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. Author manuscript; available in PMC: 2022 Jul 1.
Published in final edited form as: Womens Health Issues. 2021 Mar 22;31(4):341–352. doi: 10.1016/j.whi.2021.02.004

Revictimization is associated with higher cardiometabolic risk in sexual minority women

Billy A Caceres 1, Britney M Wardecker 2, Jocelyn Anderson 3, Tonda L Hughes 4, Henrik H Bendixen 5
PMCID: PMC8260453  NIHMSID: NIHMS1673511  PMID: 33766475

Abstract

Objectives:

Although there is evidence that interpersonal trauma is associated with cardiometabolic risk in women, previous studies have not assessed the potential role of revictimization (victimization in both childhood and adulthood) among sexual minority women.

Materials and Methods:

We used data from the Chicago Health and Life Experiences of Women study to examine the associations of revictimization (including physical, sexual, and any revictimization) with self-reported psychosocial factors, health behaviors, and cardiometabolic risk factors (e.g., obesity, hypertension, and diabetes). We tested multiple logistic regression models, adjusted for covariates, to estimate odds ratios of the associations between revictimization and cardiometabolic risk.

Results:

The sample included 615 sexual minority women: mean age of 40.0; 38.7% white. Eighty-three (13.5%) and 101 (16.4%) participants reported experiencing sexual revictimization and physical revictimization, respectively. Each form of revictimization was associated with higher odds of reporting lifetime depression and recent binge eating, but lower odds of having high social support. Physical revictimization was associated with higher odds of obesity (AOR 2.38, 95% CI = 1.38–4.10) and hypertension (AOR 3.31, 95% CI 1.70–6.46). Similarly, participants who reported any revictimization were more likely to have obesity (AOR 2.36, 95% CI = 1.42–3.92) and hypertension (AOR 2.60, 95% CI = 1.31–5.26). No form of revictimization was associated with higher odds of diabetes.

Conclusions:

The higher odds of obesity and hypertension observed among sexual minority women who reported revictimization reinforce the need for early interventions to reduce cardiometabolic risk in this vulnerable population.

Keywords: Interpersonal violence, sexual minority women, women’s health, cardiometabolic risk, health promotion

Introduction

A growing body of research indicates that sexual minority women (SMW; lesbian, bisexual, and other non-heterosexual women) have higher cardiometabolic risk than heterosexual women (Caceres et al., 2017). For instance, compared to heterosexual women, SMW are more likely to report poor mental health (Bostwick et al., 2010; Plöderl & Tremblay, 2015), tobacco use (Blosnich et al., 2013; Caceres et al., 2018; Caceres, Makarem, et al., 2019; McCabe et al., 2018), and heavy drinking (Caceres et al., 2018; Hughes et al., 2010; Hughes, Szalacha, & McNair, 2010). Each of these factors can increase SMW’s risk for cardiovascular disease (CVD), the leading cause of death among women (Virani et al., 2020). Additionally, multiple studies have found that SMW are more likely than heterosexual women to have obesity (Caceres et al., 2018; Caceres, Markovic, et al., 2019; Eliason et al., 2015; Katz-Wise et al., 2014), elevated blood pressure (Caceres et al., 2020; Kinsky et al., 2016), and hyperglycemia (Caceres et al., 2018; Corliss et al., 2018; Kinsky et al., 2016; Liu et al., 2019).

Despite evidence that SMW have elevated CVD risk compared to heterosexual women, few studies have examined social determinants (e.g., interpersonal violence and discrimination) that potentially contribute to this disparity. This limits the development of culturally tailored interventions to reduce SMW’s risk of developing CVD (Andersen & Blosnich, 2013; Balsam et al., 2005). Higher rates of interpersonal trauma (e.g., physical and sexual abuse) may contribute to SMW’s higher cardiometabolic risk via both behavioral and physiological pathways (Caceres et al., 2016, 2020; Lick et al., 2013).

Indeed, multiple studies have identified a link between interpersonal trauma and cardiometabolic risk among women in the general population. Women who report childhood abuse are more likely to have obesity and to have diabetes and a history of CVD (Friedman, Montez, Sheehan, Guenewald, & Seeman, 2015b). Several studies examining trauma exposure at different times across the life course have found an association with hypertension (Mason et al., 2012; Suglia et al., 2014) and diabetes (Mason et al., 2013; Rich-Edwards et al., 2010) in women. Although greater severity of childhood abuse is associated with higher cardiometabolic risk in adulthood (Danese et al., 2009; Felitti et al., 1998; Friedman, Montez, Sheehan, Guenewald, & Seeman, 2015a; Riley, Wright, Jun, Hibert, & Rich-Edwards, 2010; Su et al., 2015), little is known about the impact of revictimization on cardiometabolic risk (Suglia et al., 2018). Given evidence of a dose-response relationship between interpersonal trauma and cardiometabolic risk (Friedman et al., 2015b; Stein et al., 2010), individuals who experience childhood abuse and are revictimized in adulthood may have particularly high cardiometabolic risk.

Abuse in childhood is a strong predictor of subsequent abuse (Frugaard Stroem et al., 2019; Scoglio et al., 2021; Walker et al., 2019). Sexual revictimization rates vary widely based on sample characteristics and recruitment methods (e.g., college vs. community-based samples). However, a 2019 meta-analysis of 80 studies that included 12,252 survivors of childhood sexual abuse, found that across varying samples and recruitment methods, approximately 50% of women and men who experienced childhood sexual abuse reported exposure to sexual violence in adulthood (Walker et al., 2019).

Revictimization may influence cardiometabolic risk through mediated psychosocial and behavioral pathways that, in turn, can influence physiological mechanisms. Psychosocial factors are intricately intertwined with interpersonal trauma and there is strong evidence supporting the detrimental cardiometabolic effects of posttraumatic stress and depression (Edmondson & von Känel, 2017; Lee et al., 2020; Wilson et al., 2019). Further, substance use (e.g., alcohol and tobacco use) is also a cardiometabolic risk factor—as well as a risk factor for revictimization (Pittenger et al., 2018). The relationship between revictimization and substance use is complex and likely bidirectional, with evidence suggesting that substance use is associated with other risk-taking behaviors (via increased impulsivity and impaired decision making) and greater exposure to settings that increase risk for additional victimization (Finkelhor et al., 2007; Mosack et al., 2010). Binge eating, which tends to be more prevalent in SMW relative to heterosexual women, may be another behavioral factor that influences cardiometabolic risk among SMW (Bankoff & Pantalone, 2014; Calzo et al., 2017; Laska et al., 2015). The association between binge eating and obesity has been established in longitudinal studies in general population samples (Hudson et al., 2010; Nagata et al., 2018). Further, a systematic review of 70 studies (N = 306,583) that examined the relationships among interpersonal trauma, binge eating, and obesity, found that 90% of the included studies provided evidence of links between childhood trauma with binge eating and obesity in adulthood (Palmisano et al., 2016). Exposure to interpersonal trauma, particularly in childhood, has been found to increase cardiometabolic risk through activation of stress response pathways (e.g., overstimulation of the sympathetic nervous system, chronic inflammation, and hypothalamus-pituitary-adrenal axis dysfunction) (Berens et al., 2017; Miller et al., 2011).

SMW are more likely than their heterosexual counterparts to report interpersonal trauma across the lifespan (Austin et al., 2008; Balsam et al., 2005; Friedman et al., 2011; Hughes, McCabe, et al., 2010; Katz-Wise & Hyde, 2012; López & Yeater, 2018; Mattocks et al., 2013; Szalacha et al., 2017). Although literature on revictimization among SMW is limited, rates of sexual revictimization among SMW range between 20.0% to 55.0% (Balsam, Lehavot, & Beadnell, 2011; Hequembourg, Livingston, & Parks, 2013; Hughes et al., 2010; Morris & Balsam, 2003), which is consistent with estimates in the general population (Walker et al., 2019). However, another study found that among women who experienced childhood sexual abuse, rates of sexual revictimization in adulthood were three to seven times higher in SMW than in heterosexual women (Canan et al., 2019). Although less is known about physical revictimization, one study estimated the rate to be approximately 25% in SMW (Stoddard et al., 2009). In a large study of 2,431 SMW, those who reported physical or sexual abuse in childhood were four times as likely to experience sexual abuse and twice as likely to experience another form of abuse in adulthood (Morris & Balsam, 2003).

A limited number of studies have documented an association between interpersonal trauma and cardiometabolic risk factors (including obesity, hypertension, and diabetes) in SMW (Aaron & Hughes, 2007; B.A. Caceres et al., 2019; Hatzenbuehler et al., 2014; Smith et al., 2010). Using cross-sectional data from the Chicago Health and Life Experiences of Women (CHLEW) study, we examined the associations between different forms of revictimization (i.e., physical, sexual, and any revictimization) and cardiometabolic risk factors (i.e., obesity, hypertension, and diabetes) in a large and diverse community-based sample of SMW. We hypothesized that SMW who reported revictimization of any form would also report higher rates of obesity, hypertension, and diabetes than those who did not report revictimization.

Materials and Methods

Sample

The CHLEW (N = 723) is a 20-year longitudinal study of risk and protective factors associated with alcohol use, health, and well-being of cisgender (non-transgender) SMW. Since 2000, four waves of data collection have been completed. CHLEW Wave 1 (2000–2001) included a convenience sample of 447 English-speaking, adult self-identified lesbian women recruited from the Chicago metropolitan area. Detailed information about the original sample and recruitment methods can be found elsewhere (Hughes et al., 2006). Wave 2 (2004–2005) re-interviewed 384 (86%) women from the original cohort. CHLEW Wave 3 (2010–2012) retained 353 women (79%) from the original cohort and added a supplemental sample of 373 SMW including bisexual women, younger women (18–25 years), and African American and Latina women. Wave 1 and Wave 2 interviews were conducted in person; in Wave 3, 102 CHLEW participants had moved outside the Chicago Metropolitan area. These interviews were conducted by Skype or telephone. The current study uses data from Wave 3 because it includes the largest and most diverse sample of SMW. The institutional review board of University of Illinois at Chicago approved the study protocol.

Inclusion/Exclusion Criteria

We included all Wave 3 CHLEW participants who identified as lesbian, mostly lesbian, or bisexual and who had complete data for all forms of victimization and cardiometabolic risk factors (i.e., body mass index [BMI)], and diagnosis of hypertension and diabetes). We excluded participants who identified as mostly heterosexual (n = 8), heterosexual (n = 6), or other sexual identity (n = 12) due to small sample sizes. A total of 64 participants were excluded due to missing data for victimization variables and an additional 10 participants who had incomplete data for self-reported BMI (i.e., height and/or weight). An additional 4 participants were excluded because of incomplete data on diagnosis of hypertension and diabetes. We also excluded participants who provided no applicable responses for other relevant variables (n = 1 for relationship status; n = 2 for social support, n = 1 for binge eating).

Measures

Physical revictimization.

To assess childhood physical abuse participants were asked, “Do you feel that you were physically abused by your parents or other family members when you were growing up?” (1 = “Yes,” 0 = “No”). Adult physical abuse was assessed with two items asking participants whether (after age 18) someone had attacked them with or without a weapon with the intent to kill or seriously injure them (adult physical assault) and whether an intimate partner ever “threw something at you, pushed you, or hit you” (intimate partner violence, IPV). Participants who responded affirmatively to either of these questions were categorized as having experienced adult physical abuse (1 = Yes; 0 = No). We created a categorical variable to account for physical revictimization that was coded as 1 = no physical abuse; 2 = childhood physical abuse only; 3 = adulthood physical abuse only; 4 = both childhood and adulthood physical abuse.

Sexual revictimization.

To assess childhood sexual abuse participants were asked “Do you feel that you were sexually abused when you were growing up?” (1 = “Yes,” 0 = “No”). Adult sexual abuse included any experience of sexual assault (by an intimate partner or other person) after the age of 18. For adult sexual assault, participants were asked whether “since the age of 18 was there a time when you experienced any unwanted/forced sexual activity?” (1 = Yes; 0 = No). We assessed sexual IPV by asking participants whether, since they were age 18, a partner had ever sexually assaulted them (1 = Yes; 0 = No). Participants who responded affirmatively to either of these questions were categorized as having experienced adult sexual abuse (1 = Yes; 0 = No). We created a categorical variable to account for sexual revictimization that was coded 1 = no sexual abuse; 2 = childhood sexual abuse only; 3 = adulthood sexual abuse only; 4 = both childhood and adulthood sexual abuse.

Revictimization.

We created a revictimization variable to classify participants who reported either physical or sexual abuse in both childhood and adulthood, which was coded as 1 = no abuse; 2 = childhood abuse only; 3 = adulthood abuse only; 4 = both childhood and adulthood abuse.

Demographic characteristics.

Sexual identity. Participants were asked: “Recognizing that sexual identity is only one part of your identity how do you define your sexual identity? Would you say that you are: only lesbian/gay, mostly lesbian/gay, bisexual, mostly heterosexual/straight, only heterosexual/straight?” Given that few differences were found between only lesbian and mostly lesbian participants, we combined these participants into the category of lesbian. We also assessed age (continuous), race/ethnicity (non-Latina white, non-Latina African American, Latina, or non-Latina other race), household income (<$20,000, $20,000–39,999, $40,000–74,999, and ≥ $75,000), education (less than high school, high school, some college, college graduate, and graduate school), relationship status (committed-cohabitating, committed-not cohabitating, and single) and health insurance coverage (yes/no).

Psychosocial factors.

Lifetime depression was assessed using criteria for major depressive episode from the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (American Psychiatric Association, 2000). Depressive episodes were defined as persistence of four or more depressive symptoms for at least two weeks, in addition to feeling sad, blue, or depressed or having lost interest or pleasure in things usually cared about. We dichotomized this variable as “1” for any lifetime depressive episode and “0” for none.

To assess social support, we used the Multidimensional Scale of Perceived Social Support (MSPSS), a 12-item measure that assesses social support from family, friends, and significant others. Total scores range from 0–7 (Zimet et al., 1988, 1990). Cronbach’s alpha in the present sample was 0.90. Participants were categorized as having low (1.0–2.9), moderate (3.0–5.0), or high social support (5.1–7.0) based on established cutoffs (Zimet et al., 1988, 1990). Because only 18 (2.7%) participants reported low social support, we combined participants with low and moderate social support into one category and compared these participants to those with high social support.

Health behaviors.

Participants were asked if they currently smoked cigarettes (1 = Yes; 0= No). To assess heavy episodic drinking participants were asked whether in the past year they had ever consumed six or more drinks in a day (1 = Yes; 0 = No). Binge eating in the past three months was assessed with two items. First, women were asked whether in the past three months they had consumed what would be considered by others to be a large amount of food in a short period of time (1 = Yes; 0 = No). Women who responded affirmatively were then asked whether they had a sense of loss of control with respect to eating at the time (1 = Yes; 0 = No). Women who responded “Yes” to the second item were categorized as having had an episode of binge eating in the past 3 months. Women who responded “No” were categorized as not having had an episode of binge eating during that time. Women who responded “No” to the first item were also categorized as not having had an episode of binge eating in the past three months.

Cardiometabolic risk.

BMI (kg/m2) was calculated using self-reported weight and height and women were classified as having obesity if their BMI was greater than or equal to 30.0 kg/m2 (Centers for Disease Control and Prevention, 2020). We also assessed whether a healthcare provider had ever diagnosed participants with hypertension (1 = Yes; 0 = No) or diabetes (1 = Yes; 0 = No).

Statistical Analysis

Data analyses were performed in Stata, version 16. Means and frequencies across all study variables were used to characterize the sample. We then conducted multiple imputation with chained equations with 20 imputations to impute missing values for covariates. Next, we used multiple logistic regression models to estimate the odds ratios of the association of different forms of revictimization with psychosocial factors and health behaviors. Model 1 was unadjusted and Model 2 adjusted for demographic characteristics. Last, we used multiple logistic regression models to estimate odds ratios of the association of different forms of revictimization with cardiometabolic risk factors (i.e., obesity, hypertension, and diabetes). Model 1 was unadjusted and Model 2 was adjusted for demographic characteristics, psychosocial factors, and health behaviors. A significance level of p <0.05 was pre-determined.

Results

Table 1 shows sample characteristics for the 615 participants. Participants were 40 years old, on average (SD = 14.2). The majority (73.8%) identified as lesbian. More than one-third (38.7%) identified as non-Latina white and 80.2% had greater than a high school education; 30.6% had household incomes less than or equal to $20,000 and 39.1% were in a committed-cohabiting relationship. The majority of women (70.5%) reported that they had health insurance coverage. More than one-third of women (38.1%) met criteria for obesity, whereas 18.1% and 7.6% reported a history of hypertension and diabetes, respectively. More than 10% of the sample reported sexual revictimization (13.5%) or physical revictimization (16.4%). Approximately one-third (31.1%) reported experiencing some form of abuse in both childhood and adulthood.

Table 1.

Sample characteristics (N=615)

Demographic characteristics Complete data n (%)/Mean (SD)
Age (mean) 615 40.0 (14.2)
Sexual identity 615
 Lesbian 454 (73.8)
 Bisexual 161 (26.2)
Race/ethnicity 615
 Non-Latina white 238 (38.7)
 Non-Latina African American 221 (35.9)
 Latina 134 (22.0)
 Non-Latina other race 21 (3.4)
Education 615
 Less than high school 45 (7.3)
 High school 77 (12.5)
 Some college 189 (30.7)
 College graduate 128 (20.9)
 Graduate school 176 (28.6)
Household income 589
 < $20,000 188 (30.6)
 $20,000–39,999 117 (19.0)
 $40,000–74,999 135 (22.0)
 ≥ $75,000 149 (24.2)
 Missing 26 (4.2)
Relationship status 613
 Committed, cohabitating 241 (39.1)
 Committed, not cohabitating 136 (22.2)
 Single 236 (38.3)
 Missing 2 (0.3)
Health insurance coverage 615 434 (70.5)
Psychosocial factors
Lifetime depression 610
 Yes 361 (58.7)
 No 249 (40.5)
 Missing 5 (0.8)
Perceived social support 615
 Low 16 (2.6)
 Medium 191 (31.1)
 High 408 (66.3)
Health behaviors
Current smoking 615 188 (30.5)
Heavy episodic drinking (past year) 615 238 (38.7)
Binge eating (past 3 months) 613 57 (9.3)
Cardiometabolic risk
Obesity (≥ 30 kg/m2) 615 234 (38.1)
Hypertension 615 111 (18.1)
Diabetes 615 47 (7.6)
Sexual abuse
Childhood sexual abuse 615
 Yes 196 (31.9)
 No 419 (68.1)
Adulthood sexual abuse 615
 Yes 186 (30.2)
 No 429 (69.8)
Sexual abuse revictimization 615
 No lifetime sexual abuse 316 (51.4)
 Childhood sexual abuse only 113 (18.4)
 Adulthood sexual abuse only 103 (16.7)
 Both childhood and adulthood sexual abuse 83 (13.5)
Physical abuse
Childhood physical abuse 615
 Yes 159 (25.8)
 No 456 (74.2)
Adulthood physical abuse 615
 Yes 296 (48.1)
 No 319 (51.9)
Physical abuse revictimization 615
 No lifetime physical abuse 262 (42.5)
 Childhood physical abuse only 58 (9.4)
 Adulthood physical abuse only 195 (31.7)
 Both childhood and adulthood physical abuse 101 (16.4)
Revictimization
Any revictimization 615
 No lifetime abuse 177 (28.8)
 Childhood abuse only 69 (11.2)
 Adulthood abuse only 178 (28.9)
 Both childhood and adulthood abuse 191 (31.1)
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Table 2 presents results of regression models examining the associations of victimization with psychosocial factors and health behaviors. Experiencing physical abuse, sexual abuse, or any form of abuse across the lifespan was associated with higher odds of lifetime depression. These associations were strongest among women who reported physical abuse revictimization (AOR 4.99, 95% CI = 2.79–8.94), sexual abuse revictimization (AOR 4.14, 95% CI = 2.28–7.49), or any type of revictimization (AOR 6.58, 95% CI = 3.99–10.87) compared to those with no lifetime abuse. Similarly, we found that women who reported physical abuse revictimization (AOR 0.49, 95% CI = 0.29–0.82), sexual abuse revictimization (AOR 0.49, 95% CI = 0.29–0.83), or any type of revictimization (AOR 0.63, 95% CI = 0.39–0.97) were less likely to report high social support than those with no lifetime abuse. No forms of victimization were associated with current smoking or heavy episodic drinking. Women who experienced physical abuse revictimization (AOR 3.11, 95% CI = 1.42–6.80), sexual abuse revictimization (AOR 2.79, 95% CI = 1.24–6.27), or any type of revictimization (AOR 2.78, 95% CI = 1.25–6.15) were more likely to report binge eating than those who reported no abuse in their lifetime. We also found that women who reported sexual abuse only in childhood had higher odds of binge eating (AOR 2.44, 95% CI = 1.17–5.10).

Table 2.

Results of logistic regression models examining of different forms of victimization with psychosocial factors and health behaviors in sexual minority women (N = 616).

Physical abuse Sexual abuse Any abuse
Model 1
OR (95% CI)		 Model 2
AOR (95% CI)		 Model 1
OR (95% CI)		 Model 2
AOR (95% CI)		 Model 1
OR (95% CI)		 Model 2
AOR (95% CI)
Lifetime depression
 No lifetime abuse Reference Reference Reference Reference Reference Reference
 Childhood only 1.92 (1.07–3.49)* 2.27 (1.20–4.28)* 2.76 (1.73–4.41)*** 3.13 (1.92–5.10)*** 2.51 (1.41–4.46)** 2.85 (1.55–5.23)**
 Adulthood only 1.98 (1.36–2.92)*** 2.84 (1.85–4.36)*** 2.03 (1.28–3.23)** 1.92 (1.19–3.13)** 2.17 (1.41–3.32)** 2.73 (1.72–4.34)***
 Both childhood and adulthood 3.33 (2.00–5.59)*** 4.99 (2.79–8.94)*** 3.68 (2.10–6.43)*** 4.14 (2.28–7.49)*** 4.78 (3.04–7.50)*** 6.58 (3.99–10.87)***
High social support
 No lifetime abuse Reference Reference Reference Reference Reference Reference
 Childhood only 0.47 (0.26–0.85)* 0.51 (0.28–0.95)* 0.78 (0.50–1.24) 0.85 (0.52–1.35) 0.81 (0.45–1.47) 0.89 (0.48–1.67)
 Adulthood only 0.77 (0.51–1.16) 0.95 (0.61–1.47) 0.99 (0.61–1.62) 0.99 (0.59–1.64) 1.09 (0.70–1.74) 1.32 (0.80–2.16)
 Both childhood and adulthood 0.35 (0.22–0.57)*** 0.49 (0.29–0.82)** 0.44 (0.27–0.72)** 0.49 (0.29–0.83)** 0.50 (0.33–0.78)** 0.63 (0.39–0.97)*
Current smoking
 No lifetime abuse Reference Reference Reference Reference Reference Reference
 Childhood only 1.36 (0.72–2.56) 1.13 (0.55–2.29) 1.17 (0.74–1.85) 1.06 (0.63–1.78) 1.71 (0.94–3.14) 1.25 (0.64–2.43)
 Adulthood only 1.92 (1.28–2.89)** 1.40 (0.88–2.25) 1.03 (0.64–1.68) 1.22 (0.70–2.11) 1.55 (0.97–2.48) 1.04 (0.61–1.77)
 Both childhood and adulthood 1.98 (1.21–3.24)** 1.44 (0.80–2.60) 1.16 (0.69–1.94) 1.09 (0.59–2.01) 1.62 (1.02–2.56)* 1.15 (0.68–1.96)
Heavy episodic drinking
 No lifetime abuse Reference Reference Reference Reference Reference Reference
 Childhood only 1.04 (0.58–1.87) 1.34 (0.70–2.58) 0.81 (0.52–1.27) 0.84 (0.52–1.36) 1.18 (0.67–2.08) 1.21 (0.65–2.27)
 Adulthood only 1.24 (0.85–1.81) 1.46 (0.95–2.24) 0.86 (0.54–1.36) 0.97 (0.59–1.59) 1.43 (0.93–2.18) 1.54 (0.96–2.47)
 Both childhood and adulthood 1.03 (0.64–1.65) 1.53 (0.88–2.65) 0.56 (0.33–0.95)* 0.73 (0.41–1.31) 0.89 (0.58–1.36) 1.09 (0.67–1.77)
Binge eating
 No lifetime abuse Reference Reference Reference Reference Reference Reference
 Childhood only 1.32 (0.48–3.82) 1.30 (0.44–3.79) 2.46 (1.20–5.02)* 2.44 (1.17–5.10)* 1.70 (0.60–4.86) 1.64 (0.56–4.78)
 Adulthood only 1.34 (0.68–3.76) 1.54 (0.74–3.22) 1.86 (0.86–4.06) 1.82 (0.81–4.06) 1.43 (0.62–3.31) 1.57 (0.66–3.73)
 Both childhood and adulthood 3.04 (1.50–6.16)** 3.11 (1.42–6.80)** 2.63 (1.22–5.67)* 2.79 (1.24–6.27)* 2.75 (1.29–5.86)** 2.78 (1.25–6.15)**
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Note. Model 1 = unadjusted, Model 2 = adjusted for age, sexual identity, race/ethnicity, education, household income, relationship status, and health insurance coverage.

*

p < 0.05

**

p < 0.01

***

p < 0.001

Table 3 presents associations between different forms of revictimization and obesity. Non-Latina African American and other race SMW were more likely than non-Latina white SMW to meet criteria for obesity. Current smokers had lower odds of obesity. SMW who reported experiencing sexual abuse in childhood only (AOR 2.37, 95% CI = 1.45–3.87) were more likely to meet criteria for obesity. Also, SMW with physical revictimization (AOR 2.38, 95% CI = 1.38–4.10) and any type of revictimization (AOR 2.36, 95% CI = 1.42–3.92) had higher odds of having obesity than women with no lifetime abuse.

Table 3.

Results of logistic regression models examining the associations of revictimization with obesity in sexual minority women (N = 616).

Physical abuse Sexual abuse Any abuse
Model 1
OR (95% CI)		 Model 2
AOR (95% CI)		 Model 1
OR (95% CI)		 Model 2
AOR (95% CI)		 Model 1
OR (95% CI)		 Model 2
AOR (95% CI)
Revictimization
 No lifetime abuse Reference Reference Reference Reference Reference Reference
 Childhood only 1.41 (0.77–2.56) 1.01 (0.52–1.94) 2.39 (1.54–3.71)*** 2.37 (1.45–3.87)** 2.32 (1.30–4.15)** 2.18 (1.15–4.12)*
 Adulthood only 1.69 (1.14–2.50)* 1.35 (0.87–2.09) 1.23 (0.77–1.96) 1.34 (0.81–2.24) 1.48 (0.94–2.34) 1.38 (0.83–2.29)
 Both childhood and adulthood 3.48 (2.16–5.62)*** 2.38 (1.38–4.10)** 1.94 (1.19–3.18)** 1.71 (0.98–3.00) 2.88 (1.85–4.47)*** 2.36 (1.42–3.92)**
Age - 1.03 (1.01–1.04)** - 1.03 (1.01–1.04)*** - 1.03 (1.01–1.04)***
Sexual identity
 Lesbian - Reference - Reference - Reference
  Bisexual 1.16 (0.75–1.78) 1.17 (0.75–1.79) 1.16 (0.76–1.80)
Race/ethnicity
 Non-Latina white Reference Reference Reference
 Non-Latina African - 2.80 (1.73–4.55)*** - 2.87 (1.77–4.63)*** - 2.84 (1.76–4.59)***
American
 Latina 1.62 (0.95–2.76) 1.56 (0.92–2.66) 2.52 (0.89–2.58)
  Non-Latina other race 3.20 (1.17–8.77)* 3.87 (1.43–10.51)** 3.24 (1.20–8.76)*
Education
 Less than high school Reference Reference Reference
 High school - 1.45 (0.65–3.26) - 1.24 (0.56–2.75) - 1.29 (0.58–2.88)
 Some college 1.13 (0.52–2.43) 0.93 (0.44–1.96) 1.04 (0.49–2.20)
 College graduate 0.63 (0.26–1.50) 0.50 (0.21–1.19) 0.56 (0.24–1.34)
  Graduate school 0.47 (0.19–1.15) 0.38 (0.15–0.91)* 0.43 (0.18–1.06)
Household income
 < $20,000 Reference Reference Reference
 $20,000–39,999 - 1.32 (0.77–2.28) - 1.42 (0.82–2.44) - 1.38 (0.80–2.37)
 $40,000–74,999 1.37 (0.78–2.40) 1.42 (0.80–2.51) 1.42 (0.81–2.50)
  ≥ $75,000 1.02 (0.52–2.00) 1.02 (0.51–2.01) 1.03 (0.52–2.04)
Relationship status
 Committed, cohabitating - Reference - Reference - Reference
 Committed, not cohabitating 0.66 (0.39–1.12) 0.62 (0.37–1.04) 0.67 (0.39–1.13)
  Single 0.77 (0.49–1.21) 0.77 (0.49–1.23) 0.79 (0.50–1.25)
Health insurance coverage - 0.84 (0.55–1.29) - 0.88 (0.57–1.34) - 0.84 (0.55–1.30)
Lifetime depression - 1.00 (0.68–1.49) - 0.96 (0.65–1.43) - 0.92 (0.62–1.38)
High social support - 0.81 (0.54–1.19) - 0.79 (0.54–1.17) - 0.82 (0.55–1.20)
Current tobacco smoking - 0.63 (0.40–0.98)* - 0.64 (0.41–1.00)* - 0.64 (0.41–0.99)*
Heavy episodic drinking - 0.88 (0.59–1.31) - 0.93 (0.63–1.39) - 0.92 (0.62–1.36)
Binge eating - 1.40 (0.87–2.26) - 1.47 (0.91–2.37) - 1.46 (0.91–2.36)
Open in a new tab

Note. Model 1 = unadjusted, Model 2 = adjusted for age, sexual identity, race/ethnicity, education, household income, relationship status, health insurance coverage, lifetime depression, social support, current smoking, heavy episodic drinking, and binge eating episodes.

*

p < 0.05

**

p < 0.01

***

p < 0.001

Table 4 presents associations between different forms of revictimization and hypertension. Non-Latina African American and other race SMW were more likely to report hypertension than non-Latina white SMW. Women with household incomes greater than $75,000 had lower odds of reporting hypertension. Physical revictimization (AOR 3.31, 95% CI 1.70–6.46) and any type of revictimization (AOR 2.60, 95% CI = 1.31–5.26) were associated with higher odds of hypertension. Although women who reported sexual revictimization had higher odds of hypertension in unadjusted analyses (OR 2.15, 95% CI = 1.20–3.89), this association was attenuated after covariate adjustment (AOR 1.37, 95% CI = 0.69–2.73).

Table 4.

Results of logistic regression models examining the associations of revictimization with hypertension in sexual minority women (N = 616).

Physical abuse Sexual abuse Any abuse
Model 1
OR (95% CI)		 Model 2
AOR (95% CI)		 Model 1
OR (95% CI)		 Model 2
AOR (95% CI)		 Model 1
OR (95% CI)		 Model 2
AOR (95% CI)
Revictimization
 No lifetime abuse Reference Reference Reference Reference Reference Reference
 Childhood only 2.88 (1.39–5.96)** 2.21 (0.98–5.03) 1.80 (1.05–3.13)* 1.65 (0.87–3.13) 2.06 (0.94–4.45) 2.06 (0.86–5.10)
 Adulthood only 1.77 (1.02–3.10)* 1.31 (0.69–2.49) 1.72 (0.98–3.06) 1.71 (0.89–3.25) 1.51 (0.80–2.89) 1.35 (0.64–2.83)
 Both childhood and adulthood 5.69 (3.23–10.09)*** 3.31 (1.70–6.46)*** 2.15 (1.20–3.89)* 1.37 (0.69–2.73) 3.48 (1.95–6.22)*** 2.60 (1.31–5.26)**
Age - 1.07 (1.04–1.09)*** - 1.07 (1.05–1.09)*** - 1.07 (1.05–1.10)***
Sexual identity
 Lesbian - Reference - Reference - Reference
 Bisexual 0.78 (0.42–1.44) 0.79 (0.43–1.42) 0.79 (0.43–1.45)
Race/ethnicity
 Non-Latina white Reference Reference Reference
 Non-Latina African American - 2.89 (1.52–5.49)** - 2.99 (1.59–5.62)** - 2.95 (1.57–5.55)**
 Latina 1.32 (0.59–2.93) 1.32 (0.60–2.92) 1.25 (0.57–2.75)
 Non-Latina other race 4.01 (1.23–13.04)* 5.08 (1.59–16.26)** 4.54 (1.42–14.55)*
Education
 Less than high school Reference Reference Reference
 High school - 0.57 (0.21–1.57) - 0.51 (0.19–1.39) - 0.51 (0.19–1.39)
 Some college 0.76 (0.30–1.96) 0.65 (0.26–1.65) 0.73 (0.28–1.86)
 College graduate 0.62 (0.20–1.89) 0.48 (0.16–1.44) 0.57 (0.19–1.71)
 Graduate school 0.51 (0.17–1.56) 0.40 (0.13–1.21) 0.46 (0.15–1.41)
Household income
 < $20,000 Reference Reference Reference
 $20,000–39,999 - 0.99 (0.50–1.99) - 1.08 (0.54–2.15) - 1.05 (0.53–2.10)
 $40,000–74,999 0.49 (0.23–1.04) 0.52 (0.24–1.09) 0.52 (0.24–1.10)
 ≥ $75,000 0.33 (0.13–0.81)* 0.35 (0.14–0.87)* 0.34 (0.14–0.84)*
Relationship status
 Committed, cohabitating - Reference - Reference - Reference
 Committed, not cohabitating 0.51 (0.25–1.07) 0.51 (0.25–1.05) 0.52 (0.25–1.08)
 Single 0.65 (0.36–1.19) 0.69 (0.38–1.24) 0.69 (0.38–1.24)
Health insurance coverage - 1.70 (0.93–2.97) - 1.71 (0.96–3.02) - 1.61 (0.91–2.86)
Lifetime depression - 1.59 (0.93–2.73) - 1.70 (0.99–2.89) - 1.53 (0.89–2.63)
High social support - 0.94 (0.57–1.55) - 0.82 (0.50–1.34) - 0.90 (0.55–1.49)
Current tobacco smoking - 1.26 (0.71–2.22) - 1.29 (0.74–1.27) - 1.28 (0.73–2.26)
Heavy episodic drinking - 1.28 (0.75–2.19) - 1.31 (0.77–2.23) - 1.35 (0.79–2.30)
Binge eating - 0.97 (0.50–1.86) - 1.00 (0.53–1.92) - 0.97 (0.50–1.86)
Open in a new tab

Note. Model 1 = unadjusted, Model 2 = adjusted for age, sexual identity, race/ethnicity, education, household income, relationship status, health insurance coverage, lifetime depression, social support, current smoking, heavy episodic drinking, and binge eating.

*

p < 0.05

**

p < 0.01

***

p < 0.001

Table 5 presents associations between different forms of revictimization and diabetes. Non-Latina African American SMW and those with health insurance coverage were more likely to report having diabetes. In unadjusted models, only physical revictimization (OR 2.86, 95% CI = 1.36–6.12) was associated with higher odds of diabetes. However, after adjusting for covariates, physical revictimization (AOR 1.74, 95% CI= 0.71–4.27), sexual revictimization (AOR 1.45, 95% CI= 0.55–3.84), and any type of revictimization (AOR 1.62, 95% CI = 0.65–4.03) were not significantly associated with diabetes.

Table 5.

Association of different forms of victimization with diabetes in sexual minority women (N = 616).

Physical abuse Sexual abuse Any abuse
Model 1
OR (95% CI)		 Model 2
AOR (95% CI)		 Model 1
OR (95% CI)		 Model 2
AOR (95% CI)		 Model 1
OR (95% CI)		 Model 2
AOR (95% CI)
Revictimization
No abuse Reference Reference Reference Reference Reference Reference
Childhood only 1.55 (0.54–4.46) 1.26 (0.39–4.10) 1.94 (0.92–4.23) 1.95 (0.80–4.77) 0.93 (0.29–3.04) 1.04 (0.28–3.84)
Adulthood only 1.08 (0.49–2.36) 0.98 (0.41–2.36) 1.39 (0.60–3.32) 1.94 (0.75–5.01) 0.90 (0.37–2.18) 1.13 (0.42–3.08)
Both childhood and adulthood 2.86 (1.35–6.12)** 1.74 (0.71–4.27) 2.01 (0.87–4.68) 1.45 (0.55–3.84) 1.96 (0.93–4.20) 1.62 (0.65–4.03)
Age - 1.05 (1.02–1.08)** - 1.04 (1.02–1.08)** - 1.05 (1.02–1.08)**
Sexual identity
 Lesbian - Reference - Reference - Reference
 Bisexual 0.54 (0.21–1.38) 0.53 (0.21–1.35) 0.53 (0.21–1.34)
Race/ethnicity
 Non-Latina white Reference Reference Reference
 Non-Latina African American - 4.65 (1.78–12.15)** - 4.77 (1.80–12.14)** - 4.64 (1.79–12.02)**
 Latina 2.70 (0.84–8.64) 2.66 (0.83–8.48) 2.62 (0.82–8.31)
 Non-Latina other race 3.74 (0.65–21.40) 4.09 (0.72–23.19) 3.94 (0.70–22.27)
Education
 Less than high school Reference Reference Reference
 High school - 0.26 (0.06–1.18) - 0.22 (0.05–0.99)* - 0.25 (0.06–1.09)
 Some college 0.64 (0.18–2.25) 0.57 (0.16–1.99) 0.64 (0.18–2.27)
 College graduate 0.43 (0.09–2.04) 0.39 (0.08–1.83) 0.44 (0.09–2.07)
 Graduate school 0.41 (0.09–1.85) 0.36 (0.08–1.63) 0.40 (0.09–1.79)
Household income
 < $20,000 Reference Reference Reference
 $20,000–39,999 - 0.66 (0.24–1.81) - 0.68 (0.25–1.87) - 0.68 (0.24–1.84)
 $40,000–74,999 0.37 (0.13–1.06) 0.38 (0.13–1.11) 0.38 (0.13–1.09)
 ≥ $75,000 0.37 (0.11–1.21) 0.36 (0.11–1.20) 0.38 (0.11–1.26)
Relationship status
 Committed, cohabitating - Reference - Reference - Reference
 Committed, not cohabitating 0.61 (0.23–1.62) 0.60 (0.23–1.60) 0.63 (0.24–1.67)
 Single 0.56 (0.24–1.32) 0.56 (0.24–1.32) 0.58 (0.25–1.37)
Health insurance coverage - 2.92 (1.14–7.48)* - 3.19 (0.14–8.20)* - 2.87 (1.11–7.38)*
Lifetime depression - 0.75 (0.36–1.53) - 0.68 (0.33–1.40) - 0.71 (0.34–1.48)
High social support - 0.63 (0.31–1.27) - 0.58 (0.29–1.17) - 0.62 (0.31–1.25)
Current tobacco smoking - 0.60 (0.26–1.40) - 0.60 (0.26–1.41) - 0.60 (0.26–1.40)
Heavy episodic drinking - 0.43 (0.18–1.01) - 0.42 (0.18–1.01) - 0.44 (0.18–1.04)
Binge eating - 1.79 (0.74–4.35) - 1.80 (0.74–4.38) - 1.75 (0.72–4.26)
Open in a new tab

Note. Model 1 = unadjusted, Model 2 = adjusted for age, sexual identity, race/ethnicity, education, household income, relationship status, health insurance coverage, lifetime depression, social support, current smoking, heavy episodic drinking, and binge eating.

*

p < 0.05

**

p < 0.01

***

p < 0.001

Discussion

In a racially/ethnically diverse community-based sample of SMW, we found that experiencing physical revictimization and any revictimization were associated with a higher prevalence of obesity and hypertension. SMW who experienced sexual abuse in childhood alone were also more likely to meet criteria for obesity. These findings indicate that revictimization is a potential contributor to cardiometabolic risk in SMW.

Few studies have examined interpersonal trauma as a cardiometabolic risk factor among SMW. Our findings are consistent with those of previous studies that have found a link between interpersonal trauma, specifically childhood sexual abuse, and self-reported cardiometabolic risk in community samples of SMW (Aaron & Hughes, 2007; Smith et al., 2010). Similarly, a previous study also found that SMW who reported greater numbers of different forms of lifetime trauma were at increased risk for obesity and hypertension (Caceres, Veldhuis, et al., 2019). Findings from the present study make an important contribution to our understanding of interpersonal trauma, specifically revictimization, as a cardiometabolic risk factor in SMW. These findings support the need for future research to investigate whether the associations of revictimization and cardiometabolic risk we observed are present in other samples of SMW.

We also identified significant racial/ethnic differences in cardiometabolic risk among SMW. Non-Latina African American SMW in this study reported a higher prevalence of obesity, hypertension, and diabetes than non-Latina white SMW. In addition, non-Latina other race SMW were more likely than non-Latina white participants to report having obesity and hypertension. Findings for African American SMW are consistent with those of two previous studies that examined racial/ethnic differences in cardiometabolic risk in community-based samples of SMW (Caceres, Veldhuis, et al., 2019; Molina et al., 2014). To date, fewer studies have examined the prevalence of cardiometabolic risk in other race SMW. Our data suggest there is a need for targeted screening for cardiometabolic risk factors among racial/ethnic minority SMW. Additional research is needed to examine factors that might explain excess cardiometabolic risk in SMW of color.

We hypothesized that participants who reported revictimization would also have a higher prevalence of poor psychosocial outcomes. Our finding that SMW who reported any type of revictimization had the highest odds of meeting criteria for lifetime depression is consistent with evidence from studies of women in the general population (Miron & Orcutt, 2014; Najdowski & Ullman, 2011). We found that women who were revictimized reported lower levels of social support—a finding that is also consistent with those from general population studies (Aakvaag et al., 2019; Hawn et al., 2018).

Contrary to our hypothesis, we found no differences in current tobacco use and heavy episodic drinking between SMW who reported revictimization and those who did not. Overall, there is limited data on the influence of revictimization on tobacco use among women in the general population. However, our findings are inconsistent with those of several studies in the general population that suggest that revictimization is associated with higher rates of hazardous alcohol consumption in women (DeCou & Skewes, 2017; Ullman, 2016; Valenstein-Mah et al., 2015). It is possible that the higher rates of heavy drinking in SMW compared to heterosexual women may obscure the relationship between revictimization and heavy drinking in samples of SMW (Caceres et al., 2018; Hughes et al., 2010; Hughes, Szalacha, & McNair, 2010). In contrast, we found the prevalence of binge eating was higher among SMW who reported any type of revictimization or childhood sexual abuse alone. These findings are consistent with previous work that demonstrate associations between interpersonal trauma and binge eating among women (Palmisano et al., 2016). Although binge eating has been identified as a potential risk factor for cardiometabolic risk in the general population, we found no statistically significant associations between binge eating and cardiometabolic risk in our sample of SMW (Dias Santana et al., 2019; Nieto-Martínez et al., 2017; Olguin et al., 2017). Overall, research that investigates whether revictimization is associated with psychosocial and behavioral risk factors for CVD in SMW is needed as this may help identify possible targets for behavioral interventions aimed at reducing cardiometabolic risk in this population.

Limitations

Our study is not without limitations. The most important limitation is that this study used cross-sectional data, so we cannot infer causality from these results. Therefore, it remains unclear whether revictimization contributes to higher rates of psychosocial factors and health behaviors linked with cardiometabolic risk in SMW or whether these associations are bidirectional. Although the CHLEW is a longitudinal study, approximately half of the sample was added in Wave 3, which included more SMW of color and bisexual women. Cross-sectional data from Wave 3 were used to ensure adequate statistical power for analyses. Our findings support the need for longitudinal research with large, diverse samples to better understand the association between cardiometabolic risk and interpersonal trauma over time.

There are several measurement concerns in this study. Most notably, we were unable to assess severity and duration of interpersonal trauma. Our measure of revictimization assessed simply whether any trauma had occurred at a particular life stage (i.e., childhood, adulthood, or both). This may have obscured important differences between SMW who experienced more severe and a longer duration of trauma across their lives than those who experienced less severe and/or fewer instances of trauma. This is especially important because previous research indicates that individuals with greater exposure to interpersonal trauma have increased cardiometabolic risk (Friedman et al., 2015b; Stein et al., 2010). Similarly, given that health behavior variables in this study were dichotomous, we were unable to account for severity of current tobacco use, heavy episodic drinking, and binge eating in associations with revictimization and cardiometabolic risk. Future research should account for complexities in the relationships between interpersonal trauma and health behaviors with cardiometabolic risk to ascertain which factors confer the greatest risk.

Cardiometabolic risk in the present study was based on self-reported data and therefore may not accurately reflect participants’ health profiles. It is possible that SMW in our study misreported their height or weight (used to calculate BMI) or may not have known whether they had been diagnosed with hypertension or diabetes by a healthcare provider. Future research in this area should compare self-reported health data with data from health records to more accurately evaluate participants’ cardiovascular health. Lastly, well-established risk factors for CVD (e.g., physical inactivity, dietary habits, sleep duration) were not assessed in the CHLEW study. We recommend that future research comprehensively examine CVD risk factors among SMW.

Implications for Practice and Policy

This study has important implications for clinical practice and policy. Our findings support the importance of screening SMW for interpersonal trauma. Trauma-informed care is a strengths-based approach to healthcare delivery that emphasizes psychological, emotional, and physical safety for survivors of trauma and their healthcare providers (Hopper et al., 2010). It recognizes the importance of screening and focused follow-up assessment and uses a sociocultural lens to understand how individuals process and cope with trauma (Substance Abuse and Mental Health Services Administration, 2014). Support services for interpersonal trauma (e.g., hotlines, community programs, emergency departments) should recognize the unique stressors SMW face that may lead them to underutilize these services (e.g., fear of discrimination from healthcare providers) and the excess stress likely experienced by SMW who have histories of trauma (Czaja et al., 2016; Qureshi et al., 2018). Such stress may place SMW at greater risk for CVD. Thus, culturally sensitive and trauma informed support services that address traumatic stress and its impact on health are needed to reduce such risks among SMW. For example, women in same-sex relationships may not be screened for intimate partner violence because women, incorrectly, are generally not perceived as perpetrators of violence. SMW in same-sex relationships may have a harder time finding support, safety, and resources after victimization. Initiatives to ensure that healthcare providers have adequate training in trauma-informed care to adequately assess and respond to cases of trauma exposure are needed.

Policies that support routine screening of violence among women are needed to better understand how different forms of violence (e.g., childhood abuse and intimate partner violence) are associated with negative health outcomes in SMW. However, there is considerable debate about the appropriate settings and conditions to screen for violence exposure in women. In 2018, the U.S. Preventative Services Task Force concluded that evidence for routine screening of violence beyond the assessment of intimate partner violence in women of reproductive age is limited (U.S. Preventive Services Task Force, 2018). This contradicts recommendations from the American College of Obstetricians and Gynecologists and the World Health Organization that have called for universal screening of violence exposure in all women (The American College of Obstetricians and Gynecologists, 2012; World Health Organization, 2013). Given these contradictory recommendations, future research should investigate the risks and benefits of routine assessment of violence among women and which groups of women would most benefit from screening. This will be an important step in establishing evidence-based policies for violence assessment in women.

Conclusions

This study adds to the paucity of available data about the contributions of interpersonal trauma to cardiometabolic risk in SMW. Findings of higher rates of obesity and hypertension among SMW who report revictimization highlight the need for early treatment and intervention to reduce cardiometabolic risk in this vulnerable population. Healthcare providers should utilize trauma-informed approaches to support SMW with trauma histories in optimizing their health and well-being. Future research that incorporates longitudinal designs is needed to examine psychosocial, behavioral, and physiological mechanisms that link revictimization with cardiometabolic risk in SMW.

Acknowledgments:

The authors would like to thank Kelly R. Martin for her editorial assistance. Dr. Caceres had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Funding Statement: This work was supported by the National Institute on Alcohol Abuse and Alcoholism under award numbers R01AA013328 to Dr. Hughes and K23AA027288 to Dr. Anderson. Dr. Caceres was supported by an award from the National Heart, Lung, and Blood Institute (K01HL146965).

Footnotes

Conflicts of Interest: No conflicts to disclose.

Contributor Information

Billy A. Caceres, Program for the Study of LGBT Health, Columbia University School of Nursing, 560 West 168th Street, New York, NY 10032.

Britney M. Wardecker, Pennsylvania State College of Nursing.

Jocelyn Anderson, Pennsylvania State College of Nursing.

Tonda L. Hughes, Program for the Study of LGBT Health, Columbia University School of Nursing.

Henrik H. Bendixen, Program for the Study of LGBT Health, Columbia University School of Nursing.

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