Sexual Assault Victimization and Eating Disorders Among College-enrolled Men

Abstract

Sexual assault victimization and eating disorder rates are high among college populations and have significant psychological, physiological, and social outcomes. Previous research has found a positive relationship between experiences of sexual assault and eating disorder symptoms; however, these analyses have primarily focused on female students. Using data from the 2017-2018 Healthy Minds Study, the aim of this study was to investigate the relationship between experiencing a sexual assault within the previous 12 months and screening positive for an eating disorder among cisgender college-enrolled men. It was hypothesized that college-enrolled men who report experiencing a sexual assault within the previous 12 months would be more likely to screen positive for an eating disorder. Analyses were conducted using a sample of 14,964 cisgender college-enrolled men. Among the sample, nearly 4% reported a sexual assault within the previous 12 months and nearly 16% screened positive for an eating disorder. Results from logistic regression analyses indicated that college-enrolled men who reported experiencing a sexual assault in the previous 12 months, compared to those who did not, had significantly greater odds of screening positive for an eating disorder (OR = 1.40, p < .01). Analyses also indicated that college-enrolled men who identified as gay, queer, questioning, or other sexual orientation and reported experiencing a sexual assault in the previous 12 months had greater odds of screening positive for an eating disorder (OR = 2.50, p < .001) compared to their heterosexual peers who did not experience a sexual assault in the previous 12 months. These results indicate that eating disorders may be a negative outcome among college-enrolled men who have experienced a sexual assault, particularly among sexual minority men. Thus, mental health professionals need to be adequately prepared to treat the underserved population of men who experience an eating disorder and who have experienced sexual assault.

Keywords

sexual assault eating disorders college men sexual minority men college mental health

Background

Reported rates of adult sexual assault among men have varied widely (Peterson et al., 2011). This may in part be due to the stereotypes and assumptions that victims of sexual assault are primarily, if not exclusively, women (Chapleau et al., 2008; Turchik & Edwards, 2012). Research indicates that roughly one in five women (18%) experience rape, and one in two women (45%) experience a sexual assault other than rape during their lifetime (Black et al., 2011). Comparatively, 1 in 71 men (1.4%) experience rape, and 1 in 5 men (22%) experience sexual assault other than rape during their lifetime (Black et al., 2011).

Based on current data, sexual assault victimization is also less likely to occur in college-enrolled men compared to women. However, in the National Crime Victimization Survey (NCVS), college men aged 18–24 years report experiencing sexual assault at rates greater than non-college men, accounting for 17% of victimizations (1.4 per 1,000) from 1995–2013 (U.S. Department of Justice, 2014). Similarly, research at two universities in New York City found that 13% of male students had experienced a sexual assault since starting their college education (Mellins et al., 2017).

Experiencing a sexual assault may have substantial effects on an individual, particularly negative mental health effects. Among women, previous research has suggested that experiencing a sexual assault is associated with eating disorders (Capitaine et al., 2011; Fischer et al., 2010; Laws & Golding, 1996). This relationship was confirmed in a literature review conducted by Madowitz et al. (2015) that showed that individuals who experienced eating disorders also had high rates of previous sexual assault victimization. Two etiological mechanisms were proposed in the review that connect sexual trauma and eating disorders: body-related factors and management of psychological difficulties. Body-related factors include body dissatisfaction and the use of eating disorder behaviors to create body changes that protect against future sexual victimizations. Management of psychological difficulties is the use eating disorder behaviors to manage the emotional and behavioral regulation difficulties individuals experience after a sexual assault . A major limitation to this review is the lack of studies that include men in their sample (4 of 32 studies; Madowitz et al., 2015). However, studies that included men tended to focus on either investigating the impact of childhood sexual abuse and eating disorders (Corstorphine et al., 2007; Dworkin et al., 2014; Ng et al., 2013), investigating psychiatric comorbidities (including posttraumatic stress disorder; Grilo et al., 2009), or only included one man (Corstorphine et al., 2007). Despite these limitations, the existing research indicates that eating disorders may be present among men who have experienced a sexual assault, thus warranting further investigation.

Current research points to many negative mental health outcomes associated with sexual assault victimization among adult men of all sexual orientations. These include, depression, anxiety, anger, and suicidal ideation (Tewksbury, 2007; Walker et al., 2005). Substance use is also prevalent among both heterosexual and sexual minority adult men who have experienced a sexual assault (Hines et al., 2012; Hughes et al., 2010). Lastly, adult men with a sexual assault history may experience physical injury, sexually transmitted diseases, and sexual dysfunction (Tewksbury, 2007). All of these outcomes may significantly impact the overall functioning of these men.

Eating disorders research has primarily focused on women due to their overall greater risk (Smink et al., 2012; Wade et al., 2011). However, eating disorders among men are a notable public health problem particularly because they are often underdiagnosed and undertreated (Strother et al., 2012). Estimates suggest that 25% of individuals diagnosed with anorexia nervosa and bulimia nervosa, and 36% of individuals diagnosed with binge eating disorder, are men (Hudson et al., 2007). Prevalence estimates of eating disorder symptoms among college-enrolled men range from 3 to 5.5% (Eisenberg et al., 2011; Hoerr et al., 2002; Lipson & Sonneville, 2017). Given these prevalence rates, more research is needed to gain additional knowledge and understanding on this population.

Research has shown that sexual minority men are more likely to have body image concerns (Calzo et al., 2013) and engage in disordered eating behaviors (Calzo et al., 2015; Matthews-Ewald et al., 2014; Watson et al., 2017) compared to heterosexual men. Among college-enrolled men, sexual minority men have greater odds of screening positive for an eating disorder (Lipson & Sonneville, 2017). Sexual minority men may also be more susceptible to sexual assault as lifetime rates of sexual assault among gay and bisexual men are higher compared to heterosexual men (Rothman et al., 2011). Among college men, rates of sexual assault among gay and bisexual men are similar to those among heterosexual women (Ford & Soto-Marquez, 2016).

Much like sexual assault, eating disorders are associated with many mental health comorbidities. This may include, depression, substance abuse (Carlat et al., 1997), panic disorder, generalized anxiety disorder, suicidal thoughts, nonsuicidal self-injury, and cigarette smoking (Eisenberg et al., 2011). Lastly, both eating disorders and sexual assault can significantly impact academic performance (Arria et al., 2013; Baker et al., 2016; Eisenberg et al., 2009; Jordan et al., 2014), further indicating a need for college mental health professionals to be prepared to treat this population in order to help college students succeed.

Given the need for more research to understand the factors that are associated with eating disorders among men, this study aimed to identify the association between experiencing a sexual assault within the previous 12 months and screening positive for an eating disorder in college-enrolled men. Guided by the emotion regulation model, which posits the ways in which individuals engage in either adaptive or maladaptive emotion regulation techniques (Aldao et al., 2010; Gross, 1998), it is hypothesized that college-enrolled men who have experienced a sexual assault in the previous 12 months will have greater odds of screening positive for an eating disorder. This hypothesis is grounded in the notion that college-enrolled men who have experienced a sexual assault may encounter an emotional state change that is marked by either hyperarousal or hypoarousal. This requires the individual to engage in an emotion regulation technique to regulate their emotions. These techniques can either be adaptive (i.e., reappraisal, problem solving, and/or acceptance) or maladaptive (Aldao et al., 2010; Gross, 1998). The maladaptive techniques may take the form of eating disorder behaviors, such as restricting, binging and purging, and/or binging. The use of these behaviors provides temporary emotional stability until the next activating event, such as a flashback or environmental trigger. This conceptual framework is outlined in Figure 1.

Figure 1

Sexual assault and ED screen.

Methods

A secondary data analysis of the Healthy Minds Study (HMS) was used to investigate the aim of this study. HMS is an annual, cross-sectionl survey that measures mental health, substance use, and interpersonal issues, as well as help seeking, in undergraduate and graduate students. Universities elect to participate in HMS, providing a convenience sample of participating universities. At universities with greater than or equal to 4,000 students, 4,000 students are randomly recruited to participate in the survey; at universities with under 4,000 students, all students are recruited. Randomly selected students are invited to participate in the survey via email. To be eligible to participate, students must be at least 18 years old. There are no other inclusion or exclusion criteria. Data collection occurs during a three-week time period that avoids the start and end of an academic semester. The survey is distributed using Qualtrics online survey software. To incentivize participation, all students who are randomly recruited are entered into a drawing for one of ten $100 and one of two $500 Amazon gift cards. HMS is approved by the institutional review boards of all participating universities. Additionally, HMS received a certificate of confidentiality from the National Institutes of Health. This study was also approved by the first author’s University Institutional Review Board.

Sample

This analysis used the 2017–2018 (n = 68,245) school year data set. This analysis only included respondents who identified their sex assigned at birth and their gender as male (n = 21,359) and answered all questions under investigation. The final analytic sample included 14,964 participants.

Measures

Dependent variable.

Eating disorders were screened for using the SCOFF tool, which is a five-question measure that has been widely used to assess for potential eating disorders/disordered eating in a variety of populations (Morgan et al., 1999). The five questions are: “Do you ever make yourself sick because you feel uncomfortably full?” “Do you worry that you have lost control over how much you eat?” “Have you recently lost more than 15 pounds in a three-month period?” “Do you believe yourself to be fat when others say you are too thin?” “Would you say that food dominates your life?” A dichotomous “yes” or “no” response was available for each question. A score of 2 or more “yes” responses indicates the potential for an eating disorder (Luck et al., 2002; Parker et al., 2005).

Independent variables.

Sexual assault was measured using the question: “In the past 12 months, has anyone had unwanted sexual contact with you? (Please count any experience of unwanted sexual contact [e.g., touching of your sexual body parts, oral sex, anal sex, sexual intercourse, and penetration of your vagina or anus with a finger or object] that you did not consent to and did not want to happen regardless of where it happened.)” A dichotomous “yes” or “no” response was available.

In addition, we created a combined independent variable that included both sexual assault victimization and sexual orientation given the higher rates of sexual assault victimization among sexual minority men (Ford & Soto-Marquez, 2016; Rothman et al., 2011). This variable had four response categories: “No sexual assault and straight (heterosexual),” “Yes sexual assault and straight (heterosexual),” “No sexual assault and sexual minority,” and “Yes sexual assault and sexual minority.”

Control variables.

Depression was measured using the Patient Health Questionnaire-9 (PHQ-9). This screening tool is based on the nine Diagnostic and Statistical Manual for Mental Disorders, Fourth Edition criteria for a major depressive episode (Kroenke et al., 2001; Spitzer et al., 1999). Scores range from 0 to 27. Following standard scoring of the PHQ-9, a dichotomous variable was used for a negative screen (scores 0–9) and a positive screen (10–27; Kroenke et al., 2001).

Anxiety was measured using the Generalized Anxiety Disorder 7-Item (GAD-7). This screening tool was developed to reflect all components of the Diagnostic and Statistical Manual for Mental Disorders, Fourth Edition criteria for generalized anxiety disorder (Spitzer et al., 2006). Scores range from 0 to 21. This variable was converted into a dichotomous composite variable with respondents who screened negative (scores 0–9) and who screened positive (10–21) for anxiety (Spitzer et al., 2006).

Alcohol use was measured using the question: “Over the past 2 weeks, did you drink alcohol?” A dichotomous “yes” or “no” response was available.

Illicit drug use was measured using the question: “Over the past 30 days, have you used any of the following drugs? (Select all that apply).” Potential responses include: “marijuana;” “cocaine (any form, including crack, powder, or freebase);” “heroin;” “methamphetamines (also known as speed, crystal meth, or ice);” “other stimulants (such as Ritalin, Adderall) without a prescription;” “ecstasy;” “other drugs without a prescription;” and “No, none of these.” This variable was converted into a dichotomous variable with respondents who reported no illicit drug use and those who did.

Demographic variables.

Demographic variables included: age, race/ethnicity, sexual orientation, relationship status, degree program, and residence. Age was grouped into the following categories: 18–20, 21–23, 24–27, and 28 and older (Lipson & Sonneville, 2017). Race/ethnicity was grouped into the following categories: “White or Caucasian, non-Hispanic, non-Arab;” “Black or African American, non-Hispanic;” “Hispanic/Latino;” “Asian or Pacific Islander;” “Arab/Middle Eastern or Arab American;” “More than one race/ethnicity;” and “Other (American Indian, Native American, or Alaskan American”; Eisenberg et al., 2011). Sexual orientation was dichotomized into “straight (heterosexual)” and “sexual minority”, which included respondents who identified their sexual orientation as “bisexual” “gay or lesbian,” “queer,” “questioning,” and “other (open response)”. This is consistent with prior publications using HMS data (Lipson & Sonneville, 2017). Degree program was dichotomized into undergraduate or graduate students. Relationship status was grouped into the following categories: “Single;” “in a relationship, married, in a domestic partnership, or engaged;” “divorced, separated, or widowed;” and “other”. Residence was grouped into the following categories: “On-campus housing, residence hall;” “on-campus housing, apartment;” “fraternity or sorority house;” “on- or off-campus co-operative housing;” “off-campus, non-university housing;” “with my parents (or relatives);” and “other.”

Statistical Analysis

Descriptive analyses were conducted to provide an overview of the sample characteristics. Bivariate analyses were conducted to test for associations between control variables, demographic variables, the independent variable, the combined independent variable, and the outcome variable for the total sample. Only variables that were significant in the bivariate analyses were moved on to the multivariable analysis.

Logistic regression analyses were conducted to test the study hypothesis while adjusting for the control variables and demographic variables that were significant in the bivariate analyses. Model 1 of the logistic regression analyses examined the relationship between sexual assault victimization and screening positive for an eating disorder while adjusting for the control variables (depression and anxiety screening and illicit drug use) and the demographic variables (race/ethnicity, age, sexual orientation, relationship status, and residence). Model 2 of the logistic regression analyses examined the relationship between the combined independent variable (both sexual assault victimization and sexual orientation) and screening positive for an eating disorder while adjusting for the control variables (depression and anxiety screening and illicit drug use) and the demographic variables (race/ethnicity, age, sexual orientation, relationship status, and residence). We then conducted a postestimation analysis for the marginal effects of each category on screening positive for an eating disorder while holding Model 2 constant. The significance level for all analyses was set to α = 0.05. All analyses were conducted in 2019 using Stata 15.1 (Stata Corp, 2017).

Results

Descriptive and Bivariate Results

Table 1 presents the entire descriptive and bivariate results. Nearly 16% of the sample screened positive for an eating disorder while nearly 4% reported a sexual assault within the previous 12 months. Results from chi-square tests revealed significant associations between screening positive for an eating disorder and sexual assault (χ² = 75.03, p < .001), such that college-enrolled men who experienced a sexual assault had the greatest rate (28.73%) of screening positive for an eating disorder. Additionally, results from chi-square tests indicated a significant association between screening positive for an eating disorder and the combined independent variable of sexual assault and sexual orientation (χ² = 258.66, p < .001), such that college-enrolled men who experienced a sexual assault and identified as a sexual minority had the greatest rate (35.27%) of screening positive for an eating disorder. Lastly, results from chi-square tests indicated significant associations between screening positive for an eating disorder and race/ethnicity (χ² = 68.12, p < .001), age (χ² = 9.12, p < .05), sexual orientation (χ² = 230.13, p < .001), residence (χ² = 18.61, p < .01), relationship status (χ² = 8.84, p < .05), depression screen (χ² = 778.26, p < .001), anxiety screen (χ² = 602.36, p < .001), and illicit drug use (χ² = 48.45, p < .001). Due to lack of significance, degree program and alcohol use were not included in the multivariable analyses.

Table 1.

2017–2018 HMS Sample Characteristics and Results of Chi-Square Tests (n = 14,964).

			Eating Disorder Screen
	%	N	Positive % (n)	Negative % (n)	χ2
Age					9.12*
18–20	35.35	5,290	15.09 (798)	84.91 (4,492)
21–23	28.99	4,338	16.39 (711)	83.61 (3,627)
24–27	17.68	2,646	16.74 (443)	83.26 (2,203)
28+	17.98	2,690	14.31 (385)	85.69 (2,305)
Race/ethnicity					68.11***
White or Caucasian, non-Hispanic, non-Arab	57.54	8,591	13.97 (1,200)	86.03 (7,391)
Black or African American, non-Hispanic	4.60	687	12.08 (83)	87.92 (604)
Hispanic/Latino/a	7.69	1,148	19.69 (226)	80.31 (922)
Asian or Pacific Islander	16.22	2,422	19.24 (466)	80.76 (1,956)
Arab/Middle Eastern or Arab American	1.88	280	18.93 (53)	81.07 (227)
Other	2.12	317	18.30 (58)	81.70 (259)
More than one race/ethnicity	9.95	1,485	16.70 (248)	83.30 (1,237)
Sexual orientation					230.13***
Straight (Heterosexual)	85.69	12,757	13.73 (1,752)	86.27 (11,005)
Sexual minority	14.31	2,131	26.61 (567)	73.39 (1,564)
Degree program					0.39
Undergraduate	63.73	9,536	15.58 (1,486)	84.42 (8,050)
Graduate	31.73	4,748	15.56 (739)	84.44 (4,009)
Other & more than 1	4.54	680	16.47 (112)	83.53 (568)
Residence					18.61**
On-campus housing, residence hall	24.10	3,605	14.48 (522)	85.52 (3,083)
On-campus housing, apartment	7.25	1,085	17.51 (190)	82.49 (895)
Fraternity or sorority house	1.19	178	10.11 (18)	89.89 (160)
On- or off-campus co-operative housing	1.30	195	18.97 (37)	81.03 (158)
Off-Campus, non-university housing	54.37	8,133	15.46 (1,257)	84.54 (6,876)
With my parents (or relatives)	10.24	1,531	17.83 (273)	82.17 (1,258)
Other	1.54	231	17.32 (40)	82.68 (191)
Relationship status					8.84*
In a relationship/married	46.49	6,954	14.71 (1,023)	85.29 (5,931)
Single	52.22	7,811	16.34 (1,276)	83.66 (6,535)
Divorced/widowed	0.51	76	18.42 (14)	81.58 (62)
Other	0.78	116	18.97 (22)	81.03 (94)
Depression score (PHQ-9)					778.26***
Negative screen	73.38	10,743	10.60 (1,139)	89.40 (9,604)
Positive screen	26.62	3,898	29.55 (1,152)	70.45 (2,746)
Anxiety score (GAD-7)					602.36***
Negative screen	79.90	11,701	11.89 (1,391)	88.11 (10,310)
Positive screen	20.10	2,943	30.24 (890)	69.76 (2,053)
Alcohol use, past 2 weeks					0.57
No	35.72	5,299	15.23 (807)	84.77 (4,492)
Yes	64.28	9,536	15.70 (1,497)	84.30 (8,039)
Illicit drug use, past 30 days					48.45***
None	74.84	9,320	14.14 (1,318)	85.86 (8,002)
Any	25.16	3,134	19.34 (606)	80.66 (2,528)
Sexual assault, past 12 months					75.03***
No	96.34	14,291	15.02 (2,146)	84.98 (12,145)
Yes	3.66	543	28.73 (156)	71.27 (387)
Eating disorder (SCOFF Score)
Negative Screen	84.38	12,627	–	–	–
Positive Screen	15.62	2,337	–	–	–
Sexual assault, past 12 months and sexual orientation					258.66***
No and straight (Heterosexual)	83.81	12,542	13.59 (1,705)	86.41 (10,837)
Yes and straight (Heterosexual)	2.01	301	23.26 (70)	76.74 (231)
No and sexual minority	12.56	1,880	25.37 (477)	74.63 (1,403)
Yes and sexual minority	1.61	241	35.27 (85)	64.73 (156)

*p < .05 **p < .01 ***p < .001

Multivariable Results

Table 2 presents the entire multivariable results. Findings from Model 1 of the logistic regression analyses indicated that college-enrolled men who reported a sexual assault within the previous 12 months, compared to those who did not, had significantly greater odds of screening positive for an eating disorder (OR = 1.40, p < .01) while adjusting for demographic and control variables.

Table 2.

Logistic Regression Analyses for Eating Disorder Screen by Independent Variables and Covariates.

Eating Disorder Screen (Ref. group: Negative Screen)	Model 1***		Model 2***
	OR	95% CI	OR	95% CI
Age
18–20	Ref.	Ref.	Ref.	Ref.
21–23	1.00	[.87, 1.16]	1.00	[.87, 1.16]
24–27	1.08	[.91, 1.29]	1.08	[.91, 1.29]
28+	1.01	[.84, 1.22]	1.02	[.84, 1.22]
Race/ethnicity
White or Caucasian, non-Hispanic, non-Arab	Ref.	Ref.	Ref.	Ref.
Black or African American, non-Hispanic	.81	[.61, 1.08]	.81	[.61, 1.07]
Hispanic/Latino/a	1.30**	[1.08, 1.57]	1.30**	[1.08, 1.57]
Asian or Pacific Islander	1.55***	[1.34, 1.79]	1.55***	[1.34, 1.79]
Arab/Middle Eastern or Arab American	1.26	[.86, 1.86]	1.26	[.85, 1.85]
Other	.99	[.69, 1.41]	.99	[.69, 1.41]
More than one race/ethnicity	1.12	[.94, 1.33]	1.12	[.94, 1.33]
Sexual orientation
Straight (heterosexual)	Ref.	Ref.	–	–
Sexual minority	1.84***	[1.62, 2.10]	–	–
Residence
On-campus housing, residence hall	Ref.	Ref.	Ref.	Ref.
On-campus housing, apartment	1.18	[.94, 1.47]	1.18	[.94, 1.47]
Fraternity or sorority house	.69	[.39, 1.23]	.69	[.39, 1.23]
On- or off-campus co-operative housing	1.13	[.72, 1.76]	1.13	[.72, 1.76]
Off-campus, non-university housing	1.01	[.87, 1.19]	1.01	[.87, 1.19]
With my parents (or relatives)	1.23*	[1.00, 1.51]	1.23*	[1.00, 1.51]
Other	1.27	[.82, 1.98]	1.27	[.82, 1.98]
Relationship status
In a relationship/married	Ref.	Ref.	Ref.	Ref.
Single	.95	[.85, 1.06]	.95	[.85, 1.06]
divorced/widowed	1.12	[.54, 2.28]	1.12	[.55, 2.29]
Other	.65	[.36, 1.19]	.65	[.35. 1.19]
Depression score (PHQ-9)
Negative screen	Ref.	Ref.	Ref.	Ref.
Positive screen	2.48***	[2.218, 2.83]	2.48***	[2.18, 2.82]
Anxiety score (GAD-7)
Negative screen	Ref.	Ref.	Ref.	Ref.
Positive screen	1.73***	[1.51, 1.98]	1.73***	[1.51, 1.98]
Illicit drug use, past 30 days
None	Ref.	Ref.	Ref.	Ref.
Any	1.21**	[1.08, 1.37]	1.21**	[1.08, 1.37]
Sexual assault, past 12 months
No	Ref.	Ref.	–	–
Yes	1.40**	[1.10, 1.77]	–	–
Sexual assault, past 12 months and sexual orientation
No and straight (heterosexual)			Ref.	Ref.
Yes and straight (heterosexual)			1.45*	[1.04, 2.02]
No and sexual minority			1.85***	[1.62, 2.12]
Yes and sexual minority			2.50***	[1.82, 3.42]

Note: OR = odds ratio; CI = confidence interval

Model 1: n = 11,849

Model 2: n = 11,849

*p < .05 **p < .01 ***p < .001

Model 2 examined the combination of experiencing a sexual assault within the previous 12 months and sexual orientation on screening positive for an eating disorder while adjusting for the demographic and control variables. Findings indicated that, compared to college-enrolled men who did not experience a sexual assault within the previous 12 months and identified as straight (heterosexual), college-enrolled men who experienced a sexual assault within the previous 12 months and identified as a sexual minority had the greatest odds of screening positive for an eating disorder (OR = 2.50, p <. 001).

Findings from postestimation analysis for the marginal effects indicated that college-enrolled men who identify as a sexual minority had a greater (0.273–0.222 = 0.051) predictive margin for sexual assault victimization in the previous 12 months compared to those who identify as straight (heterosexual; 0.185–0.138 = 0.047). Table 3 presents the entire postestimation analysis results. The results from both the postestimation and logistic regression analyses show that sexual orientation, identifying as a sexual minority in this case, is the primary contributor in the interaction of sexual assault victimization and sexual orientation driving the significant association with a positive eating disorder screen.

Table 3.

Postestimation Marginal Effects Results

Variable Group	Predicted Probabilities (Standard Error)
No sexual assault, past 12 months and straight (heterosexual)	0.138 (0.003)***
Yes sexual assault, past 12 months and straight (heterosexual)	0.185 (0.023)***
No sexual assault, past 12 months and sexual minority	0.222 (0.009)***
Yes sexual assault, past 12 months and sexual minority	0.273 (0.028)***

*p < .05 **p < .01 ***p < .001

Discussion

The aim of this study was to explore whether experiencing a sexual assault is associated with screening positive for an eating disorder among college-enrolled men. The results from this study, using large-scale, population-level data, fill an important void in the evidence base on eating disorders among the male population. Results indicate that college-enrolled men who experienced a sexual assault within the previous 12 months had significantly greater odds of screening positive for an eating disorder. This confirms the study’s hypothesis that eating disorders are associated with sexual assault among college men and expands on previous research that has indicated there is a positive relationship between sexual assault and eating disorders among women (Capitaine et al., 2011; Fischer et al., 2010; Madowitz et al., 2015). The association may be explained by the emotion regulation model (Gross, 1998). Using this model, the experience of a sexual assault can make adaptive emotion regulation difficult (Ehring & Quack, 2010), which may lead an individual to engage in maladaptive emotion regulation techniques, such as eating disorder behaviors.

Overall, results from this study found that nearly 16% of college-enrolled men screened positive for an eating disorder, which is significantly higher than previous studies that found a prevalence rate of between 3 and 5.5% (Eisenberg et al., 2011; Hoerr et al., 2002; Lipson & Sonneville, 2017), and is similar to that of college-enrolled women (9–17%; Eisenberg et al., 2011; Hoerr et al., 2002; Lipson & Sonneville, 2017). Additionally, nearly 4% of college-enrolled men reported they had experienced a sexual assault within the previous 12 months, which is less than previous research looking at both rape and sexual assault other than rape among men (Turchik, 2012; U.S. Department of Justice, 2014). This may be explained by men being less likely to report a sexual assault due to stigma and shame (Turchik & Edwards, 2012; Weiss, 2010), as well as methodological differences.

Throughout the entirety of analyses in this study, sexual minority men had greater odds of screening positive for an eating disorder compared to their straight (heterosexual) peers. These results support previous research findings indicating that sexual minority men are more likely to have body image concerns (Calzo et al., 2013), engage in binge eating (Calzo et al., 2015), purging (Watson et al., 2017), and restrictive (Matthews-Ewald et al., 2014) eating disorder behaviors. Furthermore, Lipson and Sonneville (2017) found that sexual minority college-enrolled men, compared to heterosexual college-enrolled men, had greater odds of screening positive for an eating disorder using the Eating Disorder Examination Questionnaire (EDE-Q).

Similar to experiencing eating disorders, research has shown that lifetime sexual assault victimization is higher among gay and bisexual men compared to heterosexual men (Rothman et al., 2011), and gay and bisexual college men report similar rates of sexual assault as heterosexual women (Ford & Soto-Marquez, 2016). Given the previous research related to eating disorders and sexual assault showing an association among sexual minority men, we investigated the combination of experiencing a sexual assault and sexual orientation on screening positive for an eating disorder. Results indicate that sexual minority college-enrolled men who experienced a sexual assault within the previous 12 month had greater odds of screening positive for an eating disorder. This group also had the highest rate of a positive eating disorder screen in the bivariate analysis. Furthermore, the postestimation analysis indicated that sexual orientation had a greater effect on screening positive for an eating disorder when combined with sexual assault victimization. This is a novel finding given the lack of research investigating the connection between sexual orientation, sexual assault, and eating disorders among the male population.

It is important to note that, compared to non-Hispanic Whites, Hispanic or Latino and Asian or Asian American college-enrolled men had greater odds of screening positive for an eating disorder across all analyses. Overall, research on eating disorders among different racial/ethnic groups is lacking, particularly among male populations (Murray et al., 2017; Ricciardelli et al., 2007). The findings from research investigating weight loss strategies and binge eating across racial/ethnic identities among adolescent boys and adult men have been mixed (Ricciardelli et al., 2007). However, research has shown that Asian American and Hispanic American adolescent boys have been shown to have greater odds of experiencing body dissatisfaction and engaging in more eating disorder behaviors, including chronic dieting, binge eating, and extreme weight control behaviors, compared to White adolescent boys (Croll et al., 2002; Neumark-Sztainer et al., 2002). The greater odds of screening positive for an eating disorder in this study may be due to differences in sociocultural (Ricciardelli et al., 2007) and intersectionl (Beccia et al., 2019) pressures and expectations placed on men of Hispanic or Latino and Asian or Asian American decent. Further investigation of eating disorders among racial/ethnic minority college-age men is needed to more fully understand mechanisms underlying the development of eating disorders among these demographic groups.

College-enrolled men who screened positive for depression and anxiety and reported using illicit drugs in the previous 30 days had greater odds of screening positive for an eating disorder across all analyses. This aligns with previous research that has indicated that men with eating disorders often report comorbid depression (Carlat et al., 1997; Eisenberg et al., 2011), anxiety (Eisenberg et al., 2011), and illicit drug use (Carlat et al., 1997; Pisetsky et al., 2008). Surprisingly, alcohol use did not emerge as significantly associated with screening positive for an eating disorder in the present analysis. This contrasts with previous research revealing a positive relationship between eating disorders and alcohol use among men (Carlat et al., 1997; Pisetsky et al., 2008). The lack of relationship in the present study may be explained by the high rates of alcohol use on college campuses overall, particularly among male students (Schulenberg et al., 2018), which may have influenced the ability to find a significant association, or college-enrolled men with eating disorders may not want to ingest additional calories from alcohol. Interestingly, problematic alcohol use is associated with severe physical and psychological victimization among college men (Sabina et al., 2017) and men who frequent bars are more likely to experience a sexual assault (Tewksbury & Mustaine, 2001).

Implications and Future Research

The results from this study have important implications for mental health practitioners on university campuses. First, compared to previous research, this study found an increased prevalence of positive eating disorder screens among men in this sample. It is important that professionals are trained in assessing and treating men with eating disorders, specifically understanding the nuances between female and male presentations (i.e., muscularity and leanness concerns, exercise use, and weight gain attempts; Murray et al., 2017). Lack of knowledge of these differences may increase the number of men who are undiagnosed and untreated. Second, given that eating disorder behaviors may be used as a maladaptive emotion regulation technique after a sexual assault, and the known difficulty with emotion regulation among individuals who experience eating disorders (Brockmeyer et al., 2012; Carano et al., 2006; Harrison et al., 2009; Harrison et al., 2010; Kessler et al., 2006; Zeeck et al., 2011), it is important that mental health practitioners assist male clients in developing adaptive emotion regulation techniques (i.e., reappraisal, problem solving, and acceptance) as these techniques protect against psychopathology (Aldao et al., 2010). Third, campus prevention and intervention programming aimed at addressing sexual assault and eating disorders should be sensitive and inclusive of men. Effectiveness of sexual assault prevention programs vary and are highly focused on male perpetration of women (Vladutiu et al., 2011). Similarly, research on eating disorder and body image prevention programs on college campuses have primarily focused on women (Yager & O’Dea, 2008). Given the results from this study, it is evident that further development and research on prevention and intervention programming for eating disorders and sexual assault that are inclusive of men is needed. Given our findings, prevention and intervention efforts should consider how sexual orientation, particularly college men who identify as a sexual minority, is uniquely associated with both sexual assault victimization and eating disorder symptoms. Future research should also empirically investigate the psychological mechanisms that connect the experience of a sexual assault and eating disorders among men.

Limitations

Despite the significant findings of this study, there are important limitations to note. First, HMS only captures responses from students who are currently enrolled in higher education. Therefore, individuals who may have dropped out due to a variety of reasons, including an eating disorder or sexual assault, are missed. This may indicate that the estimates in the present study are conservative. Additionally, response rates may not account for students who have experienced a sexual assault or have an eating disorder who do not participate in the survey. The response rate for the 2017–2018 HMS was 23%, which is similar to previous years of this study. While there is a threat of nonresponse bias, we opted not to conduct the analyses using the sampling weights provided with the data set. This decision was made given that, among college students (Fosnacht et al., 2017) and population-level eating disorders participants (Mond et al., 2004), nonresponse has not been shown to produce a significant bias in survey results. Additionally, a high response rate does not necessarily equate to less nonresponses bias (Davern, 2013) and surveys with large sampling frames, such as HMS, are likely to obtain reliable results with lower response rates (Fosnacht et al., 2017). Lastly, this study is primarily focused on the level of association between the independent and dependent variables among this sample of college-enrolled men. Second, while the SCOFF tool is a valid measure for the general population, there is limited knowledge on its validity in screening men for eating disorders (Kutz et al., 2020). Additionally, the SCOFF tool does not specify a time frame of which eating disorder behaviors occur, thus it is unclear whether a positive screen occurs prior to or after the experience of sexual assault. Similarly, our analysis was not able to capture whether participants had experienced prior childhood sexual abuse, which is a risk factor for the development of an eating disorder among men in adulthood (Afifi et al., 2017), nor were we able to account for the gender or sex of the perpetrator. These limitations present important areas of future investigation. Lastly, HMS and this analysis is cross-sectionl from only one year, which limits any causal inference.

Conclusion

This study explored whether experiencing a sexual assault is associated with screening positive for an eating disorder among college-enrolled men. Results indicated that experiencing a sexual assault significantly increases the odds of screening positive for an eating disorder, which confirms the study’s hypothesis. This finding was particularly strong among sexual minority men who have also experienced a sexual assault. Results also indicated that positive eating disorder screens among college-enrolled men were higher, while sexual assault rates were lower, compared to previous studies. These results fill a gap in the current knowledge base on eating disorders and sexual assault among the male population and provide important implications for university mental health practitioners.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Kyle T. Ganson

Author Biographies

Kyle T. Ganson, PhD, MSW, is an assistant professor at the Factor-Inwentash Faculty of Social Work at the University of Toronto. His research primarily focuses on the etiology, prevention, and intervention of eating disorders among the male population. He is particularly interested in how the intersection of policy and research can impact clinical practice. Kyle is also a licensed clinical social worker.

Rachel F. Rodgers, PhD, is an associate professor in the Department of Applied Psychology at Northeastern University, Boston. Her research interests are in the area of body image, disordered eating and adolescent/young adult psychopathology, in particular focusing on sociocultural influences on body image and eating concerns.

Sarah K. Lipson, PhD, EdM, is an assistant professor in the Department of Health Law Policy and Management at the Boston University School of Public Health. She is also co-Principal Investigator of the national Healthy Minds Study, an annual survey of undergraduate and graduate student mental health and related factors.

Tamara J. Cadet, PhD, LICSW, MPH, is a faculty member at Simmons University School of Social Work and also holds a faculty appointment at the Harvard School of Dental Medicine. Her research interests include evidence-based health promotion interventions among vulnerable populations.

Michelle Putnam, PhD, is a professor at Simmons University School of Social Work in Boston, Massachusetts. Dr Putnam holds a bachelor’s degree in history from the University of Michigan, Ann Arbor, a Masters in Gerontological Studies from Miami University in Oxford, Ohio, and a doctorate in Social Welfare from the Luskin School of Public Affairs at the University of California, Los Angeles.

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