes, and hypertension.^23–25 Relative to heterosexual women, SMW report higher rates of discrimination²⁶ and interpersonal trauma^27–29 across the lifecourse. Trauma among SMW is associated with modifiable risk factors for CVD including tobacco use, heavy drinking, and self-reported obesity.^15,30–32 Although some studies have found higher rates of tobacco use^11,33 and alcohol use^34,35 in SMW who have experienced some form of discrimination, there is limited research examining the impact of discrimination on CVD risk in this population.

Cardiovascular nurses are uniquely suited to promote the CVH of SMW. They possess expertise in providing care that incorporates biobehavioral approaches for prevention and management of CVD. A recent survey by the AHA’s Council on Cardiovascular and Stroke Nursing identified addressing health disparities and self-management for the prevention and treatment of CVD as priority research areas for cardiovascular nursing science.³⁶ Although sexual orientation disparities were not highlighted in that survey, the need to address social determinants of CVH and develop precision medicine guided self-management approaches for CVH were highlighted.³⁶ Informed by these research priorities for cardiovascular nursing science and given that few studies have examined whether adverse life experiences explain the excess CVD risk observed in SMW,⁹ the purpose of the present study was to examine sexual identity differences in CVH among women (ages 35–64), and estimate the contribution of adverse life experiences to any observed differences.

Methods

Sample

We used data from the Epidemiologic STudy of HEalth Risk in Women (ESTHER) study, a cross-sectional study that examined CVD risk factors among women living in Pittsburgh, Pennsylvania and surrounding areas. A convenience sample of cisgender (non-transgender) women was recruited from 2003 to 2006. Women were eligible to participate in the ESTHER study if they were aged 35 years or older and had no history of CVD (i.e., angina, heart attack, stroke).

Trained research staff conducted recruitment calls and participants were asked to complete two in-person visits at the University of Pittsburgh. All data for the present study were collected at the first visit. During the first visit a physical examination was performed which included measurement of weight, height, and blood pressure. A blood draw was performed for biomarkers (e.g., fasting plasma glucose, total cholesterol). Participants also completed the written study questionnaire, which assessed demographic and psychosocial variables as well as health-related factors (e.g., physical activity, two-week medication history). A $50 incentive was provided in appreciation of participants’ time.

A total of 1084 women were initially recruited. Due to difficulty recruiting Black women in a city that is less racially diverse than others, the study team selected a random sample of Black heterosexual women (n=38) proportional to the number of Black SMW (n=31) recruited. Because of sample size constraints limiting power to detect differences due to biracial/multiracial status, they also removed women who did not identify as White or Black (n=29). Similarly, because of a highly skewed distribution of older heterosexual women compared to older SMW, the original study team removed all women over the age of 65 from the dataset (n=76). The final sample consisted of 867 women. The University of Pittsburgh Institutional Review Board approved the ESTHER study.

Measures

Sexual identity.

Participants were classified as SMW if they 1) identified as anything other than heterosexual, and 2) reported either being only or primarily emotionally, physically, and romantically attracted to women in the past five years or having only or primarily female sexual partners in the past five years. Heterosexual women were those who identified as “straight/heterosexual” and reported only male sexual partners since the age of 18. Therefore, the present study examined two sexual identity groups: SMW (n=472) and heterosexual women (n=395).

Demographic characteristics.

Age (35–64 years old), race, education, household income, employment, relationship status, geographic area, menopause, self-rated health, and current health insurance coverage were assessed.

Health behaviors.

We assessed alcohol use in the past month (none; 1–3 times per month; 1–2 times a week; 3–4 times a week; 5–6 times a week; every day/more than once a day) and the number of times that participants ate fast food per week (range= 0–11 times), as alcohol use^37–39 and fast food intake⁴⁰ have been associated with increased risk for CVD in previous work.

Psychosocial factors.

Depressive symptoms were assessed using the Center for Epidemiologic Studies of Depression Scale (CES-D-10; Cronbach’s alpha in present sample = 0.81; range 0–30). Perceived stress was assessed with the 4-item version of the Perceived Stress Scale (PSS; Cronbach’s alpha in present sample = 0.82; range 0–13). Higher scores for the CES-D-10 and PSS indicate worse depressive symptoms and perceived stress, respectively. In addition, we assessed perceived social support using the Interpersonal Support Evaluation List (ISEL-12; Cronbach’s alpha in present sample = 0.81). The ISEL-12 contains 12 items that assess perceived availability of social support on a 4-point Likert scale ranging from “definitely false” to “definitely true.” ISEL-12 items were summed to derive a total score (range 0–36).

Adverse life experiences.

Discrimination was measured with 20 items adapted from a widely used validated measure.⁴¹ Discrimination in the past year based on race/ethnicity (6 items), gender (7 items), and sexual orientation (7 items) from various sources (e.g., family, police, medical staff, work colleagues) were assessed. Participants were assigned a score of “1” for each experience of discrimination they reported (range 0–20). The Cronbach’s alpha for the discrimination measure in the present sample was 0.83.

Sexual abuse was assessed using three items: 1) “Do you feel that you were sexually abused by a family member when you were growing up (before age 18)?” (intrafamilial childhood sexual abuse); 2) “Do you feel that you were sexually abused by someone other than a family member when you were growing up (before age 18)?” (extrafamilial childhood sexual abuse); and 3) “Since the age of 18, was there a time when someone forced you to have sexual activity that you really did not want?” (adulthood sexual abuse). Consistent with previous research in SMW we created a count measure of lifetime sexual abuse (0–3).^15,17,42 Participants were assigned a score of “1” for each type of sexual abuse they reported in their lifetime.

Cardiovascular health (CVH) markers.

We used the AHA’s Life’s Simple 7 to assess CVH (Table 1). Although the Life’s Simple 7 incorporates a dietary component, diet data were not available in ESTHER. Therefore, we used the remaining CVH components (tobacco use, physical activity, BMI, blood pressure, fasting glucose, and total cholesterol) to calculate a cumulative CVH score. A cumulative CVH score, ranging from 0–12, was calculated with each metric assigned a score of 0 (poor), 1 (intermediate), or 2 (ideal) following previous research.⁴³

Table 1.

Measures of cardiovascular health

Cardiovascular health metric	Poor (Score = 0)	Intermediate (Score = 1)	Ideal (Score = 2)
Tobacco use	Current tobacco use	Former smoker (quit less than 12 months ago)	Never smoked or quit smoking more than 12 months ago
Physical activity	No physical activity (0 minutes) per week	1–149 minutes of moderate activity or 1–74 minutes of vigorous activity or 1–149 minutes of combined moderate and vigorous activity	≥ 150 minutes of moderate activity or ≥ 75 minutes of vigorous activity or ≥ 150 minutes of combined moderate and vigorous activity
Body mass index	≥ 30 kg/m2	25–29.99 kg/m2	< 25 kg/m2
Blood pressure	Systolic blood pressure ≥ 140 or diastolic blood pressure ≥ 90 mmHg	Systolic blood pressure 120–139 or diastolic blood pressure 80–89 mmHg or treated to goal	Systolic blood pressure < 120 or diastolic blood pressure < 80 mmHg
Fasting plasma glucose	≥ 126 mg/dL	100–125 mg/dL or treated to goal	< 100 mg/dL
Total cholesterol	≥ 240 mg/dL	200–239 mg/dL or treated to goal	< 200 mg/dL

Note. Adapted from Lloyd-Jones et al.⁴

Statistical Analyses

All analyses were performed in Stata, version 15. We used Student’s t-test and chi-square tests to examine sexual identity (heterosexual vs. SMW) differences for continuous and categorical variables, respectively. To reduce bias from missing data, multiple imputation with chained equations was used to impute missing values for covariates.⁴⁴ We then used multinomial logistic regression models to examine sexual identity differences in individual CVH components (intermediate vs. poor; ideal vs. poor). Model 1 was unadjusted; Model 2 added adjustment for demographic characteristics, and Model 3 added psychosocial factors and adverse life experiences. Lastly, we used multiple linear regression models to assess sexual identity differences in cumulative CVH. CVH was normally distributed. Model 1 was unadjusted; Model 2 added adjustment for demographic characteristics, and Model 3 added health behaviors, psychosocial factors, and adverse life experiences. Heterosexual women were the reference group for all analyses.

Results

The final sample consisted of 867 women (46% heterosexual; 54% SMW). Overall, participants had a mean age of 47.6 years, were 92% White, 33% had an income greater than $75,000, 66% had a Bachelors degree or greater, 80% were employed, 70% were in a committed relationship, and 92% had healthcare coverage.

Sample characteristics are presented in Table 2. SMW were more likely than heterosexual women to have completed graduate or professional education (p = 0.04). Compared to heterosexual women, SMW reported more forms of discrimination (p <0.001) and lifetime sexual abuse (p <0.001). SMW were less likely than heterosexual women to meet ideal criteria for tobacco use (p <0.001), BMI (p <0.01) and fasting glucose (p = 0.04) and had a lower cumulative CVH score (p <0.01) relative to heterosexual women.

Table 2.

Sample characteristics.

	Total (N=867)	Heterosexual (n=395)	SMW (n=472)	p-value
Demographic characteristics	Mean (SD)/n(%)
Age (mean)	47.6 (0.2)	47.8 (0.4)	47.4 (0.3)	0.41
Race  White  Black	797 (91.9) 70 (8.1)	363 (91.9) 32 (8.1)	434 (92.0) 38 (8.0)	0.99
Education  Less than high school  High school  Some college/2 Year  Bachelors degree  Graduate/professional	4 (0.5) 89 (10.2) 205 (23.6) 214 (24.7) 355 (41.0)	2 (0.5) 54 (13.7) 92 (23.3) 98 (24.8) 149 (37.7)	2 (0.4) 35 (7.4) 113 (24.0) 116 (24.6) 206 (43.6)	0.04*
Household income  < $15,000  $15,000-$24,999  $25,000–39,999  $40,000–59,000  $60,000–74,999  ≥ $75,000  Missing	66 (7.6) 58 (6.7) 142 (16.4) 190 (22.0) 107 (12.3) 289 (33.3) 15 (1.7)	33 (8.3) 27 (6.8) 65 (16.5) 85 (21.5) 39 (9.9) 135 (34.2) 11 (2.8)	33 (7.0) 31 (6.5) 77 (16.3) 105 (22.3) 68 (14.4) 154 (32.6) 4 (0.9)	0.17
Employment  Employed full-time or part-time  Unemployed, looking  Unemployed, not looking	622 (79.6) 39 (5.0) 120 (15.4)	282 (68.6 16 (26.5) 49 (4.9)	340 (78.3) 23 (5.3) 71 (16.4)	0.60
Relationship status  Committed relationship  Not in committed relationship  Missing	610 (70.4) 256 (29.5) 1 (0.1)	238 (66.6) 109 (33.1) 1 (0.3)	347 (73.5) 125 (26.5) 0 (0.0)	0.06
Geographic area  Open country/farm  Small town (< 50,000)  Medium city (50,000–250,000)  Suburb near large city  Large city (>250,000)	46 (5.3) 106 (12.3) 48 (5.5) 326 (37.6) 341 (39.3)	21 (5.3) 49 (12.4) 23 (5.8) 165 (41.8) 137 (34.7)	25 (5.3) 57 (12.1) 25 (5.3) 161 (34.1) 204 (43.2)	0.11
Menopause	541 (62.4)	248 (62.8)	293 (62.1)	0.83
Self-rated health  Excellent  Very good  Good  Fair  Poor/very poor	115 (13.3) 366 (42.2) 299 (34.5) 68 (7.8) 19 (2.2)	63 (15.9) 159 (40.3) 148 (37.5) 22 (5.5) 3 (0.8)	52 (11.0) 207 (43.9) 151 (32.0) 46 (9.8) 16 (3.3)	<0.001***
Healthcare coverage	797 (91.9)	365 (92.4)	432 (91.5)	0.88
Health behaviors
Alcohol use in past month  None  1–3 times per month  1–2 times per week  3–4 times per week  5–6 times per week  Every day	260 (30.0) 345 (39.8) 158 (18.2) 70 (8.1) 25 (2.9) 9 (1.0)	116 (29.4) 174 (44.0) 68 (17.2) 26 (6.6) 7 (1.8) 4 (1.0)	144 (30.5) 171 (36.2) 90 (19.1) 44 (9.3) 18 (3.8) 5 (1.1)	0.11
Fast food intake per week (mean)	1.5 (0.1)	1.5 (0.1)	1.5 (0.1)	0.96
Psychosocial factors
Depressive symptoms (CES-D-10 score; mean)	6.3 (0.2)	5.9 (0.2)	6.5 (0.2)	0.06
Perceived stress (PSS score; mean)	7.8 (0.1)	7.9 (0.1)	7.8 (0.1)	0.47
Social support (ISEL-12; mean)	35.4 (0.2)	35.2 (0.3)	35.6 (0.3)	0.30
Adverse life experiences
Experiences of discrimination in past year (mean)	3.1 (0.1)	1.8 (0.1)	4.2 (0.2)	<0.001***
Number of forms of lifetime sexual abuse  0  1  2  3  Missing	401 (46.2) 214 (24.7) 134 (15.5) 59 (6.8) 59 (6.8)	222 (56.2) 95 (24.0) 39 (9.9) 15 (3.8) 24 (6.1)	179 (37.9) 119 (25.2) 95 (20.2) 44 (9.3) 35 (7.4)	<0.001***
Cardiovascular health
Tobacco use  Poor  Intermediate  Ideal	113 (13.0) 30 (3.5) 724 (83.5)	36 (9.1) 9 (2.3) 350 (88.6)	77 (16.3) 21 (4.5) 374 (79.2)	<0.001***
Physical activity  Poor  Intermediate  Ideal	52 (6.0) 173 (20.0) 643 (74.0)	23 (5.8) 80 (20.3) 292 (73.9)	29 (6.1) 93 (19.7) 350 (74.2)	0.97
Body mass index  Poor  Intermediate  Ideal	316 (36.4) 245 (28.3) 306 (35.3)	120 (30.4) 125 (31.6) 150 (38.0)	196 (41.5) 120 (25.4) 156 (33.1)	<0.01**
Blood pressure  Poor  Intermediate  Ideal	21 (2.4) 325 (37.5) 521 (60.1)	8 (2.0) 136 (34.5) 251 (63.5)	13 (2.8) 189 (40.0) 270 (57.2)	0.16
Fasting plasma glucose  Poor  Intermediate  Ideal	26 (3.0) 194 (22.4) 647 (74.6)	7 (1.8) 79 (20.0) 309 (78.2)	19 (4.0) 115 (24.4) 338 (71.6)	0.04*
Total cholesterol  Poor  Intermediate  Ideal	167 (19.8) 340 (38.7) 260 (41.5)	78 (19.8) 153 (38.7) 164 (41.5)	89 (18.9) 187 (39.6) 196 (41.5)	0.94
Cumulative CVH score (mean)	8.9 (0.1)	9.1 (0.1)	8.6 (0.1)	<0.001***

Note. SMW = sexual minority women.

^*p <0.05

^**p <0.01

^***p <0.001

Findings for multinomial logistic regression analyses examining poor vs. intermediate and poor vs. ideal criteria for CVH metrics are shown in Table 3. Although SMW were less likely to meet ideal criteria for fasting glucose than heterosexual women in unadjusted models (OR 0.40, 95% CI= 0.17–0.97), this difference was attenuated after adjustment for psychosocial factors and adverse life experiences (AOR 0.44, 95% CI= 0.17–1.14) In fully adjusted models, SMW were significantly less likely than heterosexual women to meet ideal criteria for tobacco use (AOR 0.44, 95% CI=0.27–0.71) and were less likely to meet intermediate (AOR 0.66, 95% CI= 0.45–0.98) criteria for BMI. No differences in other CVH components were noted between SMW and heterosexual women.

Table 3.

Sexual identity differences in individual cardiovascular health components in the ESTHER study (N=867).

	Intermediate Criteria (Reference = Poor)			Ideal Criteria (Reference = Poor)
	Model 1 OR (95% CI)	Model 2 AOR (95% CI)	Model 3 AOR (95% CI)	Model 1 OR (95% CI)	Model 2 AOR (95% CI)	Model 3 AOR (95% CI)
Current tobacco use  Heterosexual  SMW	Ref 1.09 (0.45–2.62)	Ref 1.03 (0.42–2.55)	Ref 1.06 (0.41–2.76)	Ref 0.50 (0.33–0.76)***	Ref 0.45 (0.29–0.71)**	Ref 0.44 (0.27–0.71)**
Physical activity  Heterosexual  SMW	Ref 0.92 (0.49–1.72)	Ref 0.85 (0.45–1.63)	Ref 0.80 (0.40–1.59)	Ref 0.95 (0.53–1.68)	Ref 0.95 (0.52–1.72)	Ref 0.82 (0.43–1.55)
Body mass index  Heterosexual  SMW	Ref 0.59 (0.42–0.82)**	Ref 0.57 (0.40–0.81)*	Ref 0.66 (0.45–0.98)*	Ref 0.64 (0.46–0.88)**	Ref 0.63 (0.44–0.89)**	Ref 0.74 (0.51–1.09)
Blood pressure  Heterosexual  SMW	Ref 0.85 (0.34–2.12)	Ref 0.82 (0.33–2.13)	Ref 0.98 (0.35–2.74)	Ref 0.66 (0.27–1.62)	Ref 0.61 (0.24–1.58)	Ref 0.77 (0.28–2.18)
Fasting glucose  Heterosexual  SMW	Ref 0.53 (0.22–1.34)	Ref 0.50 (0.19–1.27)	Ref 0.53 (0.20–1.43)	Ref 0.40 (0.17–0.97)*	Ref 0.38 (0.15–0.94)*	Ref 0.44 (0.17–1.14)
Total cholesterol  Heterosexual  SMW	Ref 1.07 (0.74–1.55)	Ref 1.10 (0.75–1.61)	Ref 1.08 (0.71–1.63)	Ref 1.05 (0.72–1.51)	Ref 1.04 (0.70–1.56)	Ref 1.14 (0.74–1.78)

Note. Model 1 unadjusted; Model 2 added demographic characteristics; Model 3 added psychosocial factors and adverse life experiences.

^*p <0.05

^**p <0.01

^***p <0.001

Next, we used linear regression models to examine sexual identity differences in cumulative CVH scores (Table 4). Compared to heterosexual women, SMW were more likely to have a lower CVH score (B(SE)= −0.32 (0.13), p<0.05).

Table 4.

Sexual identity differences in ideal cardiovascular health scores in ESTHER study (N=867).

	Model 1	Model 2	Model 3
Cumulative ideal CVH score	B (SE)	B (SE)	B (SE)
Sexual identity  Heterosexual  SMW	Ref −0.48 (0.14)***	Ref −0.44 (0.12)***	Ref −0.32 (0.13)*
Age	-	−0.05 (0.01)***	−0.06 (0.01)***
White race	-	0.21 (0.08)**	0.12 (0.08)
Education	-	0.21 (0.06)***	0.19 (0.07)**
Household income	-	0.07 (0.05)	0.06 (0.05)
Employed	-	−0.01 (0.09)	−0.02 (0.09)
Relationship status	-	0.09 (0.15)	0.08 (0.15)
Geographic area	-	0.13 (0.05)**	0.13 (0.05)*
Self-rated health		−0.65 (0.07)***	−0.59 (0.08)***
Menopause	-	0.07 (0.18)	0.01 (0.18)
Healthcare coverage	-	0.41 (0.23)	0.40 (0.24)
Alcohol use in past month	-	-	−0.28 (0.03)
Fast food intake per week	-	-	−0.12 (0.03)***
Depressive symptoms	-	-	0.00 (0.01)
Perceived stress	-	-	−0.03 (0.02)
Social support	-	-	−0.01 (0.01)
Experiences of discrimination	-	-	−0.02 (0.02)
Lifetime sexual abuse	-	-	−0.10 (0.07)

Note. Model 1 unadjusted. Model 2 added demographic characteristics; Model 3 added health behaviors, psychosocial factors, and adverse life experiences.

^*p <0.05

^**p <0.01

^***p <0.001

Discussion

This study is one of the first to examine cumulative CVH in SMW. A notable strength of this work is that in addition to accounting for known CVD risk factors (e.g., health behaviors, psychosocial factors), we examined the impact of adverse life experiences (i.e., discrimination and sexual abuse) on the association between sexual identity and CVH among women. Consistent with previous evidence, SMW in the present study were more likely to report experiences of discrimination^26,33 and lifetime sexual abuse than heterosexual women.^30,45,46 Furthermore, we found that established risk factors for CVD and adverse life experiences only partially explained sexual identity differences in CVH among women. The lower cumulative CVH score observed in SMW was primarily attributed to higher rates of tobacco use and elevated BMI compared to heterosexual women. This is consistent with previous studies that have found higher rates of tobacco use^11,12 and elevated BMI^12,13,47 in SMW. Although SMW had lower rates of meeting ideal criteria for fasting glucose, which is consistent with previous evidence,^12,14 this difference was attenuated after adjustment for psychosocial factors and adverse life experiences.

Although a notable strength of this study was the inclusion of discrimination and sexual abuse as potential contributors to poor CVH, it is likely that additional stressors that are unique to SMW, called minority stressors (e.g., harassment, expectations of rejection, internalized homophobia),⁴⁸ may contribute to poor CVH in this population. Overall, few studies have investigated the association of minority stressors and CVD in sexual minorities.⁹ Findings from a small number of studies suggest that exposure to sexual minority-specific stressors are associated with higher rates of tobacco use and hazardous drinking (e.g., heavy drinking and binge drinking)^49–51 in SMW. On the contrary, a recent study of young lesbian women found that internalized homophobia was not associated with elevated BMI.⁵² Therefore, additional research that examines the link between sexual minority-specific and general life stressors with poor CVH in this population is needed. Further, in the United States there are currently 28 states that provide no legal protection for SMW against discrimination in healthcare, employment, education, housing, and other settings.⁵³ These forms of structural stigma are conceptualized as fundamental causes for health disparities among sexual minorities,^10,12 but their relationships with health outcomes have not been tested. More work is needed to examine the potential link between structural stigma and CVH in SMW. Moreover, although we included a measure of perceived social support, future work should investigate how resilience and coping self-efficacy may mitigate the effect of stress on CVH in SMW.

These findings have important implications for cardiovascular care of SMW. Although interventions that address fundamental causes of health disparities (e.g., lack of laws that protect against discrimination) are needed, at this time targeting behavioral factors is the most appropriate approach to improve CVH in SMW. Cardiovascular nurses possess skills in health promotion and behavior change that are essential to promote the CVH of SMW.⁵⁴ Our findings indicate that prevention efforts for SMW should target behavior change, including smoking cessation and weight management, to promote their CVH. There is a paucity of culturally tailored interventions aimed at reducing modifiable risk factors for CVD in SMW.⁵⁵ Given this and mounting evidence of SMW’s elevated risk for CVD, nurses and other healthcare professionals should consider developing tailored interventions to promote CVH in this population. A recent multi-site intervention conducted in 10 cities across the United States found that tailored health promotion interventions (i.e., mindfulness, pedometer use, and gym membership) were effective at increasing physical activity and reducing waist-to-height ratio in SMW over the age of 40.⁵⁶ That work can serve as a model for future cardiovascular prevention interventions in this population. Research that examines how behavioral interventions can be used to promote the CVH of SMW is needed.

Limitations

This study has several limitations. First, because the ESTHER study used a cross-sectional design, we cannot infer causality from these findings. Second, participants were recruited via convenience sampling from one large city and its surrounding areas in the United States, which limits generalizability of findings to SMW in other cities and in rural areas. In addition, ESTHER study participants were predominately White (92%) and highly educated. We were unable to examine whether CVH differed by race/ethnicity or education. Future research should explore whether the lower CVH scores observed in SMW in this sample are consistent across geographic region, race/ethnicity, and educational status. Additionally, our measure of CVH did not include the dietary component of the Life’s Simple 7, which limits confidence in our findings. However, we adjusted all models for fast food intake, which has been associated with higher rates of diabetes, hyperlipidemia, and CVD.^40,57 Posttraumatic stress disorder (PTSD), which is associated with adverse life experiences,^58,59 has been linked with incident CVD and hypertension in women^60–63 and SMW report higher rates of PTSD than heterosexual women.^64,65 Since PTSD was not measured in the ESTHER study, we were unable to examine the association of PTSD with CVH in the present study. This is an important area to examine in future work. Further, given that the present study only included cisgender women, the experience of transgender women who might also identify as a SM are not represented. Future work should be done to explore CVH in transgender women as the use of exogenous hormones may place them at increase risk for CVD.⁶⁶ Finally, data were collected from 2003–2006. Cultural, legal, and technological changes since the study was conducted may have changed how SMW’s CVH is influenced by their sexual minority status, and/or how adverse life experiences influence the association of sexual minority status with CVH.

Conclusion

This study contributes to growing evidence of poor CVH in SMW and represents a first step in understanding the role that adverse life experiences play in SMW’s CVH. These findings have implications for health promotion efforts aimed at improving the CVH of SMW. Additional research is needed to investigate the association of stressors and CVH in this population. Cardiovascular nurses have the opportunity to lead the field toward implementing evidence-based approaches to the prevention of CVD in this underserved and understudied population of women.