Eating Disorder Treatment Access in the United States: Perceived Inequities Among Treatment Seekers

Eating disorders are psychiatric illnesses characterized by severe impairment, elevated mortality and relapse rates, and high rates of co-occurrence with other psychiatric disorders (e.g., anxiety, substance use, and trauma) (1–4). Eating disorders have a lifetime prevalence rate of 9%–13% in the U.S. population and an estimated lifetime economic and well-being cost of >$326.5 billion, making eating disorders a serious threat to public health (4, 5). Despite the high prevalence rates, substantial costs to society, and significant health problems associated with eating disorders, most individuals with these disorders (80%) never access treatment (6). Efforts to improve access to treatment for these serious illnesses are urgently needed.

Barriers to Treatment Access for Eating Disorders

Among the barriers to treatment access (BTAs) for eating disorders in the United States, treatment costs—averaging approximately $20,817 per eating disorder inpatient stay (7, 8)—represent a major hurdle to accessing treatment (9, 10). The cost of treatment may be unaffordable for most families given that the national median household income is $67,521, and even individuals with insurance coverage report difficulty accessing care (11). Other common BTAs include geographic, identification, sociocultural, and treatment quality barriers.

Geographic barriers include the inability to access care in many rural and underresourced locations; many patients in the United States must travel out of state for higher levels of care (12). Identification barriers include underdiagnosis of eating disorders because providers in nonspecialty care lack training in eating disorder assessment (13). Only for 20% of those with an eating disorder seen by outpatient providers (e.g., primary care physicians) the disorder is detected and accurately diagnosed (14). Individuals with marginalized identities are much less likely to receive an eating disorder diagnosis and subsequent treatment (9, 15–21).

Sociocultural BTAs include cultural (e.g., stigma) (6, 10, 20, 22) and personal (e.g., attitudes) (6, 10) factors. Because of harmful racial-ethnic, gender, and socioeconomic biases and misperceptions regarding eating disorders, individuals from racial-ethnic minority groups, men, and those with lower income and educational attainment are less likely to receive eating disorder treatment (23–26). In addition, many individuals with eating disorders do not seek treatment because they do not believe that they are “sick enough” or they hold other personal attitudes that preclude access to care (6). Finally, barriers related to treatment quality include lack of access to inclusive (e.g., gender-affirming), culturally sensitive, evidence-based, transdiagnostic, and integrative (i.e., coordinated) treatment. Each of these issues may prevent individuals from seeking and returning for eating disorder treatment.

The Present Study

To our knowledge, no comprehensive nationwide survey of BTAs among a heterogeneous sample of treatment seekers with self-reported eating disorders and both with and without lifetime access to eating disorder treatment has been conducted in the United States. The aim of this study was to examine eating disorder treatment access by comprehensively assessing BTAs, providing initial estimates of BTAs in the United States among those attempting to access treatment, comparing BTAs across different demographic characteristics, and examining the association between BTAs and eating disorder symptomatology.

We hypothesized that most participants would report multiple lifetime treatment barriers; that financial barriers would be the most frequently reported treatment barrier; that individuals with marginalized identities would report elevated BTAs; and that, across BTAs, higher frequencies of reported treatment barriers would be associated with higher levels of eating disorder symptomatology.

Methods

Participants

We recruited individuals to participate in an anonymous online survey through social media advertisements (e.g., Instagram, Twitter, Facebook, and laboratory and nonprofit websites) between January 2021 and June 2022. Study advertisement materials and an unsigned consent form (i.e., preamble) at the beginning of the survey invited individuals ages ≥18 years living in the United States with a self-reported eating disorder and who had attempted to access treatment to complete the survey on behalf of themselves or a minor in their care. All study procedures were approved by the University of Louisville Institutional Review Board. The study was preregistered on Open Science Framework (https://doi.org/10.17605/OSF.IO/9FN5T).

BTA Measures

To assess BTAs, three study authors (S.P.B, R.E., C.A.L.) designed a 109-item self-report instrument, informed by a comprehensive literature search and drawn from our experiences as the chief executive officer of an eating disorder nonprofit organization (R.E.), the director of an eating disorder clinic (C.A.L.), and eating disorder treatment providers (R.E., C.A.L.). The survey assessed respondents’ demographic information, clinical characteristics, treatment barriers, treatment history, and treatment experiences. We used five domains to assess BTAs: financial barriers (14 items), identification barriers (four items), treatment quality barriers (six items), sociocultural barriers (three items), and geographic barriers (two items). We analyzed barriers both at the item level and by using domain totals. (See the online supplement to this article for an explanation of how these categories map onto standard public health frameworks [27] and for a copy of the survey.)

Eating Disorder Symptoms

We assessed eating disorder symptoms and behaviors with nine items from the Eating Disorder Examination Questionnaire, version 6 (EDE-Q) (28), which has demonstrated excellent factor validity, internal consistency, test-retest reliability, convergent validity, and discriminant validity (29, 30). Items selected represent items from the original four EDE-Q subscales (i.e., eating concerns, shape concerns, weight concerns, and restraint) along with the four questions about the frequency of eating disorder behavior. Items were selected before publication of validated EDE-Q short forms.

For this study, we calculated an approximate EDE-Q global score by averaging responses to the following five items assessing symptoms over the past 28 days: “Have you been deliberately trying to limit the amount of food you eat to influence your shape or weight (whether or not you have succeeded)”? “Have you gone long periods of time (8 waking hours or more) without eating anything at all in order to influence your shape or weight”? “Has thinking about food, eating, or calories made it very difficult to concentrate on things you are interested in (for example, working, following a conversation, or reading)”? “Have you had a definite fear that you might gain weight”? and “Has your weight or shape influenced how you think about (judge) yourself as a person”? For descriptive purposes, we assessed behavior use in the past 28 days, including binge eating, loss-of-control eating, self-induced vomiting, and compulsive exercise. Internal consistency in this sample was good (ω_t=0.86).

Data Analysis

For analyses, BTAs were conceptualized in two different ways: first, we calculated each treatment barrier (i.e., category) by adding the total number of items endorsed within each domain to yield a total score (i.e., frequency). Second, we dichotomized each treatment barrier into “not endorsed” (i.e., item total=0) and “endorsed” (i.e., item total ≥1).

We used independent-samples t tests and one-factor, between-subject analyses of variance (ANOVAs) to examine whether significant differences in overall reported barriers existed across demographic characteristics (i.e., sexual orientation, race and ethnicity, gender, education level, employment status, yearly household income, disability status, urbanicity, or primary self-reported eating disorder diagnosis).

We conducted Pearson chi-square tests to detect possible systematic differences in the likelihood to endorse individual treatment barriers on the basis of demographic characteristics. Comparisons were conducted between heterosexual and sexual minority participants and among White participants; American Indian, Native Alaska, Native Hawaiian, or Pacific Islander participants (which we combined into one category for analyses); Asian or South Asian participants; Black/African American participants; and participants who reported multiple races. We conducted comparisons between transgender or nonbinary participants and cisgender participants and between cisgender women and cisgender men. We conducted comparisons among those with a high school education (i.e., those with some high school or a high school diploma), postsecondary education (i.e., some college, an associate degree, or a bachelor’s degree), master’s degree, or doctoral degree and among those who reported that they were employed full-time, part-time, or unemployed. Finally, we conducted comparisons between those with a household income ≤$70,000 and those with a household income >$70,000. Because of the number of comparisons, we used Bonferroni corrections to adjust for potential familywise error, with alpha set at 0.05 (31).

We used independent-samples t tests to examine whether endorsement of overall and individual BTAs was associated with age at eating disorder onset, age at eating disorder diagnosis, eating disorder treatment delay, eating disorder symptoms, or body mass index (BMI). Finally, we used Pearson correlations to examine the relationship between total number of barrier items reported and eating disorder symptoms. Statistical analyses were performed with SPSS, version 28 (32).

Results

Sample Selection and Characteristics

The data set contained 2,238 respondents. Of those, 243 (11%) were excluded from the analyses because they met any of the following criteria: failing traffic light validation checks (N=53; see the online supplement), submitting duplicate responses based on contact information supplied (i.e., e-mail; N=47), having an international zip code (N=35), being <18 years old (N=73), responding on behalf of someone else (N=19), or not responding to any BTA items (N=16) (see the online supplement). The final sample consisted of 1,995 participants. Demographic and clinical characteristics of the study participants are shown in Tables 1 and 2. (See the online supplement for the results including participants who responded on behalf of someone else.)

BTA Characteristics

BTA endorsement rates and total scores are provided in Table 3. Participants endorsed a mean±SD of 3.0±1.3 barrier domains and 8.7±5.4 barrier items. Of the sample, 96% (N=1,923) endorsed at least one barrier. Financial barriers were the most frequently endorsed barrier, followed by disorder identification, sociocultural, treatment quality, and geographic barriers.

Associations of Disparities in BTAs With Demographic Characteristics

The mean number of BTAs reported varied by sexual orientation, gender, employment status, household income, disability status, and eating disorder diagnosis. Sexual minority participants reported significantly more BTAs than did heterosexual participants (p<0.001). Nonbinary participants reported significantly more BTAs than did cisgender women or cisgender men (p<0.05 for both). Unemployed participants reported significantly more BTAs compared with participants employed full-time (p<0.001) or part-time (p<0.05). Participants with a household income ≤$70,000 reported significantly more BTAs than did those with a household income >$70,000 (p<0.001). Participants who reported a disability reported significantly more BTAs compared with those who did not report a disability (p<0.001). Participants with anorexia nervosa reported significantly more barriers than those with binge eating disorder (BED; p<0.001), avoidant/restrictive food intake disorder (ARFID; p<0.05), or participants who had recovered (p<0.001). Participants with bulimia nervosa reported significantly more BTAs than those with BED (p<0.05), ARFID (p<0.05), or recovered participants (p<0.001). Participants with other specified feeding or eating disorder (OSFED) reported significantly more BTAs than did those with BED (p<0.001), ARFID (p<0.001), or recovered participants (p<0.001). No significant differences were detected for race, ethnicity, education level, or urbanicity. (The t test and ANOVA results are shown in the online supplement.)

Additional BTA Findings

Results from the chi-square analyses of differences in BTA endorsements across demographic characteristics are shown in the online supplement. Results from the independent-samples t test analyses of BTAs, eating disorder symptoms, illness trajectory, and BMI are shown in Table 4. The total number of BTAs was positively associated with the approximated EDE-Q global score (r=0.22, p<0.001).

Discussion

We found that individuals who sought treatment for eating disorders endorsed at least three BTA domains and that participants with marginalized identities or an OSFED diagnosis reported the greatest inequities in accessing treatment for these disorders. Financial barriers were most frequently endorsed, compared with the other BTA categories. Given the increasing prevalence of these impairing and life-threatening disorders, it is important to increase access to eating disorder treatment. These data shed light on why only 20% of individuals with eating disorders in the United States access lifesaving care and pinpoint specific inequities that need improvement to increase access to eating disorder treatments.

Participants with marginalized identities were more likely to endorse barriers related to treatment quality and sociocultural factors than those with historically represented identities. This finding is consistent with those of earlier literature (23–26) highlighting that stigma and attitudes about treatment disproportionally affect individuals with marginalized identities. We also found that participants in rural areas, those who reported a household income ≤$70,000, and those with anorexia nervosa, bulimia nervosa, or OSFED were more likely to report geographic barriers than those in suburban or urban areas, those with a household income >$70,000, and those with BED or who reported having recovered, respectively. Most individuals must travel out of state to receive specialty eating disorder treatment (12), consistent with the fact that those in rural areas and those reporting a household income ≤$70,000 may experience geographic barriers. In addition, participants with anorexia nervosa, bulimia nervosa, or OSFED may be more likely to be referred to a higher level of care, which may require long-distance travel.

We found that participants who were more likely to report any of the BTAs reported more severe eating disorder symptoms. We also found that those who were more likely to report barriers due to disorder identification and sociocultural factors reported longer delays in treatment, lower age at eating disorder onset, higher BMI, and more eating disorder symptoms. Because stigma can affect the identification of eating disorders among those with marginalized identities (23–26), these findings support the observation that individuals with these identities experience longer treatment delays and report more eating disorder symptoms. Relatedly, participants who were more likely to report BTAs related to treatment quality reported less delay in treatment and lower age at receiving a diagnosis of eating disorder. Finally, we found that those who reported higher rates of lifetime treatment barriers had elevated eating disorder symptoms.

Evidence of treatment disparities may be explained by unique and compounded structural barriers faced by individuals with marginalized identities (33). For example, individuals with a sexual minority identity might experience both identification (e.g., delay in diagnosis) and sociocultural (e.g., stigmatizing medical experiences) barriers. Moreover, our results suggest that those experiencing multiple barriers may be not only less likely to access treatment but also more likely to experience elevated eating disorder pathology, which could lead to higher chronicity and vulnerability to relapse (34, 35).

Treatment inequities among individuals with eating disorder diagnoses could be related to real or perceived differences in severity among disorders. Individuals with some eating disorders may experience specific financial and geographic barriers. Evidence suggests that those who receive an eating disorder diagnosis on the basis of being underweight are likely to be referred for intensive eating disorder treatment (36), such as, for example, individuals with anorexia nervosa, who may need to travel out of state for acute medical stabilization. In contrast, individuals with bulimia nervosa, BED, or OSFED may be admitted to outpatient care, which is more accessible. However, individuals with bulimia nervosa, BED, or OSFED may be more likely to experience sociocultural barriers because of providers’ weight bias or because of the misconception that they are not “sick enough” compared with those with anorexia nervosa (6).

Clinicians and treatment centers should continue to advocate for and negotiate with insurance companies for affordable reimbursement rates to help alleviate financial barriers. Medical and mental health providers need to be trained on detecting eating disorders and conducting evidence-based, culturally competent screenings (e.g., with the SCOFF questionnaire) (37). Such training activities could help decrease potential provider biases and increase identification of eating disorders in outpatient settings, where most individuals with eating disorders are initially seen (14). In addition, state-specific referral resources should be created and maintained so that nonspecialty providers can easily refer their patients to specialists. Establishing legislative groups, such as the Kentucky or Missouri Eating Disorder Council, could be helpful for implementation of statewide advocacy, educational materials, and resources. To help alleviate treatment quality barriers, treatment centers should expand group materials to include diverse examples and activities (e.g., manuals should be inclusive of race, ethnicity, gender identity, sexuality, religious affiliation, and diverse cultures). Efforts to reduce weight stigma in health care may help alleviate BTAs related to disorder identification, sociocultural factors, and treatment quality, especially for individuals with larger bodies. Finally, to reduce geographic barriers, treatment centers could provide financial aid to those who need to travel out of state.

Some limitations of this study should be considered. We did not use epidemiological methods, so we could not estimate prevalence rates of BTAs. Participants self-reported their eating disorder and co-occurring diagnoses, precluding generalizability to populations with clinical eating disorders because of potential errors in self-reported diagnoses. Moreover, generalizability of the current findings may be limited to individuals who seek treatment in their lifetime, including those who suspect that they have an eating disorder. Indeed, findings from a comprehensive review of the literature (10) suggest several barriers to treatment before help seeking (e.g., failure to recognize one’s eating disorder or its seriousness and lack of awareness of treatment resources) that were not captured in the present study. In addition, we approximated the EDE-Q global score with an unvalidated subset of items from the EDE-Q, selected by using clinical judgment (by R.E. and C.A.L.) at the expense of psychometric strength. Therefore, interpretation of the findings regarding the relationships between BTAs and eating disorder symptoms should be interpreted with caution. Finally, participants who provided a response on behalf of someone else were removed from the analyses because of potential sample differences. Future research should examine potential differences in barriers between individuals who self-report BTAs and those who are collateral reporters to characterize access to eating disorder treatment from the perspective of caregivers and social support networks.

The strengths of the study included a low burden on participants due to the short duration of the survey, large sample size and diversity, data integrity, and the assessment of treatment experiences alongside systemic barriers to access. The study included responses across all 50 U.S. states and Puerto Rico.

Conclusions

To our knowledge, this study is the most comprehensive report to date on perceived barriers to eating disorder treatment access among individuals seeking treatment in the United States. The results highlight that barriers to eating disorder treatment access are pervasive and that treatment inequities affect individuals from various treatment-seeking stages and with different demographic characteristics and self-reported diagnoses. Of note, this study included individuals who suspected that they had an eating disorder (with or without receiving a diagnosis) and reported efforts to seek care. Although lack of recognition of an eating disorder or of motivation to seek treatment often delays or precludes seeking of eating disorder treatment, it is critical to attend to barriers that arise once an individual decides to pursue treatment. Our results reflect a severe system-level failure to meet the needs of individuals who report a desire and commitment to seek help. Given evidence suggesting that historically underrepresented groups are disproportionately excluded from eating disorder treatment, public health efforts to eliminate structural barriers to eating disorder treatment should prioritize equity and inclusion. Removing structural barriers to eating disorder treatment may lead to increased treatment seeking, decreased chronicity, and, ultimately, attenuation of the personal and societal burden accrued by these disorders.