Abstract
Weight stigma is persistent across contexts and is associated with disordered eating cognitions and behaviors. This systematic review aimed to examine the existing literature that has explored the relationship between weight stigma and disordered eating cognitions and behaviors. We specifically examined three dimensions of weight stigma – experienced, anticipated, and internalized – and adopted an inclusive conceptualization of outcomes related to disordered eating (including constructs such as binge eating, body dissatisfaction, and other cognitions and behaviors such as dietary restraint, unhealthy weight control behaviors, and drive for thinness). We searched PubMed, Embase, CINAHL, Web of Science, Sociological Abstracts, and PsycINFO for English-language, peer-reviewed articles and dissertations with quantitative methodology published through October 2023. The search resulted in 242 articles meeting inclusion criteria. A narrative review found a consistent relationship between greater weight stigma and more disordered eating cognitions and behaviors. Methodological and theoretical limitations are discussed, as are critical avenues for future research and potential clinical implications stemming from this body of research. Given the widespread nature and impact of weight stigma on disordered eating, it is imperative that we intervene to address weight stigma at all levels, from the structural to the intrapersonal.
1. Introduction
Disordered eating is both pervasive and escalating. Using broad screening criteria, 19.4 % of women and 13.8% of men globally meet the criteria for an eating disorder (Galmiche et al., 2019). Disordered eating is particularly common among adolescents and young adults. In a recent systematic review and meta-analysis across 16 countries, over 22% of children and adolescents screened positive on the Sick, Control, One stone, Fat, Food questionnaire (SCOFF; Morgan et al., 1999) for a probable eating disorder (Lopez-Gil et al., 2023). This prevalence was higher among girls (~30%) compared to boys (~17%) and increased with body weight. Similar rates of disordered eating behaviors have been found among high school students in the United States (Beccia, et al., 2019) and university students globally (Alhaj et al., 2022). Importantly, these figures often overlook disordered eating behaviors that fall below clinical thresholds but are nonetheless harmful (Stice et al., 2009, Stice et al., 2010). Likewise, these figures often fail to capture related cognitions such as drive for thinness and poorer body image that are incredibly common (Fitzsimmons-Craft et al., 2012; Wang et al., 2020) and potent risk factors for the development of eating disorders (Stice et al., 2011). The impact of eating disorders on wellbeing cannot be understated. Indeed, they are associated with comorbidity with other forms of psychopathology, such as increased anxiety, depression, and obsessive-compulsive symptoms (Berkman et al., 2007; Van Alsten & Duncan, 2020), physical health problems, such as anemia, and osteoporosis (Udo & Grilo, 2019), and premature mortality (Deloitte Access Economics, 2020; Smink et al., 2012). Beyond this immense personal toll, eating disorders are estimated to result in an annual economic cost of $64.7 billion in the United States alone (Deloitte Access Economics, 2020).
Considering the pervasiveness and impact of disordered eating, it is crucial to identify potentially modifiable risk factors that give rise to and perpetuate it. One factor that has received increasing scholarly attention over the past two decades is weight stigma (e.g., Vartanian & Porter, 2016; Mason et al., 2020). Contemporary theorizing on the consequences of weight stigma (at the individual level) often considers three components of stigma: experienced, anticipated, and internalized (e.g., Major, et al., 2018). Weight stigma can be directly experienced, such as when individuals are devalued, rejected, or discriminated against because of their weight. Individuals often come to anticipate these negative weight-related experiences, stemming both from past discrimination (e.g., Hunger et al., 2020) as well as exposure to cues or messages that signal the potential weight-based mistreatment (e.g., Major et al., 2020). Weight stigma can also be internalized, where individuals come to agree with and self-direct the negative stereotypes, prejudice, and mistreatment they face (Pearl et al., 2023). Each component of weight stigma is common. Over 40% of US adults individuals report experiencing and anticipating weight stigma (Lee et al., 2021), and 24% report high levels of internalized weight stigma (Prunty et al., 2020), and these figures increase with an individual’s weight. Each component of weight stigma has been linked to an array of outcomes related to disordered eating. For example, experiencing weight-based discrimination is associated with disordered eating behaviors (e.g., restrained eating; Hübner et al., 2016) as well as related risk factors such as drive for thinness (e.g., Gallardo et al., 2020; Vartanian & Novak, 2011) and poorer body image (e.g., Gan et al., 2012). Internalized weight stigma is likewise related to binge eating (e.g., Boswell & White, 2015; Puhl & Himmelstein, 2018), disinhibited eating (e.g., Soulliard et al., 2021a), and weight concern (e.g., Almenara et al., 2017). Anticipated weight stigma has received the least empirical attention, but is nonetheless associated with disordered eating intentions (Major et al., 2020) and behaviors (Lee, et al., 2021; Hunger et al., 2020), as well as binge eating (e.g., Palmeira et al., 2018).
The present work builds from related reviews in this domain, yet extends them in important ways. Vartanian and Porter (2016) provided a foundational review of how weight stigma is associated with disordered eating outcomes. Indeed, this article can be credited with motivating a considerable amount of research in the years since its publication, which has warranted the need for further reviews of the literature. Emmer, Bosnjak, and Mata (2020) did so as part of a larger meta-analysis on the relationship between weight stigma and mental health. Although they offer critical quantitative data on this relationship, the broader aim of the research necessitated less precision in search parameters related to disordered eating behaviors and cognitions, in favor of more global terms (e.g., mental health). As a result, articles such as Jendrzyca and Warschburger (2016) and Womble et al. (2001) were not captured by their search. Emmer and colleagues’(2020) review also did not include anticipated stigma as part of its search, overlooking a crucial component of weight stigma (Hunger, at al., 2015; Major et al., 2018). Mason, Mozdzierz, Wang, and Smith (2020) also touched on the issue of weight stigma and disordered eating in their meta-analysis examining the relationship between discrimination and eating disorder psychopathology. In contrast to Emmer et al. (2020), the review by Mason and colleagues had very thorough search parameters for disordered eating and related outcomes. However, their review was limited specifically to discrimination experiences, again overlooking important dimensions of weight stigma (i.e., anticipation and internalization). Finally, Zhu, Smith, and Buteau (2022) conducted a meta-analysis on weight stigma and health behaviors. Although their theoretical framework considered the three dimensions of weight stigma outlined above, the search parameters did not explicitly include terms (e.g., discrimination, bullying) often used in the literature that fall under the umbrella of stigma. Likewise, given the broad nature of the search terms related to health behaviors, this review failed to capture numerous articles relevant to weight stigma and disordered eating, including those captured by earlier reviews (e.g., Eisenberg et al., 2012; Farrow & Tarrant, 2009).
Each of the previous reviews represent an important contribution to the field. However, as outlined above, they also have limitations that warrant the need for a systematic review designed to capture each dimension of weight stigma and a fuller array of outcomes related to disordered eating. Here we provide the most updated and comprehensive systematic review of the literature examining the association between weight stigma and disordered eating cognitions and behaviors. We opted to conduct a systematic review rather than a meta-analysis for a few reasons. First, our theoretically-derived search terms were purposefully more comprehensive than the previous reviews described above. As such, the present review was designed to serve more of an exploratory function, with one goal being the identification of areas of pressing research need within the weight stigma and disordered eating literature. At the same time, we expected that this inclusive search approach would yield considerable heterogeneity in sample characteristics (e.g., developmental period, clinical or non-clinical) and operationalization of both weight stigma and disordered eating-related phenomena, the former often using measures that have not undergone thorough psychometric evaluation. This heterogeneity and limited use of well-validated weight stigma measures raised concerns about the appropriateness of meta-analysis in this particular context (Cooper et al., 2019), leading to our decision to instead conduct a rigorous systematic review. Through this review, we hope to spur further theoretical, empirical, and applied work on the topic, points we return to in the general discussion.
2. Methods
This systemic review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and was registered on PROSPERO (ID: CRD42021254545).
2.1. Search Strategy
The review sought to identify English language quantitative studies reporting a relationship or association between a measure or conceptualization of disordered eating and a measure or conceptualization of weight stigma, bias, or discrimination. Published journal articles as well as articles in press and theses and dissertations were included. The following databases were initially searched in July 2021, and again in May 2023 and October 2023: PubMed/MEDLINE, Embase, CINAHL via the EBSCO platform, Web of Science Core Collection, and PsycINFO and Sociological Abstracts via the ProQuest platform. Search concepts included a variety of keywords to describe weight stigma and eating disorders. MeSH terms, Emtree terms, and other controlled vocabulary terms were incorporated into the search strategies. Full search strategies for each database can be found in Supplementary Material. In-press studies were also identified via professional listservs.
2.2. Inclusion and Exclusion Criteria
To be included, articles needed to be available in English, be a quantitative study design, and be in one of the following formats: peer reviewed academic article, dissertation or thesis, peer reviewed conference proceedings and clinical trials, or paper in press retrieved from professional listservs and personal communication. The article must also have reported a relationship or association between a measure or conceptualization of disordered eating and a measure or conceptualization of weight stigma, bias, or discrimination in main article or supplementary materials. Articles could have been published at any time and included human participants of any age. Articles were excluded if an English version could not be located, the study included non-human participants, the study reported only on a global discrimination measure and not a weight-specific one, the study used qualitative methods only, if there was no measurement of weight stigma or a target outcome, or if the only available information from conference proceedings was an abstract.1
2.3. Study Selection
Search results were exported to a reference manager and duplicates were removed. The first and second authors screened titles and abstracts. Both reviewers independently screened the same randomly selected 20% (804) of the initial search results, and Cohen’s Kappa was calculated to determine coding agreement for inclusion and exclusion (Cohen’s K = .68; substantial agreement according to Landis & Koch, 1977). Then, the remaining 80% of results were screened separately between the two. Both reviewers independently screened the full text of all publications included at the title and abstract stage. Disagreements on inclusion or exclusion of articles were resolved by the senior author. For the second and third rounds of searches, the first and second authors independently screened articles at all stages.
2.4. Data Extraction
The research team decided on demographic, methodological, and results data to be extracted from each article. Each junior author extracted data from half of the final sample of articles, and then conducted an accuracy check on the data extracted from the other half of the final sample of articles. The primary outcome of interest was any data regarding relationships between weight stigma and disordered eating behaviors and cognitions. Additional variables were also extracted: sample size, study year, and participant demographics including gender, race, weight, age, sexual identity, BMI, and disordered eating treatment status.
2.5. Quality Assessment
The NHLBI Study Quality Assessment Tools were used to assess the internal validity of included studies. The two junior authors completed the checklist for each article and agreed on a rating of Poor, Fair, or Good. Disagreements were resolved by the senior author.
3. Results
3.1. Study Selection
Two hundred and forty-two articles met inclusion criteria for this systematic review. Of these studies, 194 (80.2%) had a cross-sectional design, 44 (18.2%) had a longitudinal design, 2 (0.08%) had an experimental design, and 1 (0.4%) had a combination of designs. See PRISMA diagram for flow of article inclusion and exclusion.
3.2. Study Characteristics
3.2.1. Demographics
In terms of the gender composition of samples, 72 (29.8%) articles had samples that were 100% female, 50 (20.7%) articles had samples that were over 75% female, and 89 (36.8%) articles had samples that were over 50% female (but less than 75%). In terms of racial/ethnic composition of samples, 63 (26.0%) articles had samples that were over 75% White and 35 articles (14.5%) had samples that are over 50% White (but less than 75%). See Table 1 for demographic information of all studies. Regarding sample age groups, 150 (61.9%) studies were conducted with adult samples and 88 (36.4%) studies were conducted with child and/or adolescent samples, with the remaining studies using a combination of age groups. Some longitudinal studies surveyed adolescents at baseline and conducted a follow up during adulthood. Only 14 (5.8%) studies were conducted with clinical samples, namely, participants who were actively seeking or involved in treatment for disordered eating.
Table 1.
Demographic qualities of included studies
| Author(s) (year) | Age | Population | Country | Race/Ethnicitya,b | Sex/Gendera,c | |
|---|---|---|---|---|---|---|
| Adult samples | ||||||
| Nonclinical | ||||||
| Akan & Grilo (1995) | Adults | Nonclinical | United States | 36.7% 34.7% 28.6% |
African American Asian American Caucasian |
100% female |
| Almeida et al. (2011) | Adults | Nonclinical | United States | 48.0% 38.0% 4.0% 9.0% 50.0% 20.0% 16.0% 14.0% |
Sample 1 Black/African American Latino/a or Hispanic Asian/Other White/Caucasian Sample 2 Asian/Other White/Caucasian Black/African American Latino/a or Hispanic |
Sample 1 94% female Sample 2 77% female |
| Almenara et al. (2017) | Adults | Nonclinical | Canada | 100% | Canadian | 100% women |
| Annis et al. (2004). | Adults | Nonclinical | United States | 70.0% 20.0% 6.0% 2.0% 2.0% |
European American African American Asian Hispanic Other/Unspecified |
100% women |
| Austen et al. (2020) – Study 1 | Adults | Nonclinical | United States United Kingdom Australia Canada |
79.2% 6.0% 3.5% 2.5% 6.6% |
White Asian Black Hispanic, Asian, or Spanish Multiracial |
100% men |
| Austen et al. (2020) – Study 2 | Adults | Nonclinical | United States United Kingdom Australia Canada |
64.2% 9.0% 8.2% 6.3% 7.7% |
White Hispanic, Latino, or Spanish Black Asian Multiracial |
100% men |
| Bannon et al. (2018) | Adults | Nonclinical | United States | 49.0% 29.6% 8.1% 5.7% 6.8% |
Caucasian Asian Hispanic African American Other |
55.3% women 44.7% men |
| Bardone-Cone et al. (2008) | Adults | Nonclinical | United States | 87.0% 5.0% 3.0% 5.0% 88.0% 5.0% 1.0% 2.0% 3.0% |
Males Caucasian African American Asian Biracial/other Females Caucasian African American Hispanic Asian Biracial/other |
68% female 32% male |
| Becker et al. (2021) | Adults | Nonclinical | United States | 65.0% 16.5% 11.3% |
Hispanic/Latinx Black/African American nonHispanic White/Caucasian |
76.5% female 23.5% male |
| Benas (2009) | Adults | Nonclinical | United States | 63.0% 14.0% 11.0% 6.0% 6.0% |
Caucasian Asian African American Hispanic Other |
100% women |
| Benas & Gibb (2008) | Adults | Nonclinical | United States | 53.7% 27.6% 8.9% 3.9% 5.4% |
Caucasian Asian Hispanic African American Other |
64% female |
| Bennett et al. (2022) | Adults | Nonclinical | United States | 30.1% 19.4% 15.8% 7.5% 5.4% 5.4% 2.9% 2.5% 1.4% 0.4% 8.2% 16.8% |
White/Caucasian Filipino Japanese Chinese Korean Native Hawaiian Vietnamese Pacific Islander Black or African American Asian Indian Not listed Hispanic, Latino/a, or Spanish origin |
100% female |
| Berman (2006) | Adults | Nonclinical | Canada | NR |
Community sample 82% female College sample 64% female |
|
| Bidopia et al. (2023) | Adults | Nonclinical | United States | 49.0% 15.5% 14.9% 0.09% 0.14% 10.6% 5.0% 1.2% 0.1% 0.3% |
White Black Asian American Indian/Alaska Native Native Hawaiian/Pacific Islander Hispanic Multiracial Middle Eastern or North African West Indian Other |
80.88% Female 18.88% Male 0.20% Other 0.05% Prefer not to say |
| Bidstrup et al. (2022) | Adults | Nonclinical | Australia | NR | 73.6% female | |
| Boswell & White (2015) | Adults | Nonclinical | United States | NR | 85.4% women 14.6% men |
|
| Burnette & Mazzeo (2020) | Adults | Nonclinical | United States | 45.50% 20.49% 5.32% 16.80% 11.89% 39.7% 19.93% 6.75% 20.26% 0.02% 13.18% |
Men White Black Latinx Asian/Hawaiian/Pacific Islander Multiracial Women White Black Latinx Asian/Hawaiian/Pacific Islander Native American Multiracial |
71.35% female 28.65% male |
| Carels et al. (2019) | Adults | Nonclinical | United States | 59.0% 32.0% 3.0 |
European American African American Asian/Pacific Islander |
85% female |
| Chen et al. (2023) | Adults | Nonclinical | China | 100% | Chinese | 76.2% female 23.8% male |
| Cheng et al. (2018) | Adults | Nonclinical | China | 100% | Han | 43.8% male |
| Christian et al. (2023) | Adults | Nonclinical | United States | 69.2% 14.0% 5.1% 4.5% 3.7% 1.8% 0.6% |
non-Hispanic White non-Hispanic Black Multiracial or biracial Asian or Asian-American Hispanic Other/Not listed American Indian or Alaska Native |
76.4% cisgender woman 22.9% cisgender man 0.5% non-binary 0.1% transgender woman 0.1% transgender man |
| Cohen (1998) | Adults | Nonclinical | United States | 89.9% 3.6% 1.9% 1.9% 1.9% |
White Native American African American Asian Hispanic |
100% women |
| Concepcion (2008) | Adults | Nonclinical | United States | 82.3% 5.0% 4.2% 2.0% |
Caucasian Hispanic Multi-Ethnic American Indian, Asian, or African American |
73% women |
| DeFeciani (2011) | Adults | Nonclinical | United States | 57.9% 19.0% 13.5% 7.9% |
White Black/African American Hispanic Asian |
100% male |
| de Macêdo, et al. (2023a) | Adults | Nonclinical | Brazil | 51.0% 49.0% |
White Non-White |
76.0% women 24.0% |
| de Macêdo et al. (2023b) | Adults | Nonclinical | Brazil | 52.7% 30.2% 13.5% 1.6% 0.2% 1.6% |
White Brown Black Yellow Indigenous Rather not say |
76.6% female 22.9% male |
| Donahue et al. (2022) | Adults | Nonclinical | United States | 90% | Non-Hispanic White | 75% female |
| Douglas (2020) | Adults | Nonclinical | United States | 86.7% 4.4% 4.4% 2.2% 2.2% 2.2% 95.6% 2.2% |
White or Caucasian Asian Black or African American American Indian or Alaskan Native Hawaiian or other Pacific Islander Hispanic nonHispanic NR |
73.4% women 22.6% men |
| Douglas & Varnado-Sullivan (2016) | Adults | Nonclinical | United States | 70.2% 11.5% 1.9% 3.8% 12.5% |
Caucasian African American Hispanic Asian or Pacific Islander Other |
15.38% males 72.11% females 12.5% did not report |
| Douglas et al. (2021) | Adults | Nonclinical | United States | 91% 4.5% 3.2% 2.6% 0.6% 0.6% |
White or Caucasian Asian Black or African American Hispanic Native Hawaiian or Pacific Islander American Indian or Alaskan Native |
74.4% women 25.6% men |
| Durso & Latner (2008) | Adults | Nonclinical | United States Canada United Kingdom Norway India New Zealand |
75.4% 14.7% 3.7% 3.7% 2.1% 0.5% |
White African American Biracial/Mixed Race Hispanic Asian American Native American |
82,8% women 17.2% men |
| Durso et al. (2015) | Adults | Nonclinical | United States | 79.5% 5.3% 4.6% 4.3% 3.4% 0.7% |
Caucasian Asian/Pacific Islander Latina/o Mixed ethnic heritage African American Native American |
81.7% women |
| Durso et al. (2016) | Adults | Nonclinical | United States | 24.4% 23.3% 10.0% 3.3% 1.1% 1.1% |
Caucasian Asian American Native Hawaiian/Pacific Islander Multiracial African American Latino/a |
64.4% female |
| Eipe (2005) | Adults | Nonclinical | United States | 95.1% 3.7% 1.2% |
Caucasian African American Other |
100% women |
| Essayli et al. (2017) | Adults | Nonclinical | United States | 45.1% 23.0% 10.6% 2.7% 1.8% 16.8% |
Asian Caucasian Pacific Islander Latina Native American Mixed ethnicity |
100% female |
| Farrow & Tarrant (2009) | Adults | Nonclinical | United Kingdom | NR | NR | |
| Favre (2019) | Adults | Nonclinical | United States | 75.4% 2.9% 2.1% 1.3% 4.1% |
White Multiple races Black or African American Other Hispanic or Latino/a |
Biological sex: 84.2% female Gender identity: 82.9%female 2.4% Transgender, Gender Queer, or Other Gender 14.6% male |
| Fekete et al. (2021) | Adults | Nonclinical | United States | 86.8% 5.3% 3.0% 3.0% 1.9% |
nonHispanic White Hispanic Asian Black/African American Multiracial/Other |
100% women |
| Fortesa & Ajete (2014) | Adults | Nonclinical | Kosovo | NR | 100% female | |
| Gan et al. (2012) | Adults | Nonclinical | Malaysia | 44.5% 9.9% 4.7% 0.9% |
Chinese Indian Malay Other |
59.4% female 40.6% male |
| Gerend et al. (2023) | c | Nonclinical | United States | 57.0% 34.0% 1.0% <1.0% <1.0% 3.0% 4.0% |
White Black or African American American Indian or Alaska Native Native Hawaiian or Other Pacific Islander Asian Multiracial Unknown |
50% men 50% women |
| Gordon et al. (2023) | Adults | Nonclinical | United States | 90.8% 1.3% 2.6% 2.3% 3.1% |
White Black Latinx/Hispanic Asian Other/Multiracial |
75.5% women 24.5% men |
| Groshon & Pearl (2023) | Adults | Nonclinical | United States | 28.2% 67.8% 2.8% 1.4% 8.5% |
White Black Asian Multiracial Hispanic/Latinx |
84.5% female 15.5% male |
| Hall (2020) | Adults | Nonclinical | United States | 74.5% 8.0% 6.6% 3.1% 0.3% 3.8% 2.8% |
Caucasian Latino/Latina/Hispanic Asian/Pacific Islander African American/Black Native American/Alaskan Native Multiracial Other |
84.9% female 13.4% male 0.7 % transgender 0.4% other |
| Heijens et al. (2012) | Adults | Nonclinical | Belgium | 100% | Flemish | 66.53% female 33.47% male |
| Herbozo et al. (2017) | Adults | Nonclinical | United States | 46.1% 24.9% 13.9% 6.6% 7.3% 0.6% 0.3% 0.3% |
White Black Latina Asian Multiracial Native Hawaiian/Pacific Islander American Indian/Alaskan Native Decline to specify |
100% women |
| Hill et al. (2023) | Adults | Nonclinical | Canada | 69.2% 12.6% 11.5% 1.1% 1.1% 0.5% 0.5% 1.1% 2.4% |
White Indigenous Black East/Southeast Asian South Asian Latino Middle Eastern Prefer not to say No response |
100% women |
| Himes (2011) | Adults | Nonclinical | United States | 65.8% 15.3% 13.3% 3.6% 2.0% |
Caucasian Hispanic American African American Asian American Other |
100% female |
| Himmelstein et al. (2017) | Adults | Nonclinical | United States | 64.7% 16.3% 13.0% 5.90% |
White Latinx/Hispanic Black or African American Asian/Pacific Islander |
50.30% female 49.70% male |
| Himmelstein et al. (2018) | Adults | Nonclinical | United States | 64.9% 15.8%13.0% 4.4% 1.9% |
White Hispanic Black Asian Other |
53.90% female 46.10% male |
| Himmelstein et al. (2019) | Adults | Nonclinical | United States | 52.7% 23.1% 16.2% 5.8% 32.3% 34.1% 33.5% 0.0% |
Sample 1 White Hispanic/Latinx Black Asian Sample 2 White Hispanic/Latinx Black Asian |
100% men |
| Himmelstein et al. (2020) | Adults | Nonclinical | United States | 90.0% 3.6% 3.0% 2.0% 0.6% |
White Hispanic or Latino Black Other Asian |
94.5% female |
| Hopkins (2023) | Adults | Nonclinical | United States | 71.9% 16.5% 2.5% 0.8% 1.7% 3.3% 2.5% 3.3% 95.9% |
White Black or African American South Asian East Asian American Indian or Native American Multiracial Other Latin American Not Latin American |
77.7% female 19% male 1.7% GNC or Non-binary 1.7% Prefer to self-describe |
| Hübner et al. (2016) | Adults | Nonclinical | Germany | NR | 63.52% female | |
| Huellemann et al. (2023) | Adults | Nonclinical | Canada | 48.8% 13.8% 13.4% 5.9% |
White South Asian Chinese Multiple ethnic identities |
100% women |
| Hunger et al. (2020) | Adults | Nonclinical | United States | 75.4% 15.5% 7.1% 1.7% 0.3% |
White Asian/Pacific Islander African American/Black Other/prefer to self-describe American Indian/Native American/Alaska Native |
52.8% female 47.1% male |
| Jiwanmall et al. (2022) | Adults | Nonclinical | India | 80.0% 6.7% 2.0% 6.7% 4.7% |
White Asian Black Hispanic Multiracial |
73% female |
| Kamolthip et al. (2022) | Adults | Nonclinical | Taiwan | NR | 53.75% female 46.25% male | |
| Keast et al. (2023) | Adults | Nonclinical | Canada | 44.9% 22.6% 11.1% 7.1% 4.0% 2.2% 1.7% 1.3% 0.2% 0.7% |
White East Asian South Asian Mixed Middle Eastern Southeast Asian Latinx Black Pacific Islander Other |
80.8% female 18.3% male 1.2% genderqueer |
| Kerr (2008) | Adults | Nonclinical | United States | 79.7% 0.6% 3.8% 0.0% 5.1% 11.4% |
White American Indian/Alaskan Native African American Asian Indian Other Asian Hispanic |
100% female |
| Latner et al. (2009) | Adults | Nonclinical | United States | 96.4% | Caucasian | 83.7% women |
| Lawrence et al. (2023) | Adults | Nonclinical | Australia France Canada Germany United Kingdom United States |
94.0% 0.01% 0.0% 0.02% 0.01% 0.01% |
non-Hispanic White non-Hispanic Black non-Hispanic Asian Hispanic/Latino Other Mixed/multiple |
94.9% female 5.1% male 0.1% other |
| Lawson et al. (2021) | Adults | Nonclinical | United States | 83.9% | White | 82.6% female |
| Lee et al. (2019) | Adults | Nonclinical | United States | 77.0% 72.0% |
nonHispanic White |
81% female |
| Lee et al. (2021) | Adults | Nonclinical | United States | 64.1% 12.2% 1.4% 15.1% 5.4% 0.1% 1.3% 0.4% |
White Black/African American Native American, Eskimo, Aleut Hispanic, Latino/a Asian, Asian American Native Hawaiian or Pacific Islander Biracial/Multiracial Other |
50.4% Women 49.4% Men |
| Leget et al. (2023) | Adults | Nonclinical | United States | 78.8% | non-Hispanic White | 100% women |
| Levy et al. (2022) | Adults | Nonclinical | Canada | 65.2% 13.0% 4.3% 4.3% 12.4% |
White Asian Black Hispanic Other |
52.8% female 47.2% male |
| Lin et al. (2020) | Adults | Nonclinical | China & Taiwan | NR | 53.9% female | |
| Locker (2015) | Adults | Nonclinical |
United States Canada United Kingdom Australia New Zealand Greece + |
82.0% 2.0% 7.0% 2.0% 1.0% 4.0% |
White or Caucasian Black or African American Hispanic Asian or Pacific Islander Biracial or Multiracial East Indian, Indian American, or Middle Eastern Other |
100% female |
| Macho et al. (2023) | Adults | Nonclinical | Spain | 92.5% 0.3% 4.8% 2.4% |
White Black Latin Combined |
77.4% female 22.6% male |
| Marshall et al. (2020) | Adults | Nonclinical | United States | 45.8% 31.6% 8.0% 6.2% 2.7% 2.2% 1.8% |
Asian Caucasian Native Hawaiian/Pacific Islander Other Ethnicity Multiracial Hispanic/Latina African American |
100% women |
| Mason et al. (2017) | Adults | Nonclinical | United States | 77.3% 13.7% 12.0% |
White Two or more races Hispanic, Latin, or Spanish Origin |
100% female |
| Mehak (2018) | Adults | Nonclinical | Canada | 41.6% 16.8% 12.9% 5.9% 5.9% 3.0% 2.0% 11.9% |
Caucasian South Asian Southeast Asian Arab/West Asian East Asian Black/African American Latin/South American Other |
100% female |
| Mensinger et al. (2021) | Adolescents/ Adults |
Clinical | United States | 78.0% 12.0% 4.0% 2.0% 3.0% |
White Latinx Asian Black Native American/Alaskan |
94% male 6% female |
| Mensinger et al. (2016) | Adults | Nonclinical | United States | 93.8% 0.05% 0.01% |
White Hispanic African American |
100% women |
| Mensinger et al. (2023) | Adults | Nonclinical | United States | 93.0% | White | 100% women |
| Mora-Giral et al. (2004) | Adults | Nonclinical | Spain | NR | 100% female | |
| Nightingale & Cassin (2023) | Adults | Nonclinical | Canada | 39.8% 17.8% 13.6% 8.3% 4.7% 2.9% 11.3% |
White South Asian East Asian Black Arabic/Middle Eastern Indigenous Other |
100% women |
| O’Brien et al. (2016) | Adults | Nonclinical | Australia | 60.0% 37.0% 3.0% |
White Asian or Pacific Islander Black |
26.6% male |
| O’Hara et al. (2016) | Adults | Nonclinical | United Arab Emirates | 100% | Arab | 100% female |
| O’Neill et al. (2023) | Adults | Nonclinical | United States | 66.4% 25.8% 7.8% |
White Black Other people of color |
100% women |
| Osa et al. (2021) | Adults | Nonclinical | United States | 28.3% 23.4% 24.3% 23.8% |
Non-Hispanic White African American Hispanic/Latino Asian/Asian American |
100% male |
| Panza (2019) | Adults | Nonclinical | United States | 54.5% 14.5% 12.7% 9.1% 7.3% 1.8% |
White Multiracial Asian Hispanic African American/Black Native American |
100% female |
| Panza et al. (2021) | Adults | Nonclinical | United States | 55.0% 7.0% 13.0% 7.0% 18.0% |
Caucasian/White Black/African American Asian Hispanic/Latina More than one race |
96.0% Cisgender female 4.0% gender-queer/nonconforming |
| Pape et al. (2021) | Adults | Nonclinical | Germany | NR | 67.1% female | |
| Park & Seo (2023) | Adults | Nonclinical | Korea | 100% | Korea | 72.0% women 28.0% men |
| Pearl & Puhl (2016) | Adults | Nonclinical | United States | 83.4% 7.3% 4.6% 3.1% 1.5% |
White Black or African American Hispanic, Latino/a, or Mexican-American Asian or Pacific Islander Other |
48.8% female |
| Pearl et al. (2015) | Adults | Nonclinical | United States | 43.0% 28.0% 11.0% 8.0% 10.0% |
White nonHispanic African American Asian or Pacific Islander Mexican American, Latino, or Hispanic Other |
100% women |
| Pearl et al. (2020) | Adults | Nonclinical | United States | 91.1% 3.2% 0.6% 2.4% 1.7% |
White Black Asian Hispanic/Latinx Other |
94.6% women 5.4% men |
| Pearl et al. (2021) | Adults | Nonclinical | Australia, Canada, France, Germany, the United Kingdom, and United States | 90.8% 9.2% 97.2% 2.8% 95.3% 4.7% 96.2% 3.8% |
US sample White Non-White Australian sample White Non-White Canadian sample White Non-White UK sample White Non-White |
US sample 94.5% female 5.3% male Australian sample 97.4% female 2.6% male Canadian sample 93.7% female 6.2% male French sample 96.4% female 3.5% male German sample 95.0% female 4.9% male UK sample 6.0% male 93.8% female |
| Petersen et al. (2021) | Adults | Nonclinical | United States | 92.4% | White | 82.3% female |
| Puhl & Brownell (2006) | Adults | Nonclinical | United States | 95% 2.0% 1.5% 1.5% 85.5% |
Sample 1 White African American Hispanic Indian, Asian, and other Sample 2 White |
Sample 1 100% women Sample 2 50% women 50% men |
| Puhl et al. (2007) | Adults | Nonclinical | United States | 95.0% | White | 100% female |
| Puhl et al. (2020) | Adults | Nonclinical | United States | 30.2% 24.3% 17.1% 16.8% 11.6% |
White Asian American Hispanic African American or Black Other |
64.2% females 34.4% males 0.01% other gender identity |
| Puhl et al. (2022) | Adults | Nonclinical | United States | 75.1% 12.4% 7.3% 4.1% 1.1% |
Non-Hispanic White Black Hispanic White Asian Other |
51.4% female |
| Pullmer et al. (2021) | Adults | Nonclinical | United States | 79.7% 6.3% 8.2% 0.4% 5.3% |
White Asian Black Native American Multiracial |
45.7% men 53.6% women 0.3% trans women 0.3% nonbinary |
| Poon et al. (2023) | Adults | Nonclinical | United States | 55.0% 23.0% 7.0% 7.0% 18.0% |
Non-Hispanic White Asian/Asian American African American Hispanic/Latino Multiracial |
100% assigned female at birth 4% gender nonconforming |
| Purton et al. (2019) | Adults | Nonclinical | United States | 51.3% 20.3% 16.2% 5.4% 3.2% 3.0% |
Asian American, Asian, or Pacific Islander European American or Caucasian Biracial or multiracial Native American or American Indian Hispanic African American or Other |
68.25% women 31.75% men |
| Quick et al. (2013) | Adults | Nonclinical | United States | 55.0% 20.0% 10.0% 10.0% 5.0% |
White Asian Hispanic African American Other |
100% female |
| Raffoul et al. (2023) | Adults | Nonclinical | United States | 93.5% 1.9% 1.2% 1.1% 2.3% |
non-Hispanic White Hispanic/Latine non-Hispanic Asian non-Hispanic Black Other |
100% women |
| Reinka et al. (2021). | Adults | Nonclinical | United States | 64.1% 15.1% 12.5% 5.8% 2.0% |
White Latino Black/African American Asian/Pacific Islander Other |
50.8% female 49.2% male |
| Rodriguez et al. (2019). | Adults | Nonclinical | United States | 67.3% 14.8% 10.2% 2.8% 2.8% 2.2% |
White NR Latinx Black Asian/Pacific Islander Other/Multiracial |
100% women |
| Romano et al. (2021) | Adults | Nonclinical | United States | 41.2% 37.8% 12.7% 5.0% 2.7% 0.6% 14.4% 85.6% 42.9% 35.8% 10.9% 5.85% 4.02% 0.29% 13.1% 86.8% |
Sample 1 White Black/African American Multiracial, Asian, Asian American, Native Hawaiian, or Pacific Islander Other American Indian or Alaskan Native Hispanic/Latinx NonHispanic/Latinx Sample 2 White Black/African American Multiracial, Asian, Asian American, Native Hawaiian, or Pacific Islander Other American Indian or Alaskan Native Hispanic/Latinx NonHispanic/Latinx |
Sample 1 75.8% female Sample 2 75.80% female |
| Romano & Heron (2023) | Adults | Nonclinical | United States | 49.5% 5.56% 32.3% 0.5% 4.0% 11.1% 88.9% |
White Asian Black American Indian or Alaska Native Other Hispanic Non-Hispanic |
87.9% women 12.1% men |
| Rosenbaum & Bernstein (2022) | Adults | Nonclinical | United States | 26.3% 17.2% 11.2% 38.2% 2.5% 2.3% 1.0% |
Asian/Asian American Black/African American Latinx White Biracial or multiracial Other Declined to respond |
|
| Rosenberger et al. (2006) | Adults | Nonclinical | United States | 66.4% 20.6% 13.0% |
Caucasian African American Other |
100% female |
| Salwen (2016) | Adults | Nonclinical | United States | 48.9% 30.2% 8.2% 5.8% 3.0% 3.8% |
Caucasian Asian Hispanic African American Multiple ethnicities Other |
55.3% women 44.7% men |
| Salwen et al. (2015) | Adults | Nonclinical | United States | 48.7% 30.3% 8.5% 5.6% 2.9% 4.0% |
Caucasian Asian Hispanic African American Multiple ethnicities Other |
43.6% men 56.4% women |
| Schuster et al. (2013) | Adults | Nonclinical | United States | 64.7% 15.6% 9.9% 4.8% 4,9% |
Non-Hispanic White Hispanic/Latino African American Asian American Other |
100% men |
| Schvey & White (2015) | Adults | Nonclinical | United States | 77.2% 13.7% 3.6% 2.0% 4.1% |
Caucasian Asian Hispanic Black Other |
89.3% female |
| Schvey et al. (2017) | Adults | Nonclinical | United States | 53.0% 25.0% 6.0% 6.0% 1.0% 9.0% 11.0% 89.0% |
White Black Asian Multiracial Native American Other Hispanic or Latino nonHispanic |
75% female 25% male |
| Selensky & Carels (2021) | Adults | Nonclinical | United States | 66.1% 8.7% 6.3% 4.8% 4.0% |
White Black or African American Hispanic or Latino Asian or Pacific Islander Other |
100% female |
| Shonrock et al. (2022) | Adults | Nonclinical | United States | 4.0% 12.7% 6.0% 1.5% 68.3% 6.3% |
Asian Black/African American Latinx/Hispanic Middle Eastern White Other |
72.3% cisgender women 27.7% cisgender men |
| Shope et al. (2022) | Adults | Nonclinical | United States | NR | 100% female | |
| Sienko et al. (2016) | Adults | Nonclinical | United States | 70.3% | White | 100% women |
| Simone & Lockhart (2016) | Adults | Nonclinical | United States | 87.5% 4.3% 1.0% 1.0% 0.5% 0.5% 4.7% |
White/Non-Hispanic Hispanic/Latino African American American Indian/Alaskan Native Asian Pacific Islander Other |
100% women |
| Sonneville et al. (2023) | Adults | Nonclinical | United States | 69.4% 10.8% 8.8% 5.9% 3.8% 1.1% 0.2% |
non-Hispanic White non-Hispanic AAPI Multiracial/multiethnic non-Hispanic Black Hispanic non-Hispanic MENA non-Hispanic AIAN |
54.9% cisgender female 39.3% cisgender male 1.3%gender minority |
| Thompson et al. (1991) | Adults | Nonclinical | United States | 95.0% | White | 100% women |
| Trobert (2014) | Adults | Nonclinical | United States | 92.8% 1.3% 5.3% 0.7% 96.7% 3.3% |
Caucasian African American Asian Native Hawaiian or other Pacific Islander nonHispanic or Latino Hispanic or Latino |
100% female |
| Vartanian & Novak (2011) | Adults | Nonclinical | United States | 71.0% | White | 75.6% female 24.4% male |
| Wellman et al. (2018) – Study 1 | Adults | Nonclinical | United States | 65.5% 13.8% 7.4% 5.3% 1.1% 6.9% |
Latino White Asian African American American Indian Other |
81% female |
| Wellman et al. (2018) – Study 1 | Adults | Nonclinical | United States | 94.7% | White | 100% female |
| Wellman et al. (2019) | Adults | Nonclinical | United States | 54.6% 22.5% 10.2% 6.3% 4.6% 1.7% |
Hispanic/Latino American African American European American/White Asian American Other Native American/American Indian |
75.1% female 24.9% male |
| Wetzel & Himmelstein (2023a) | Adults | Nonclinical | United States | 33.9% 33.4% 32.6% |
Latino or Hispanic Black non-Hispanic White non-Hispanic |
51.2% female 48.8% male |
| Wetzel & Himmelstein (2023b) | Adults | Nonclinical | United States | 57.1% 15.9% 15.1% 5.9% 6.0% |
non-Hispanic White Latino or Hispanic Black or African American Asian or Pacific Islander Other |
100% women |
| White et al. (2023) | Adults | Nonclinical | United Kingdom | 75.1% | White | 100% female |
| Williamson et al. (2021) | Adults | Nonclinical | United States | 25.7% 24.7% 24.9% 24.6% |
Non-Hispanic white African American Asian/Asian American Hispanic/Latino |
100% male |
| Womble et al. (2001) | Adults | Nonclinical | United States | NR | 54.95% female 45.05% male |
|
| Wu (2018) | Adults | Nonclinical | United States | 100% | Asian American | 55.4% male 44.6 female |
| Wu & Liu (2015) | Adults | Nonclinical | Taiwan | NR | 51.8% female 48.2% male | |
| Wu et al. (2020) | Adults | Nonclinical | United States | 94% | Asian American | 55.4% men 44.6% women |
| Zhao et al. (2023) | Adults | Nonclinical | United States | 69.5% 16.1% 6.9% 3.7% 0.4% 3.8% 15.0% |
White African American Asian American Indian/Alaska Native Pacific Islander/Native Hawaiian Other races Hispanic |
55.2% women 37.8% men 0.2% FTM transgender 0.2% genderqueer 0.2% other gender 6.3% did not report |
| Clinical | ||||||
| Ashmore et al. (2008) | Adults | Clinical | United States | 94.6% 1.1%% 2.1% 1.1% 1.1% |
White Black Latino Middle Eastern Native American |
74.19% female 25.81% male |
| Baldofski et al. (2016) | Adults | Clinical | Germany | NR | 68.75% women | |
| Burmeister & Carels (2014) | Adults | Clinical | United States | 84.3% 6.1% 3.5% 3.5% 0.9% 1.7% |
Caucasian/White Hispanic/Latino African American/Black Asian American Native American Other |
74% female |
| Calugi et al. (2023) | Adults | Clinical | United States | NR | 65.4% female | |
| Carels et al. (2010) | Adults | Clinical | United States | 89% | White | 81.8% females |
| Chen & Gonzales (2022) | Adults | Clinical | United States | 80.3% 10.6% 6.3% 0.7% 2.1% 5.6% |
White Black/African American Asian/Pacific Islander American Indian Multiracial Hispanic/Latino(a) |
54.2% male 43.7% female 1.4% non-binary 0.7% transgender |
| Durso et al. (2012) | Adults | Clinical | United States | 79.0% 14.0% 4.0% |
Caucasian Black/African American Hispanic |
65% female |
| Friedman et al. (2008) | Adults | Clinical | United States | 81.0% 16.0% 1.0% 2.0% |
White African American Latino Other |
73.3% women 26.6% men |
| Grilo et al. (1994) | Adults | Clinical | United States | 97.5% | White | 100% women |
| Jackson et al. (2000) | Adults | Clinical | United States | 88.0% 7.8% 2.6% 1.7% |
White African American Hispanic Other |
100% female |
| Jackson et al. (2002) | Adults | Clinical | United States | 96.9% 3.1% |
Caucasian Asian |
100% women |
| Lawson et al. (2020) | Adults | Clinical | United States | 51.0% 33.8% 9.7% 5.5% |
White nonHispanic Black nonHispanic Latinx other |
82.8% female 17.2% male |
| Martin-Wagar & Weigold (2023) | Adults | Clinical | United States | 91.8% 1.0% 5.1% 2.0% |
White Asian Multiracial Hispanic/Latinx |
100% women |
| Mensinger (2021) | Adults | Clinical | United States | 87.1% 5.7% 4.3% 1.4% |
White Hispanic Multiracial Other |
97.1% women |
| Olvera et al. (2017) | Adults | Clinical | United States | 78.0% 16.0% 6.0% |
Hispanic African American Did not specify |
100% women |
| Palmeira et al. (2017) | Adults | Clinical | Portugal | NR | 100% women | |
| Palmeira et al. (2018) | Adults | Clinical | Portugal | NR | 100% women | |
| Remmert et al. (2019) | Adults | Clinical | United States | 50.6% 26.5% 3.5% 9.4% |
White Black/African American Asian Other/More than one |
82.4% female 17.6% male |
| Rosenberger et al. (2007) | Adults | Clinical | United States | 68.4% | White | 75% women 25% men |
| Simone et al. (2021) | Adults | Clinical | United States | 81.5% 10.5% 5.8% 2.4% 0.4% 5.1% |
White (includes Middle Eastern) Asian Black Native American/Alaskan Indian Native Hawaiian/Pacific Islander Alternative |
Heterosexual sample: 65.3% cisgender women 34.7% cisgender men SGM sample: 72.1% cisgender women 24.9% cisgender men |
| Soulliard, Brode, Tabone, Abunnaja, et al (2021) | Adults | Clinical | United States | 93.7% 3.1% 1.3% 0.6% 0.3% 0.9% |
White Black Hispanic or Latinx Native American Asian/Pacific Islander Multiracial |
77.1% women 22.9% men |
| Soulliard, Brode, Trabone, Szoka, et al. (2021) | Adults | Clinical | United States | 95.3% 2.4% 1.1% 0.1% 0.1% 0.8% |
White Black/African American Hispanic or Latino/a/x Asian/Pacific Islander Native American or American Indian Other |
79.4% cigsender women 20.6% cisgender man |
| Child and Adolescent Samples | ||||||
| Nonclinical | ||||||
| Ahorsu et al. (2020) | Adolescents | Nonclinical | Iran | NR | 45.7% male | |
| Andrés et al. (2022) | Adolescents | Nonclinical | Spain | 77.2% 1.0% 5.4% 5.7% 1.7% 9.1% |
Parental origin Spanish European Latino North African Mixed origin Other |
51.7% male 48.3% female |
| Balantekin et al. (2018) | Adolescents | Nonclinical | United States | 100% | nonHispanic White | 100% women |
| Barker (1995) | Adolescents | Nonclinical | United States | 95.1% 3.8% 1.2% |
Caucasian African American Asian American |
100% women |
| Barnhart et al. (2023) | Adolescents | Nonclinical | China | NR | 59.7% girls | |
| Cattarin & Thompson (1994) | Adolescents | Nonclinical | United States | 94% 3.0% 3.0% |
White Hispanic Other |
100% females |
| Chen et al. (2020) | Children/ Adolescents |
Nonclinical | China | NR | 52.5% male 47.5% female |
|
| Chen et al. (2023) | Adolescents | Nonclinical | Taiwan | NR | 51.0% female 49.0% male |
|
| Chen et al. (2023) | Adolescents | Nonclinical | China | NR | 53.6% female 46.4% male |
|
| Chen et al. (2022) | Adolescents | Nonclinical | Taiwan | NR | 48.9% boys | |
| Chen & Jackson (2009) | Adolescents | Nonclinical | China | 82.8% 8.2% 5.7% |
Han Buyi Miao |
63.3% girls 36.7% boys |
| Cohrdes et al. (2021) | Adolescents | Nonclinical | Germany | NR | 54.4% female | |
| Dahill, Hay, et al. (2022) | Adolescents | Nonclinical | Australia | NR | 46% boys | |
| Dahill, Morrison, et al. (2022) | Adolescents | Nonclinical | Australia | 83.1% 2.3% 12.0% 1.1% 1.4% |
Australian European Asian Oceania/Pacific Island Other |
53% female 47% male |
| Day et al. (2021) | Adolescents | Nonclinical | Australia | NR | 53.2% female 41.4% male |
|
| Decker et al. (2022) | Adolescents | Nonclinical | United States | 66.2% 18.0% 8.6% 7.2% 54.2% 39.8% 0.0% 6.0% |
Surgical group Non-Hispanic White Non-Hispanic Black Non-Hispanic Biracial Hispanic Non-surgical group Non-Hispanic White Non-Hispanic Black Non-Hispanic Biracial Hispanic |
Surgical group 79.9% female Non-surgical group 81.9% female |
| Diaz-Zubieta (2005) | Children/ Adolescents |
Nonclinical | United States | 96.6% 0.7% 2.8% 99.3% 0.7% |
Hispanic Non-Hispanic Both White Mixed |
100% female |
| Eisenberg et al. (2003) | Adolescents | Nonclinical | United States | 48.5% 19.2% 19.0% 5.8% 3.5% 3,9% |
White Asian Black Hispanic Native American Mixed or Other Race |
49.7% girls 50.1% boys 0.2% not listed |
| Eisenberg et al. (2012) | Adolescents* | Nonclinical | United States | 48.4% 19.6% 18.6% 5.9% 3.3% 4.2% |
White Asian African American Hispanic Native American Mixed/Other ethnicitŷ |
56.8% female 43.2% male |
| Eisenberg et al. (2019) | Adolescents | Nonclinical | United States | 30.4% 29.9% 7.2% |
Hmong Latinx Somali |
NR |
| Ferma (2005) | Adolescents | Nonclinical | United States | 47% 11% 22% 7.0% 13% |
White African American Latina Asian/Pacific Islander Biracial |
100% women |
| Forney et al. (2019) | Adolescents | Nonclinical | United States | 79% 9.0% 9.0% 4.0% 2.0% >1.0% |
Caucasian African American More than one race Hispanic Missing data Asian and American Indian or Alaska Native |
100% female |
| Francisco et al. (2013) | Adolescents | Nonclinical | Portugal | NR | 70.6% females | |
| Gallardo et al. (2022) – Sample 1 | Adolescents | Nonclinical | Spain | NR | 48.7% females 50.3% males |
|
| Gallardo et al. (2022) – Sample 2 | Adults | Nonclinical | Spain | NR | 73.5% females 26.5% males |
|
| Gmeiner & Warschburger (2020) | Children | Nonclinical | Germany | NR | 51.47% girls | |
| Gmeiner & Warschburger (2022) | Children | Nonclinical | Germany | NR | 52.1% female | |
| Goldfield, et al. (2010) | Adolescents | Nonclinical | Canada | NR | 57.1% female 42.9% male |
|
| Guardabassi & Tomasetto (2022) | Children | Nonclinical | Italy | NR | 52.0% girls | |
| Haines et al. (2006) | Adolescents* | Nonclinical | United States | 48.5% 19.2% 19.0% 5.8% 3.5% 3,9% |
White Asian Black Hispanic Native American Mixed or Other Race |
55.1% female 44.9% male |
| Haines et al. (2010) | Adolescents | Nonclinical | United States | 93.4% 93.0% 6.2% 6.8% |
Cross sectional sample White girls White boys Nonwhite girls Nonwhite boys Prospective sample NR |
Cross sectional sample 56.6% girls 43.4% boys Prospective sample 59.4% girls 40.6% boys |
| Hayden-Wade et al. (2005) | Adolescents | Nonclinical | United States | 80.0% 4.0% 4.0% 3.0% 3.0% 6.0% 70% 14% 3.0% 1.0% 5.0% 7.0% |
Overweight sample White Hispanic African American Asian Multiracial or other Did not report Non-overweight sample** White Hispanic African American Asian Native American Multiracial/other |
Overweight sample 30% male Non-overweight sample 48.4& male |
| Himmelstein et al. (2019) | Adolescents | Nonclinical | United States | 66.0% 13.7% 10.0% 4.2% 4.0% 2.0% |
White Biracial or Multiracial Hispanic or Latino Black Asian Something else |
44% cisgender female 23% AFAB non-binary 21% cisgender male 8.7% transgender male 2.1% AMAB non-binary 1.2% transgender female |
| Hooper et al. (2021) | Adolescents* | Nonclinical | United States | 28.6% 20.0% 19.2% 17.2% 15.2% |
African American or Black Asian American White Latinx or Hispanic Mixed or other |
53.7% female 46.3% male |
| Hooper et al. (2023) | Adolescents | Nonclinical | United States | 29.1% 17.0% 15.2% 18.8% |
Black/African American Latinx/Hispanic Mixed/other race White |
53.1% female 46.3% male |
| Hunger & Tomiyama (2018) | Adolescents | Nonclinical | United States | 52.8% 47.2% |
White Black |
100% women |
| Hutchinson et al. (2010) | Adolescents | Nonclinical | Australia | NR | 100% female | |
| Jackson & Chen (2007) | Adolescents | Nonclinical | China | 74.3% 5.8% 5.6% 3.9% 2.7% 2.2% 5.3% |
Han Miao Buyi Yi Tu Zuang Other |
63.3% female 36.7% male |
| Jendrzyca & Warschburger (2016) | Children | Nonclinical | Germany | NR | 52% female 48% male |
|
| Johnon & Salafia (2022) | Adolescents | Nonclinical | United States | 93.8% | White | 100% girls |
| Keery et al. (2005) | Adolescents | Nonclinical | United States | 85.0% 5.0% 2.0% 2.0% 1.0% 4.0% |
White Hispanic African American Native American Asian Other |
100% female |
| King et al. (2013) | Adolescents | Nonclinical | United States | 71.0% 18.0% 11.0% |
White Black Other |
48% female |
| Lampard et al. (2014). | Adolescents | Nonclinical | United States | 29.0% 19.9% 18.9% 16.9% 3.7% 11.6% |
African American Asian American White Hispanic Native American Mixed or other |
53.2% girls 46.8% boys |
| Leme & Philippi (2013) | Adolescents | Nonclinical | Brazil | NR | 100% female | |
| Libbey et al (2008) | Adolescents | Nonclinical | United States | 58.4% 13.6% 14.4% 7.2% 2.4% 0.8% |
White Black Mixed Race American Indian Asian Hispanic |
65.5% female |
| Lessard et al. (2023) | Adolescents | Nonclinical | United States | 40.0% 25.0% 23.0% 12.0% |
White, non-Hispanic, non-Latinx Black or African American Latinx or Hispanic Multiethnic or another race/ethnicity |
59.0% female |
| Lin et al. (2021) | Adolescents | Nonclinical | Taiwan | NR | 50.8% female 49.2% male | |
| Liu et al. (2023) | Children | Nonclinical | China | NR | 52.6% male 47.4% female |
|
| Loth et al. (2014) | Adolescents* | Nonclinical | United States | 67.0% | White | 59.9% female |
| Lucibello et al. (2023) | Adolescents | Nonclinical | Canada | 46.0% 12.2% 10.9% 13.8% |
White Black South Asian More than one |
75.2% girls 10.6% boys 12.9% another gender identity |
| Lunner et al. (2000) | Adolescents | Nonclinical | Sweden & Australia | NR | 100% girls | |
| Madowitz et al. (2012) | Children/ Adolescents |
Nonclinical | United States | 76.0% 17.5% 10.0% 5.0% 2.5% 2.5% 7.5% |
White Hispanic or Latino African American Asian Hawaiian or Pacific Islander Native American Other |
58.8% female |
| Maïano et al. (2019) | Adolescents | Nonclinical | Canada | NR | 51.9% boys 48.1% girls |
|
| Munir & Dawood (2021) | Adolescents | Nonclinical | Pakistan | NR | 100% girls | |
| Najjar et al. (2018) | Adolescents | Nonclinical | United States | 47.0% 46.0% |
Hispanic African American |
66% female |
| Neumark-Sztainer et al. (2002) | Adolescents | Nonclinical | United States | 48.5% 9.0% 19.2% 5.8% 3.5% 3.9% |
White African American Asian American Hispanic Native American Mixed/Other |
50.2% boys 49.% girls |
| Neumark-Sztainer et al, (2010) | Adolescents | Nonclinical | United States | 28.4% 24.4% 14.3% 23.0% 2.5% 7.3% |
Black White Hispanic Asian Native American Mixed/Other |
100% girls |
| Olvera et al. (2013) | Children/ Adolescents |
Nonclinical | United States | 75.0% 19.0% 6.0% |
Mexican/Central American African American Unspecified/Missing |
100% female |
| Pearlman et al. (2023) | Children | Nonclinical | United States | 54.1% 13.6% 2.1% 0.5% 0.1% 9.1% 0.6% |
non-Hispanic White non-Hispanic Black Asian American Indian/Alaska Native Native Hawaiian/Pacific Islander Multi-Racial Other/Unknown |
47.6% female |
| Phares et al. (2004) | Children/ Adolescents |
Nonclinical | United States | 63.1% 21.3% 12.8% 0.7% 2.1% |
Caucasian African American Hispanic/Latino/Latina Asian American Other |
54.6% girls 35.4% boys |
| Philippi & Leme (2018) | Adolescents | Nonclinical | Brazil | NR | 100% female | |
| Plumed et al. (2019) | Adolescents | Nonclinical | Spain | 95.4% 1.59% 0.71% 0.21% 0.11% 1.90% |
Spanish Hispanic Eastern European Arabic Asiatic Others |
52.3% girls 47.7% boys |
| Pötzsch et al. (2018) | Adolescents | Both | Germany | NR | 78.9% girls | |
| Puhl et al. (2017) | Adolescents* | Nonclinical | United States | NR | 56.9% women 43.1% men | |
| Puhl & Himmelstein (2018) | Adolescents | Nonclinical | United States | 90.5% 4.7% 2.7% 2.0% |
White Latino Asian Black |
50% female 50% male |
| Quick et al. (2013) | Adolescents* | Nonclinical | United States | 48.0% 20.0% 18.0% 5.0% 3.0% 5.0% |
White African American Asian Hispanic Native American Mixed or other race/ethnicity |
52.8% female 46.2% male |
| Roberto et al. (2012) | Adolescents | Nonclinical | United States | 50.9% 31.6% 12.3% 5.3% |
White Hispanic African American Other |
80.7% female 19.3% male |
| Rodgers et al. (2021) | Adolescents* | Nonclinical | United States | 48.3% 19.7% 18.5% 5.5% 3.5% 4.5% |
White Asian African American Hispanic Native American Mixed or Other |
57% girls 43% boys |
| Rodgers, Simone, et al. (2021) | Adolescents | Nonclinical | United States | 48.2% 18.5% 19.7% 5.5% 3.5% 4.5% |
White African American Asian Hispanic Native American Mixed or other race |
57.0% girls 43.0% boys |
| Rojo-Moreno et al. (2013) | Adolescents | Nonclinical | Spain | NR | 50.1% boys 49.1% girls |
|
| Rosewall et al. (2018) | Adolescents | Nonclinical | New Zealand | 73.7% 10.3% 5.6% 2,6% 3.0% |
New Zealand European New Zealand Maori Asian Pacific Islander Other |
100% female |
| Simone et al. (2019) | Adolescents* | Nonclinical | United States | 45.6% 20.6% 20.1% 5.2% 4.4% 3.9% 0.3% |
White Asian Black or African American Hispanic Mixed race/ethnicity Native American Hawaiian or other Pacific Islander |
100% women |
| Simone et al. (2022) | Adolescents/Adults | Nonclinical | United States | 22.7% 22.1% 17.5% 23.4% 14.2% |
Asian African American/Black Hispanic/Latino/a White Mixed or other race |
58.0% female 41.3% male 0.7% other gender |
| Sinton et al. (2012) | Children/ Adolescents |
Nonclinical | United States | 66.0% 20.5% 10.5% 3.0% |
White Hispanic Black Other |
64% female |
| Smith (2009) | Children/Adolescents | Nonclinical | United States | 83.0% 3.4% 3.4% 3.4% 6.8% |
White American Indian/Native American White and American Indian/Native American White and other Other |
65.3% girls 34.7% boys |
| Tan et al. (2022) | Adolescents | Nonclinical | China | NR | 55.3% boys 44.7% girls |
|
| Trimble (2002) | Adolescents | Nonclinical | United States | 76.1% 6.8% 9.9% 6.7% 0.4% |
White** African American Hispanic Asian/Pacific Islander Native American |
100% female |
| Turker et al. (2012) | Adolescents | Nonclinical | Turkey | NR | 100% female | |
| Wang et al. (2020) | Adolescents | Nonclinical | China | NR | 54% boys 45.7% girls |
|
| Warschburger & Zitzmann (2018) | Adolescents | Nonclinical | Germany | NR | 49% girls | |
| Wertheim et al. (2001) | Adolescents | Nonclinical | Australia | NR | 100% female | |
| West et al. (2023) | Adolescents | Nonclinical | United States | 28.1% 21.1% 19.8% 17.4% 13.6% |
non-Hispanic Black non-Hispanic White Asian American Hispanic/Latinx Mixed/other |
54.1% female 45.9% male |
| Wojtowicz & von Ranson (2012) | Adolescents | Nonclinical | Canada | 75.1% 5.9% 2.5% 1.5% 1.3% 13.7% |
Caucasian Asian Black South Asian Arab Other |
100% female |
| Womble et al. (1998) | Adolescents | Nonclinical | United States | 95% | Caucasian | 100% girls |
| Clinical | ||||||
| Gerke et al. (2013) | Adolescents | Clinical | United States | 78.0% 17.0% 2.0% 1.0% 1.0% |
African American White Latino Other Did not report |
67.4% female 32.6% male |
| Gerke (2008) | Adolescents | Clinical | United States | 78.0% 15.0% 2.0% 2.0% 2.0% |
African American European American Hispanic Other Did not report |
69% female 30% male 1% did not report |
| Lieberman (2001) | Adolescents | Clinical | Canada | NR | 100% female | |
| Lin et al. (2023) | Children/Adolescents | Clinical | United States | 80.0% 2.0% 6.7% 6.7% 7.0% |
White Black Asian Hispanic Multiracial |
86.0% female 14.0% male |
| Matthews et al. (2022) | Adolescents | Clinical | United States | NR | 84.9% male 15.1% male |
|
| Pearlman et al. (2019) | Adolescents | Clinical | United States | 51.6% 23.4% 12.5% 3.1% 9.4% 21.7% |
White Black Multiracial Asian Other/Unknown Hispanic |
54% female |
| Rubin et al. (2021) | Children/ Adolescents |
Clinical | United States | 48.3% 30.3% 10.9% 10.5% 9.0% |
White African American/Black Asian Multiple/Other/Unknown Hispanic/Latinx |
54.3% female |
This table uses language for gender and race/ethnicity categories as they appear in each individual paper.
This table reports the only race/ethnicity reported in the paper so as to not make assumptions about the race/ethnicity of the remaining participants
This table reports only gender/sex information reported in the paper so as to not make assumptions about the gender/sex of the remaining participants
NR = Not reported;
At baseline;
Estimated breakdown of school or school district; ^ weighted sample
3.2.2. Predictors and Outcomes
Predictors in this review included any form of weight stigma, including experienced weight stigma (185 studies), anticipated weight stigma (6 studies), and internalized weight bias (87 studies). Experienced weight stigma included constructs such as weight teasing, weight-based victimization, and weight discrimination. Internalized weight bias included constructs such as weight self-stigma. Anticipated weight stigma included constructs such as weight stigma consciousness. For the purpose of this review, constructs such as ‘pressure to be thin’ or ‘encouragement to diet’ were not considered weight stigma, and constructs such as ‘internalization of the thin ideal’ and ‘fear of fat’ were not considered internalized weight bias. We made these exclusions primarily on theoretical grounds – although these constructs likely stem from and reflect broader societal anti-fatness, they themselves do not assess a dimension of weight stigma at the individual level. We return to this point in the discussion section. Outcomes were divided into three main categories: Binge eating, body image, and general disordered eating cognitions and behaviors. Constructs such as ‘emotional eating’ or ‘overeating’ were not considered disordered eating. Undoubtedly, some eating disorders (e.g., binge eating disorder) include dimensions of emotional eating and overeating. At the same time, individuals can and do engage in these behaviors without the presence of associated diagnostic features (e.g., distress) that would reflect an underlying disorder. Recognizing this is currently a debated topic in the literature, we address it further in the general discussion. Some articles included multiple studies or analysis of multiple weight stigma constructs of disordered eating constructs.
3.2.3. Quality Assessment
Using the NHLBI Study Quality Assessment Tool, 10.3%% (25) of articles were classified as Good quality, 87.6% (212) of articles were found to be of Fair quality, and 2.1% (5) of articles were found to be of Poor quality. Findings from all included articles can be found in Table 2. See below for a brief overview of the findings.
Table 2.
Design, constructs, and results of included studies.
| Author (year) | Designa | Weight Stigma Construct | Weight Stigma Measure (including subscales) | Disordered Eating Construct | Disordered Eating Measure (including subscales) | Relationship b/t WS and DEb |
|---|---|---|---|---|---|---|
| Adult samples | ||||||
| Nonclinical | ||||||
| Akan & Grilo (1995) | CS | Experienced | PARTS – W/ST | Body dissatisfaction | BSQ | +/0 |
| Almeida et al. (2011) | CS | Experienced | SSI | Binge eating | BES | + |
| Body dissatisfaction | Author created | + | ||||
| Almenara et al. (2017) | CS | Internalized | WSSQ | Shape Concern | EDE-Q | + |
| Weight Concern | + | |||||
| Eating Concern | + | |||||
| Restraint | + | |||||
| Annis et al. (2004). | CS | Experienced | SSQ-Extended | Body image satisfaction | MBSRQ | - |
| Overweight preoccupation | SIBID | + | ||||
| Dysfunctional appearance investment | ASI | + | ||||
| Binge eating | BES | +/0 | ||||
| Austen (2020) – Study 1 | CS | Internalized | WBIS-M | Body dissatisfaction | Male Body Attitudes Scale – Revised - Muscularity and Body Fat Subscales | + |
| Experienced | Modified EDS | + | ||||
| Austen (2020) – Study 2 | CS | Internalized | WBIS-M | Body dissatisfaction | Male Body Attitudes Scale – Revised - Muscularity and Body Fat Subscales | + |
| Experienced | Modified EDS | +/0 | ||||
| Bannon et al. (2018) | CS | Experienced | WRAQ | Binge eating | QEWP-R | +/0 |
| Bardone-Cone et al. (2008) | CS | Experienced | POTS - WT | Weight Concern | EDE-Q | + |
| Shape Concern | + | |||||
| Becker et al. (2021) | CS | Internalized | WSSQ | Restraint | EDE-Q Restraint | +/0 |
| Eating pathology | EDDS-5 | + | ||||
| Benas (2009) | CS | Experienced | PARTS – W/ST | Disordered eating | EDE-Q | + |
| Benas & Gibb (2008) | CS | Experienced | PARTS – W/ST | Body Appearance-related concerns | BAAS | + |
| Body dissatisfaction | BSQ | + | ||||
| Body dissatisfaction | EDI-BD | + | ||||
| Drive for thinness | EDI-DT | + | ||||
| Bulimia | EDI-BUL | + | ||||
| Restraint | DEBQ – Restrained eating | + | ||||
| Binge eating | BES | + | ||||
| Bennett et al. (2022) | CS | Internalized | WBIS-M | Body image | BSQ | + |
| Berman (2006) | CS | Experienced | Author created | Drive for thinness | EDI-DT | + |
| Body dissatisfaction | EDI-BD | + | ||||
| Bulimia | EDI-BUL | + | ||||
| Bidopia et al. (2023) | CS | Experienced | WRAQ | Dietary restraint | EDE-Q | + |
| Body dissatisfaction | EDE-Q | +/0 | ||||
| Shape/weight overvaluation | EDE-Q | +/0 | ||||
| Bidstrup et al. (2022) | CS | Experienced | POTS - WT | Restraint | EDE-Q - Restraint + DEBQ – Restrained eating | +/0 |
| Eating concern | EDE-Q – Eating concern | 0 | ||||
| Weight concern | EDE-Q – Weight concern | + | ||||
| Shape concern | EDE-Q – Shape concern | 0 | ||||
| Global disordered eating | EDE-Q | + | ||||
| Internalized | WBIS-11 | Restraint | EDE-Q - Restraint + DEBQ – Restrained eating | +/0 | ||
| Eating concern | EDE-Q – Eating concern | + | ||||
| Weight concern | EDE-Q – Weight concern | + | ||||
| Shape concern | EDE-Q – Shape concern | + | ||||
| Global disordered eating | EDE-Q | + | ||||
| Boswell & White (2015) | CS | Internalized | WBIS | Shape Concern | EDE-Q – Shape concern | + |
| Weight Concern | EDE-Q – Weight concern | + | ||||
| Eating Concern | EDE-Q – Eating concern | + | ||||
| Restraint | EDE-Q - Restraint | +/0 | ||||
| Eating pathology | EDE-Q | + | ||||
| Binge Eating | EDE-Q | + | ||||
| Purging | EDE-Q | +/0 | ||||
| Weight Cycling | QEWP-R | +/0 | ||||
| Burnette & Mazzeo (2020) | CS | Internalized | WBIS-M | Restraint | EDEQ | + |
| Carels et al. (2019) | LONG (EMA) | Internalized | WBIS | Urge to restrict | Author created | 0 |
| Restraint | Author created | 0 | ||||
| Urge to overeat | Author created | + | ||||
| Overeating | Author created | + | ||||
| Body appreciation | BAS | - | ||||
| Chen et al. (2023) | CS | Experienced | Based on SSI | Disordered eating | Based on Brief Coping Responses Inventory | + |
| Cheng et al. (2018) | CS | Experienced | Everyday Discrimination Scale – WS version | Disordered eating behaviors | TFEQ-R18 | + |
| Christian et al. (2023) | CS | Experienced | SSI | Disordered eating behaviors | EDE-Q | + |
| Internalized | WBIS-M | + | ||||
| Cohen (1998) | CS | Experienced | POTS - WT | Body dissatisfaction | EDI-BD | 0 |
| Concepcion (2008) | CS | Anticipated | WSSQ | Disordered eating behaviors | EDE-Q | + |
| DeFeciani (2011) | CS | Experienced | POTS - WT | Drive for thinness | MEBBIE | + |
| Over-exercise | MEBBIE | 0 | ||||
| de Macêdo, et al. (2023a) | CS | Experienced | Author created | Binge eating | EDE-Q and based on Hay, 1998 | +/0 |
| Restriction | 0 | |||||
| Purging | 0 | |||||
| de Macêdo et al. (2023b) | LONG | Experienced | Based on Himmelstein et al., 2018 & author created | Binge eating | EDE-Q | 0 |
| Restriction | 0 | |||||
| Purging | 0/+ | |||||
| Internalized | WBIS | Binge eating | + | |||
| Restriction | + | |||||
| Purging | + | |||||
| Donahue et al. (2022) | CS | Internalized | WSSQ | Disinhibited eating | TFEQ | + |
| Dietary restraint | TFEQ | + | ||||
| Binge eating | EDE-Q | + | ||||
| Douglas (2020) | EXP | Experienced | SSI | LOC Eating | Eating Loss of Control Scale | + |
| Internalized | WBIS | + | ||||
| Douglas & Varnado-Sullivan (2016) | CS | Experienced | SSI | Eating pathology | EDDS | + |
| Internalized | WBIS | + | ||||
| Douglas et al. (2021) | CS | Experienced | SSI | Eating pathology | EDDS | + |
| Durso & Latner (2008) | CS | Internalized | WBIS | Body satisfaction | BSQ - Short | + |
| Disordered eating | EDDS | + | ||||
| Drive for Thinness | EDI-DT | + | ||||
| Durso et al. (2015) | CS | Internalized | WBIS | Binge eating | EDDS | + |
| Drive for thinness | EDI-DT | + | ||||
| Body dissatisfaction | EDI-BD | + | ||||
| Bulimia | EDI-BUL | + | ||||
| Durso, et al. (2016) | CS | Internalized | WBIS | Body appreciation | BAS | + |
| Eipe, A. (2005) | CS | Experienced | PARTS – W/ST | Binge eating | BES/QEWP-R | + |
| Essayli et al. (2017) | LONG | Experienced | Experimental manipulation | Body Satisfaction | BISS | + |
| Intended disordered weight loss behaviors | Weight Loss Methods Scale | 0 | ||||
| Farrow & Tarrant (2009) | CS | Experienced | Author created | Body dissatisfaction | EDI-BD | + |
| Favre (2019) | CS | Internalized | WBIS | Binge eating | EDDS | +/0/- |
| Fekete et al. (2021) | CS | Internalized | WBIS | Restraint | DEBQ – Restrained eating | + |
| Fortesa & Ajete (2014) | CS | Experienced | The Family Influence Scale | Disordered eating | EAT-26 | + |
| Gan, et al. (2012) | CS | Experienced | POTS - WT | Disordered eating | EAT-26 | + |
| Body image concerns | MBIS | + | ||||
| Gerend et al. (2023) | CS | Experienced | Items from Puhl et al., 2017 | UWCB | Items from Neumark-Sztainer et al., 2015 | +/0 |
| Binge eating | Author created | +/0 | ||||
| Gordon et al. (2023) | CS | Experienced | EDS | UWCB | GUTS | + |
| Binge eating | GUTS | + | ||||
| Groshon & Pearl (2023) | CS | Internalized | WBIS | Binge Eating Disorder | Diagnostic interview/EDE-Q | |
| Hall (2020) | CS | Experienced | Scale from Jackson, Beeken, and Wardle (2015) | Disordered eating attitudes | EAT-8 | 0 |
| Body appreciation | BAS | - | ||||
| Heijens et al. (2012) | CS | Experienced | POTS - WT | Body dissatisfaction | BSQ | + |
| Herbozo, et al. (2017) | CS | Experienced | VCOPAS Negative Weight and Shape subscale | Binge eating | BES | + |
| Hill et al. (2023) | CS | Experienced | Author created | Body dissatisfaction | Body Image in Pregnancy Scale | + |
| Himes (2011) | CS | Experienced | Modified SATAQ-3 | State Body dissatisfaction | Visual Analogue Scales | + |
| Trait Body dissatisfaction | EDI-BD | + | ||||
| Drive for thinness | EDI-DT | + | ||||
| Bulimia | EDI-BUL | + | ||||
| Intentions to engage in UWCB | Modified EDE-Q | + | ||||
| Experienced | PARTS - W/ST subscale | State Body dissatisfaction | Visual Analogue Scales | +/0 | ||
| Trait Body dissatisfaction | EDI-BD | +/0 | ||||
| Himmelstein et al. (2017) | CS | Internalized | WBIS-M | Disordered eating-related coping | Author created | + |
| Experienced | Author created | + | ||||
| Himmelstein et al. (2018) | CS | Experienced | Author created | Restrictive dieting | Item from Venditti, Wing, Jakicic, Butler, & Marcus, 1996 | + |
| Maladaptive eating | Items from Himmelstein, Puhl, & Quinn, 2017 | + | ||||
| Himmelstein et al. (2019) | CS | Internalized | WBIS-M | Binge eating | Author created | +/0 |
| Experienced | Author created | + | ||||
| Himmelstein et al. (2020) | CS | Experienced | Author created | Eating pathology | CWSS | + |
| Internalized | WBIS | + | ||||
| Hopkins (2023) | EXP | Internalized | WBIS-M | Eating disorder diagnosis | Weight and Lifestyle Inventory | 0 |
| Body appreciation | BAS | - | ||||
| Hübner et al. (2016) | CS | Experienced | POTS - Effect | Restraint | German DEBQ – Restrained eating | + |
| Huellemann et al. (2023) | LONG | Internalized | WBIS | Body shame | Phenomenological Body Shame Scale-Revised | + |
| Body appreciation | BAS | - | ||||
| Disordered eating | EAT-26 | + | ||||
| Hunger et al. (2020) | CS | Experienced | EDS – WS version | Disordered eating | EDE-Q | + |
| Anticipated | Items from Hunger & Major, 2015 | + | ||||
| Jiwanmall et al. (2022) | Internalized | WSSQ | Binge eating | Author created | 0 | |
| Anticipated | WSSQ | 0 | ||||
| Kamolthip et al. (2022) | CS | Experienced | PWS | Cognitive restraint | TFEQ-R18 | + |
| Uncontrolled eating | TFEQ-R18 | + | ||||
| Overall disordered eating | TFEQ-R18 | + | ||||
| Keast et al. (2023) | LONG | Experienced | SSI | Restriction | EPSI | +/0 |
| Binge eating | +/0 | |||||
| Body dissatisfaction | 0 | |||||
| Internalized | WBIS-M | Restriction | 0 | |||
| Binge eating | + | |||||
| Body dissatisfaction | + | |||||
| Kerr (2008) | CS | Experienced | POTS - WT | Body satisfaction | MBSRQ | - |
| Latner et al. (2009) | CS | Experienced | SSI | Body dissatisfaction | BSQ | + |
| Lawrence et al. (2023) | CS | Experienced | Interpersonal Sources of Weight Stigma scale | Body image | MBSRQ-Appearance Evaluation | +/0 |
| Lawson et al. (2021) | CS | Internalized | WBIS | Loss of control eating | EDE-Q-7 | + |
| Overall disordered eating | EDE-Q-7 | + | ||||
| Lee et al. (2019). | CS | Experienced | SSI | Binge Eating | BES | + |
| Body dissatisfaction | MBSRQ-Body Area Satisfaction Scale | + | ||||
| Body dissatisfaction | MBSRQ-Appearance Evaluation | + | ||||
| Internalized | WBIS | Binge Eating | BES | + | ||
| Body dissatisfaction | MBSRQ-Body Area Satisfaction | + | ||||
| Body dissatisfaction | MBSRQ-Appearance Evaluation | + | ||||
| Lee et al. (2021) | CS | Anticipated and Experienced | Author Created | Eating pathology | EDE-Q-S | + |
| Leget et al. (2023) | CS | Internalized | WBIS | Body dissatisfaction | Body Parts Satisfaction Scale | + |
| Cognitive restraint | TFEQ | +/0 | ||||
| Uncontrolled eating | TFEQ | + | ||||
| Levy et al. (2022) | CS | Internalized | WBIS-M | UWCB | Items from Neumark-Sztainer et al. 2012 | + |
| EWCB | Items from Neumark-Sztainer et al. 2012 | + | ||||
| Lin et al. (2020) | CS | Experienced | Perceived weight stigma questionnaire (PWS) | Disordered eating | TFEQ | + |
| Locker (2015) | CS | Experienced | Modified Schedule of Sexist Events | Disordered eating | EAT-26 | +/0 |
| Macho et al. (2023) | CS | Internalized | WBIS | Body dissatisfaction | MBSRQ-Physical Attractiveness Subscale | - |
| Experienced | Author created | +/- | ||||
| Marshall et al. (2020) | CS | Internalized | WBIS | Disordered eating | EAT-26 | + |
| Mason et al. (2017) | CS | Experienced | EDS | Disordered eating | SCOFF | + |
| Loss of control eating | SCOFF | + | ||||
| Mehak et al. (2018) | CS | Internalized | WBIS | Binge eating | BES | + |
| Body dissatisfaction | Objectified Body Consciousness Scale – Body Shame | + | ||||
| Mensinger et al. (2021) | CS | Experienced | Author created | Eating pathology | EDE-Q | + |
| Mensinger et al. (2016) | LONG | Internalized | WBIS | Disordered eating | EDE-Q | +/0 |
| Mensinger et al. (2023) | LONG | Internalized | WBIS | Loss of control eating | TFEQ | + |
| Mora-Giral et al. (2004) | CS | Experienced | Teasing Assessment Scale | Body dissatisfaction | BSQ | + |
| Nightingale & Cassin (2023) | CS | Internalized | WBIS-M | Body dissatisfaction | VAS & BISS | + |
| O’Brien et al. (2016) | CS | Experienced | POTS - WT | Disordered eating | TFEQ | + |
| LOC Eating | LOC Eating Scale | + | ||||
| Internalized | WBIS | Disordered eating | TFEQ | + | ||
| LOC Eating | LOC Eating Scale | + | ||||
| O’Hara et al. (2016) | CS | Experienced | Project EAT | Disordered eating | EAT-26 | +/0 |
| Internalized | Weight- and Body-Related Shame and Guilt Scale | + | ||||
| O’Neill et al. (2023) | CS | Experienced | Anti-Fat Microaggression Experiences Questionnaire | Body dissatisfaction | BAS-2 | + |
| Osa et al. (2021) | CS | Experienced | POTS - WT | Loss of control eating | EDE-Q | + |
| Panza (2019) | LONG | Experienced | SSI | Binge eating | BES | + |
| Internalized | WBI | + | ||||
| Panza et al. (2020) | LONG | Experienced | SSI | Disordered eating | EDE-Q | + |
| Binge eating | EMA questions | + | ||||
| Internalized | WBIS | Disordered eating | EDE-Q | + | ||
| Binge eating | EMA questions | + | ||||
| Pape et al. (2021) | CS | Internalized | WBIS German | Cognitive restraint | FRIS | - |
| Park & Seo (2023) | CS | Internalized | WSSQ Korean | Weight concern | Weight Concern Scale Korean | |
| Pearl & Puhl (2016) | CS | Internalized | WBIS | Body dissatisfaction | EDI-BD | +/0 |
| Pearl et al. (2015) | LONG/EXP | Experienced | SSI | Drive for thinness | EDI-DT | +/0 |
| Body dissatisfaction | EDI-BD | + | ||||
| Pearl et al. (2020) | CS | Internalized | WBIS | Weight Cycling | Author created | + |
| Appearance Evaluation/Orientation | MBSRQ | + | ||||
| Experienced | Interpersonal Sources of Weight Stigma Scale | Weight Cycling | Author created | + | ||
| Appearance Evaluation/Orientation | MBSRQ | 0 | ||||
| Pearl et al. (2021) | LONG | Internalized | WBIS-M | Body dissatisfaction | MBSRQ - Appearance Evaluation subscale | + |
| Petersen et al. (2021) | CS | Internalized | WSSQ | Cognitive restraint | TFEQ | +/0 |
| Uncontrolled eating | TFEQ | +/0 | ||||
| Puhl & Brownell (2006) | CS | Experienced | SSI and Interpersonal Sources of Weight Stigma | Binge eating | QEWP - R | 0 |
| Puhl et al. (2007) | CS | Internalized | Author Created | Binge Eating | QEWP-R | + |
| Puhl et al. (2020) | LONG | Experienced | Project EAT | Binge eating | Adapted QEWP-R | + |
| Puhl et al. (2022) | CS | Experienced | Author created | Binge eating | QEWP-5 | 0 |
| Internalized | WBIS-M | + | ||||
| Pullmer et al. (2021) | CS | Experienced | EDS | Eating disorder pathology | EDE-Q-7 | + |
| Body appreciation | BIS | - | ||||
| Internalized | WBIS-M | Eating disorder pathology | EDE-Q-7 | + | ||
| Body appreciation | BIS | - | ||||
| Poon et al. (2023) | LONG (EMA) | Experienced | SSI & Author created | Weight and shape concerns | Author created | +/0 |
| Purton et al. (2019) | CS | Internalized | WBIS | Body dissatisfaction | EDE-Q - Items from Weight/Shape Concerns subscales | + |
| Quick et al. (2013) | CS | Experienced | POTS - WT | Shape Concern | EDE-Q – Shape concern | + |
| Weight Concern | EDE-Q – Weight concern | + | ||||
| Eating Concern | EDE-Q – Eating concern | + | ||||
| Restraint | EDE-Q - Restraint | + | ||||
| Eating pathology | EDE-Q | + | ||||
| Binge Eating | EDE-Q | + | ||||
| Compensatory Behaviors (Purging, Laxatives, Over-exercise) | EDE-Q | +/0 | ||||
| Raffoul et al. (2023) | LONG | Experienced | EDDS | Weight loss supplement use | Author created | + |
| Reinka, et al. (2021). | CS | Internalized | WBIS | Disinhibited eating | TFEQ - Disinhibition | + |
| Restraint | TFEQ - Cognitive Restraint | + | ||||
| Rodriguez et al. (2019). | CS | Experienced | Author created measure | Maladaptive eating behavior | EAT | +/0 |
| Romano et al. (2021) | CS | Experienced | EDS/SSI | Binge eating | EPSI – Binge eating | +/0 |
| Purging | EPSI - Purging | +/0 | ||||
| Body dissatisfaction | EPSI – Body dissatisfaction | +/0 | ||||
| Muscle building | EPSI – Muscle building | +/0 | ||||
| Restriction | EPSI - Restraint | +/0 | ||||
| Excessive exercise | EPSI – Excessive exercise | +/0 | ||||
| Internalized | WBIS | Binge eating | EPSI – Binge eating | +/0 | ||
| Purging | EPSI - Purging | +/0 | ||||
| Body dissatisfaction | EPSI – Body dissatisfaction | + | ||||
| Muscle building | EPSI – Muscle building | +/0 | ||||
| Restriction | EPSI - Restraint | +/0 | ||||
| Excessive exercise | EPSI – Excessive exercise | +/0 | ||||
| Romano & Heron (2023) | LONG (EMA) | Experienced | Author created | Binge eating | Author created, (EMA, based on EDE-Q, Intuitive eating scale, EPSI and BISS) | +/0 |
| Body dissatisfaction | Author created (EMA, based on EDE-Q, Intuitive eating scale, EPSI and BISS) | + | ||||
| Overexercise | Author created (EMA, based on EDE-Q, Intuitive eating scale, EPSI and BISS) | 0 | ||||
| Purging | Author created (EMA, based on EDE-Q, Intuitive eating scale, EPSI and BISS) | +/0 | ||||
| LOC Eating | Author created (EMA, based on EDE-Q, Intuitive eating scale, EPSI and BISS) | 0 | ||||
| Restriction | Author created (EMA, based on EDE-Q, Intuitive eating scale, EPSI and BISS) | +/0 | ||||
| Rosenbaum & Bernstein (2022) | CS | Experienced | Author created | Binge eating | BES | + |
| Internalized | WBIS-M | + | ||||
| Rosenberger et al. (2006) | CS | Experienced | Author created | Body dissatisfaction | BSQ | +/0 |
| Binge Eating | EDE-Q | +/0 | ||||
| Salwen (2016) | CS | Experienced | Weight-Related Abuse Questionnaire (WRAQ) | Binge eating | QEWP-R | + |
| UWCB | QEWP-R | + | ||||
| Salwen et al. (2015) | CS | Experienced | POTS - WT | Binge eating | QEWP-R | 0 |
| UWCB | QEWP-R | 0 | ||||
| Experienced | WRAQ | Binge eating | QEWP-R | +/0 | ||
| UWCB | QEWP-R | + | ||||
| Schuster et al. (2013) | CS | Experienced | VCAS | Eating Pathology | EDI-DT and EDI-BUL | + |
| Body satisfaction | EDI-BD | + | ||||
| Schvey & White (2015) | CS | Internalized | WBIS | Shape Concern | EDE-Q – Shape concern | + |
| Weight Concern | EDE-Q – Weight concern | + | ||||
| Eating Concern | EDE-Q – Eating concern | + | ||||
| Restraint | EDE-Q - Restraint | + | ||||
| Eating pathology | EDE-Q | + | ||||
| Bulimia | EDE-Q | + | ||||
| Binge Eating | QEWP-R | + | ||||
| Schvey et al. (2017) | CS | Internalized | WBIS | UWCB | Author created | 0 |
| Experienced | Author created | + | ||||
| Selensky & Carels (2021) | LONG | Internalized | WBIS-M | Body Satisfaction | BISS | - |
| Shonrock et al. (2022) | CS | Experienced | SSI-B | Restraint | EDE-Q - Restraint | +/0 |
| Eating concern | EDE-Q – Eating concern | +/0 | ||||
| Shape concern | EDE-Q – Shape concern | +/0 | ||||
| Weight concern | EDE-Q – Weight concern | + | ||||
| Internalized | WBIS-M | Restraint | EDE-Q - Restraint | +/0 | ||
| Eating concern | EDE-Q – Eating concern | +/0 | ||||
| Shape concern | EDE-Q – Shape concern | +/0 | ||||
| Weight concern | EDE-Q – Weight concern | + | ||||
| Shope et al. (2022) | CS | Experienced | POTS - WT | Body dissatisfaction | EPSI – Body dissatisfaction | +/0 |
| Binge eating | EPSI – Binge eating | +/0 | ||||
| Overexercise | EPSI - Overexercise | + | ||||
| Cognitive restraint | EPSI - Restraint | + | ||||
| Muscle building | EPSI – Muscle building | 0 | ||||
| Dietary restraint | EDE-Q - Restraint | 0 | ||||
| Shape and weight concerns | EDE-Q – Shape & Weight concerns | + | ||||
| LOC eating | Loss of Control over Eating Scale | + | ||||
| Sienko et al. (2016) | CS | Internalized | WBIS | Disordered eating | EDE-Q | + |
| Simone & Lockhart (2016) | CS | Experienced | SSI | Dietary restraint | DEBQ – Restrained eating | + |
| Sonneville et al. (2023) | Experienced | Based on Hunger & Major | High weight concerns | Weight Concerns Scale | + | |
| Purging | EDE-Q | +/0 | ||||
| Binge eating | EDE-Q | + | ||||
| High ED risk | SCOFF | + | ||||
| Anticipated | Based on Hunger & Major | High weight concerns | Weight Concerns Scale | + | ||
| Purging | EDE-Q | + | ||||
| Binge eating | EDE-Q | + | ||||
| High ED risk | SCOFF | + | ||||
| Thompson, et al. (1991) | CS | Experienced | PARTS – W/ST | Disordered eating | EDI | + |
| Trobert (2014) | CS | Experienced | Family Influence Questionnaire | Disordered eating | EDI | + |
| Vartanian & Novak (2011) | CS | Experienced | SSI | Body dissatisfaction | EDI-BD | + |
| EDI-DT | + | |||||
| Bulimia | EDI-BUL | + | ||||
| Wellman et al. (2018) – Study 1 | CS | Experienced | Author created | Restriction | DEBQ – Restrained eating | + |
| Wellman et al. (2018) – Study 2 | LONG | Experienced | Author created | Restriction | TFEQ – Cognitive restraint | + |
| Wellman et al. (2019) | CS | Experienced | Author created | Binge eating | BES | + |
| Internalized | Author created | +/0 | ||||
| Wetzel & Himmelstein (2023a) | CS | Experienced | Author created | Binge eating | Project EAT | + |
| Restrictive dieting | Author created | + | ||||
| Internalized | WBIS-M | Binge eating | Project EAT | + | ||
| Restrictive dieting | Author created | + | ||||
| Wetzel & Himmelstein (2023b) | CS | Experienced | Stigmatizing Situations in Health Care Scale | Uncontrolled eating | TFEQ | + |
| Dietary restraint | + | |||||
| Internalized | WBIS-M | Uncontrolled eating | + | |||
| Dietary restraint | + | |||||
| White et al. (2023) | CS | Experienced | Project EAT | Dietary restraint | EDE-Q | + |
| Body dissatisfaction | + | |||||
| Shape/weight overvaluation | + | |||||
| Williamson et al. (2021) | CS | Experienced | POTS - WT | Muscularity concerns | Revised Male Body Image Attitudes Scale | + |
| Body fat concerns | Revised Male Body Image Attitudes Scale | + | ||||
| Loss of control eating | EDE-Q | + | ||||
| Restraint | EDE-Q - Restraint | + | ||||
| Womble et al. (2001) | CS | Experienced | POTS - WT | Binge eating | BES | + |
| Wu (2018) | CS | Experienced | SSI | Binge eating | BES | + |
| Wu & Liu (2015) | CS | Experienced | SSI | Binge eating | BES | + |
| Wu et al. (2020) | CS | Experienced | SSI | Binge eating | BES | + |
| Zhao et al. (2023) | Experienced | EDS | Shape/weight concerns | EDE-Q | + | |
| Disordered eating | EDDS | + | ||||
| Clinical | ||||||
| Ashmore et al. (2008) | CS | Experienced | SSI | Binge eating | BES | + |
| Baldofski et al. (2016) | CS | Internalized | WBIS | Eating disorder pathology | EDE-Q | + |
| Burmeister & Carels (2014) | CS | Internalized | WBIS | Body satisfaction | MBSRQ-BASS | + |
| Binge eating | BES | + | ||||
| Calugi et al. (2023) | CS | Internalized | WBIS | Disordered eating | EDE | 0 |
| Carels et al. (2010) | CS/Pre-Post | Internalized | WBIS | Binge eating | BES | + |
| Body satisfaction | MBSRQ | + | ||||
| Chen & Gonzales (2022) | CS | Experienced | Scale of Treatment-Based Experiences of Weight Stigma | Disordered eating | EAT-26 | + |
| Durso et al. (2012) | CS | Internalized | WBIS | Eating disorder pathology | EDE-Q | + |
| Friedman et al. (2008) | CS | Experienced | SSI | Binge eating | BES | +/0 |
| Body dissatisfaction | BSQ | + | ||||
| Grilo et al. (1994) | CS | Experienced | PARTS – W/ST | Body dissatisfaction | BSQ | + |
| MBSRQ | + | |||||
| Jackson et al. (2000) | CS | Experienced | PARTS – W/ST | Eating disorder pathology | EDE-Q | 0 |
| Body dissatisfaction | BSQ | 0 | ||||
| Jackson et al. (2002) | CS | Experienced | PARTS – W/ST | Disordered eating | EDE-Q | 0 |
| Body dissatisfaction | BSQ | 0 | ||||
| Lawson et al. (2020) | CS | Internalized | WBIS | Overvaluation of weight/shape | EDE-Q-BSV | + |
| Body dissatisfaction | EDE-Q-BSV | + | ||||
| Restraint | EDE-Q-BSV | + | ||||
| Eating pathology | EDE-Q-BSV | + | ||||
| LOC Eating Episodes | EDE-Q-BSV | + | ||||
| Martin-Wagar & Weigold (2023) | CS | Experienced | SSI-B | Eating pathology | EDE-Q | + |
| Internalized | WBIS-s | + | ||||
| Mensinger (2021) | LONG | Internalized | WBIS | Eating concerns | EDE-Q | + |
| Binge eating | QEWP | + | ||||
| Overvaluation of weight/shape | QEWP | + | ||||
| Olvera et al. (2017) | CS | Experienced | MRFS-IV - Weight Teasing–Peers | Disordered eating behaviors | MRFS-IV | + |
| Body image disturbance | FRS | + | ||||
| Palmeira et al. (2017) | CS | Internalized | WSSQ | Binge eating | BES | + |
| Palmeira et al. (2018) | CS | Internalized | WSSQ-Self Devaluation | Uncontrolled Eating | TFEQ-R18 | + |
| Cognitive Restraint | TFEQ-R18 | - | ||||
| Binge Eating | BES | + | ||||
| Anticipated | WSSQ-Fear of Enacted Stigma | Uncontrolled Eating | TFEQ-R18 | +/0 | ||
| Cognitive Restraint | TFEQ-R18 | 0 | ||||
| Binge Eating | BES | + | ||||
| Remmert et al. (2019) | CS | Experienced | SSI | Uncontrolled eating | TFEQ-R18 | + |
| Internalized | WBIS | Restrained eating | TFEQ-R18 | 0 | ||
| Rosenberger et al. (2007) | CS | Experienced | Author created | Eating disorder pathology | EDE-Q | +/0 |
| Body dissatisfaction | BSQ | + | ||||
| Simone et al. (2020) | CS | Experienced | EDS | Lifetime diagnosis | Author created | + |
| Soulliard, Brode, Tabone, Abunnaja, et al (2021) | CS | Internalized | WBIS | Binge eating | BES | + |
| Disinhibited eating | TFEQ-D | + | ||||
| Soulliard, Brode, Trabone, Szoka, et al. (2021) | CS | Internalized | WBIS | Binge eating | BES | + |
| Disinhibited eating | TFEQ - Disinhibition | + | ||||
| Restraint | TFEQ - Cognitive Restraint | +/0 | ||||
| Child and Adolescent samples | ||||||
| Nonclinical | ||||||
| Ahorsu et al. (2020) | LONG | Internalized | WBIS | Binge eating | BES | 0 |
| Andrés et al. (2022) | CS | Internalized | WBIS-M | Body image | BSQ | + |
| Disordered eating | EDI-DT | + | ||||
| Binge eating | Adapted QEWP | + | ||||
| Balanteki, et al. (2018) | CS | Experienced | Author created | Unhealthy weight control behaviors | Author created | +/0 |
| Barker (1995) | CS | Experienced | POTS - WT | Body dissatisfaction | BSQ | +/0 |
| Eating pathology | EAT | + | ||||
| Bulimia | BULIT-R | + | ||||
| Barnhart et al. (2023) | LONG | Internalized | WBIS | Body dissatisfaction | EDI-BD | + |
| Disordered eating | EDE-QS | + | ||||
| Cattarin & Thompson (1994) | LONG | Experienced | PARTS – W/ST subscale | Drive for thinness | EDI-DT | 0 |
| Bulimia symptoms | EDI - BUL | 0 | ||||
| Body dissatisfaction | EDI-BD | 0 | ||||
| Body image | SIQYA | + | ||||
| Chen et al. (2020) | CS | Internalized | WBIS-C | Disordered eating behaviors | DEBQ-C | + |
| Chen et al. (2023) | CS | Experienced | Author created | Disordered eating | EAT-26 | +/0 |
| Chen et al. (2023) | CS | Experienced | Author created | Disordered eating | EAT-26 | + |
| Chen et al. (2022) | CS | Experienced | Author created | Disordered eating | EAT-26 | +/0 |
| Chen & Jackson (2009) | LONG | Experienced | POTS - WT | Body satisfaction | Modified BES | 0 |
| Cohrdes et al. (2021) | CS | Experienced | Author created | Disordered eating | SCOFF | + |
| Dahill, Hay, et al. (2022) | LONG | Experienced | Author created | Disordered eating | EDEQ-WS | 0 |
| Dahill, Morrison, et al. (2022) | CS | Experienced | Author created | Disordered eating | EDEQ-WS | +/0 |
| Day et al. (2021) | CS | Experienced | Cyberbullying Questionnaire | Drive for muscularity | Drive for Muscularity Scale | + |
| Muscularity-oriented Behaviors | DMS | + | ||||
| Drive for leanness | Drive for Leanness Scale | +/0 | ||||
| Drive for thinness | EDE-Q | +/0 | ||||
| Restriction | EDE-Q - Restraint | +/0 | ||||
| Binge eating | EDE-Q | +/0 | ||||
| Purging | EDE-Q | + | ||||
| Compulsive Exercise | EDE-Q | +/0 | ||||
| Decker et al. (2022) | LONG | Experienced | POTS - WT | Binge eating | EDE-Q-BSV | +/0 |
| Disordered eating | EDE-Q-BSV | +/0 | ||||
| Binge eating | QEWP-R | +/0 | ||||
| Diaz-Zubieta (2005) | CS | Experienced | MRFS-IV | Eating pathology | EDI-C | + |
| Eisenberg et al. (2003) | CS | Experienced | Author created/One item | Body dissatisfaction | Project EAT | + |
| Eisenberg et al. (2012) | LONG | Experienced | Project EAT | Unhealthy weight control behaviors | Project EAT | + |
| Extreme weight control behaviors | Project EAT | +/0 | ||||
| Binge eating | Project EAT | + | ||||
| Eisenberg et al. (2019) | CS | Experienced | Project EAT | Body dissatisfaction | Project EAT | + |
| UWCB | Project EAT | + | ||||
| Ferma (2005) | CS | Experienced | PARTS – W/ST | Restrained eating | DEBQ - Restrained eating | + |
| Extreme weight loss behaviors | Extreme Weight Loss Behavior Checklist | + | ||||
| Body attitudes | BAQ | + | ||||
| Forney et al. (2019) | CS | Experienced | POTS | Body image concerns | MEBS - BD and weight preoccupation subscales & Y-EDEQ - shape concerns and weight concerns subscales | + |
| Francisco et al. (2013) | CS | Experienced | MRFS | Disordered eating | EDE-Q | + |
| Body satisfaction | Contour Drawing Rating Scale | -/0 | ||||
| Gallardo et al. (2022) – Sample 1 | CS | Experienced | POTS - WT | Body dissatisfaction | BSQ | + |
| Drive for thinness | EDI-DT | + | ||||
| Body dissatisfaction | EDI-BD | + | ||||
| Disordered eating | ChEAT | + | ||||
| Gallardo et al. (2022) – Sample 2 | CS | Experienced | POTS - WT | Drive for thinness | EDI-DT | + |
| Body dissatisfaction | EDI-BD | + | ||||
| Gmeiner & Warschburger (2020) | LONG | Internalized | WBIS-C | Body satisfaction | Author created | + |
| Gmeiner & Warschburger (2022) | CS | Internalized | WBIS-C | Disordered eating | SCOFF | + |
| Goldfield, et al. (2010) | CS | Experienced | MRFS - Parent and peer teasing subscales | Restraint | DEBQ – Restrained eating | + |
| Guardabassi & Tomasetto (2022) | CS | Experienced | POTS - WT | Restraint | EAT-26 | + |
| Body dissatisfaction | C-BIS | +/0 | ||||
| Haines et al. (2006) | LONG | Experienced | Author created | Binge eating | Project EAT | + |
| Unhealthy weight control behaviors | Project EAT | +/0 | ||||
| Haines et al. (2010) | CS | Experienced | Author created | Binge eating | MRFS-IV | +/0 |
| Purging | MRFS-IV | 0 | ||||
| Hayden-Wade et al. (2005) | CS | Experienced | POTS - WT | Disordered eating | EDI | + |
| Himmelstein et al. (2019) | CS | Experienced | Author created | Disordered eating behaviors | Author created | +/0 |
| Hooper et al. (2021) | LONG | Experienced | Author created/One item | Unhealthy weight control behaviors | Project EAT | + |
| Binge eating | QEWP-Revised | + | ||||
| Hooper et al. (2023) | LONG | Experienced | Project EAT | UWCB | Project EAT | + |
| EWCB | Project EAT | + | ||||
| Binge eating | Project EAT | +/0 | ||||
| Hunger & Tomiyama (2018) | LONG | Experienced | Author created | Bulimic symptoms | EDI-BUL | + |
| Drive for Thinness | EDI-DT | + | ||||
| Body Dissatisfaction | EDI-BD | + | ||||
| Disordered eating | EDI | + | ||||
| Hutchinson et al. (2010) | CS | Experienced | POTS - WT | Body dissatisfaction | EDI-BD | + |
| Body dissatisfaction | BAQ | + | ||||
| Restraint | DEBQ – Restrained eating | + | ||||
| Extreme weight loss behaviors | Extreme Weight Loss Behaviors Checklist | + | ||||
| Bulimic symptoms | EDI-BUL | + | ||||
| Jackson & Chen (2007) | CS | Experienced | POTS - WT | Eating disorder pathology | EDDS | + |
| Jendrzyca & Warschburger (2016) | LONG | Experienced | Author created | Disordered eating | SCOFF | +/0 |
| Restraint | DEBQ – Restrained eating | +/0 | ||||
| Body dissatisfaction | Author created | +/0 | ||||
| Johnon & Salafia (2022) | CS | Experienced | Author created based on Perceived Socioculture Pressure Scale | Body dissatisfaction | EDI-BD | +/0 |
| Keery et al. (2005). | CS | Experienced | POTS - WT | Body dissatisfaction | SIQYA-Body Image Subscale | +/0 |
| Body dissatisfaction | EDI-BD | +/0 | ||||
| Drive for thinness | EDI-DT | +/0 | ||||
| Bulimia | EDI-BUL | +/0 | ||||
| King et al. (2013) | CS | Experienced | Author created | Unhealthy weight control behaviors | Project EAT | + |
| Binge eating | Frequency question | + | ||||
| Lampard et al. (2014). | CS | Experienced | Project EAT | Body fat dissatisfaction | Project EAT | +/0 |
| Body build dissatisfaction | Project EAT | +/0 | ||||
| UWCB | Project EAT | 0 | ||||
| EWCB | Project EAT | 0 | ||||
| Leme & Philippi (2013) | CS | Experienced | Author created | Body satisfaction | Author created | + |
| Unhealthy weight control behaviors | Author created | + | ||||
| Binge eating | Author created | + | ||||
| Libbey et al. (2008) | CS | Experienced | Project EAT | Binge eating | EDE-Q | + |
| Unhealthy weight control behaviors | Project EAT | + | ||||
| Lessard et al. (2023) | CS | Experienced | Parental Comments Questionnaire | Unhealthy weight control behaviors | Project EAT | + |
| Body appreciation | BAS | - | ||||
| Lin et al. (2021) | CS | Internalized | WSSQ | Cognitive restraint | TEFQ-R21-Taiwan – Cognitive restraint | +/0 |
| Uncontrolled eating | TEFQ-R21-Taiwan – Uncontrolled eating | 0 | ||||
| Liu et al. (2023) | CS | Experienced | AASSQ | Body dissatisfaction | EDI-BD | + |
| Loth et al. (2014) | LONG | Experienced | Author created | Unhealthy weight control behaviors | Project EAT | 0 |
| Lucibello et al. (2023) | CS | Internalized | WBIS-M | Body appreciation | BAS | - |
| Experienced | Based on Pearl and Puhl, 2016, Puhl et al., 2011 | - | ||||
| Lunner et al. (2000) | CS | Experienced | POTS - WT | Drive for thinness | EDI-DT | + |
| Body dissatisfaction | EDI-BD | + | ||||
| Madowitz et al. (2012) | CS | Experienced | Author Created | UWCB | EDE-Q | +/0 |
| Maïano et al. (2019) | CS | Internalized | WSSQ | Eating pathology | EAT-18 French | + |
| Munir & Dawood (2021) | CS | Physical weight victimization | WRAQ | Body esteem | BESAA | - |
| Global eating disorder pathology | DEBS | + | ||||
| Social pressure | DEBS | + | ||||
| Eating habits | DEBS | + | ||||
| Eating withdrawal | DEBS | + | ||||
| Overeating | DEBS | + | ||||
| Experienced | WRAQ | Body esteem | BESAA | - | ||
| Global eating disorder pathology | DEBS | + | ||||
| Social pressure | DEBS | + | ||||
| Eating habits | DEBS | + | ||||
| Eating withdrawal | DEBS | + | ||||
| Overeating | DEBS | + | ||||
| Najjar et al. (2018) | CS | Experienced | SSI | Disordered eating | QEWP-Adolescent | + |
| Body dissatisfaction | BSQ | + | ||||
| Neumark-Sztainer et al. (2002) | CS | Experienced | Project EAT questionnaire | UWCB | Project EAT | + |
| Neumark-Sztainer et al, (2010) | CS | Experienced | Author created | Body dissatisfaction | Modified BSSS | + |
| UWCB | Project EAT | + | ||||
| Binge eating | Author created | + | ||||
| Olvera et al. (2013) | CS | Experienced | MRFS-IV | Binge eating | MRFS-IV | +/0 |
| Pearlman et al. (2023) | LONG | Experienced | ABCD Youth Discrimination Questionnaire | ED diagnosis | Kiddie Schedule for Affective Disorders and Schizophrenia for School-Aged Children | + |
| Phares et al. (2004) | CS | Experienced | POTS - WT | Body dissatisfaction | EDI-BD | + |
| Drive for thinness | EDI-DT | + | ||||
| Bulimia | EDI-BUL | + | ||||
| Philippi & Leme (2018). | CS | Experienced | Author created | UWCB | Author created | + |
| Body dissatisfaction | Author created | + | ||||
| Plumed et al. (2019) | LONG | Experienced | POTS - WT | Disordered eating | ChEAT | + |
| Drive for thinness | EDI-DT | + | ||||
| Body dissatisfaction | EDI-BD | + | ||||
| Pötzsch, et al. (2018) | CS | Experienced | POTS - WT | Eating disorder pathology | EDE-Q | + |
| Internalized | WBIS | |||||
| Puhl et al. (2017) | LONG | Experienced | Project EAT | Binge eating | Project EAT | +/0 |
| Eating as a coping strategy | Motivations to Eat Measure - Coping Subscale | + | ||||
| Unhealthy weight control behaviors | Project EAT | +/0 | ||||
| Body satisfaction | BSSS | - | ||||
| Puhl & Himmelstein (2018) | CS | Internalized | WBIS-M | Binge eating | Author created | + |
| Quick et al. (2013) | LONG | Experienced | Author created | Body dissatisfaction | BSSS | + |
| Roberto et al. (2012) | CS | Internalized | WBIS | Shape Concern | EDE-Q | + |
| Weight Concern | EDE-Q | + | ||||
| Eating Concern | EDE-Q | + | ||||
| Restraint | EDE-Q | 0 | ||||
| Rodgers et al. (2021) | LONG | Experienced | Project EAT | UWCB | Project EAT | 0 |
| Body Satisfaction | Project EAT | -/0 | ||||
| Rodgers, Simone, et al. (2021) | LONG | Experienced | Project EAT | Body satisfaction | EAT II | +/0 |
| UWCB | +/0 | |||||
| Rojo-Moreno et al. (2013) | CS | Experienced | POTS - WT | Eating pathology | ChEAT | + |
| Drive for thinness | EDI-DT | + | ||||
| Body dissatisfaction | EDI-BD | + | ||||
| Rosewall et al. (2018) | CS | Experienced | POTS - WT | Eating pathology | EAT-26 | + |
| Body dissatisfaction | Stunkard Body Figure Drawings | + | ||||
| Body dissatisfaction | EDI-BD | + | ||||
| Simon et al. (2019) | LONG | Experienced | POTS - WT | UWCB | Pound of Prevention Survey – UWCB items | + |
| Simone et al. (2022) | LONG | Experienced | Project EAT | Binge eating | QEWP-R | + |
| UWCB | Project EAT | + | ||||
| Sinton et al. (2012) | CS | Experienced | POTS - WT | Shape Concern | ChEDE | + |
| Weight Concern | ChEDE | + | ||||
| Smith (2009) | CS | Experienced | Author created | Eating concerns | ChEAT | + |
| Body Esteem | BES-Revised | - | ||||
| Body Satisfaction | CFRS | - | ||||
| Tan et al. (2022) | CS | Experienced | Project EAT | Binge eating | Adapted QEWP | + |
| Trimble (2002) | CS | Experienced | Measure of Perceived Social Influence | Drive for thinness | EDI-DT | + |
| Body dissatisfaction | EDI-BD | + | ||||
| Bulimia | EDI-BUL | + | ||||
| Turker et al. (2012) | CS | Experienced | Author created | Body dissatisfaction | BSQ | + |
| Disordered eating | EAT-26 | + | ||||
| Wang et al. (2020) | CS | Experienced | POTS - WT | Disordered eating behaviors | TFEQ-R18 | +/0/- |
| Warschburger & Zitzmann (2018) | CS | Experienced | POTS - WT | Disordered eating | EAT-26 | + |
| Drive for thinness | EDI-DT | + | ||||
| Body dissatisfaction | EDI-BD | + | ||||
| Bulimia | EDI-BUL | + | ||||
| Wertheim et al. (2001) | LONG | Experienced | POTS - WT | Body dissatisfaction | EDI-BD | + |
| Drive for thinness | EDI-DT | + | ||||
| Bulimia | EDI-BUL | + | ||||
| Restraint | DEBQ – Restrained eating | + | ||||
| West et al. (2023) | CS | Experienced | Project EAT | UWCB | Project EAT | 0 |
| Wojtowicz & von Ranson (2012) | LONG | Experienced | POTS - WT | Body dissatisfaction | Satisfaction and Dissatisfaction with Body Parts Scale | 0 |
| Womble et al. (1998) | LONG | Experienced | POTS - WT | Bulimia | BULIT-R | + |
| Clinical | ||||||
| Gerke et al. (2013) | CS | Experienced | POTS - WT | Disordered eating | ChEDE-Q | + |
| Gerke (2008) | CS | Experienced | POTS - WT | Global disordered eating | ChEDE-Q | + |
| Restraint | ChEDE-Q - Restraint | 0 | ||||
| Eating concern | ChEDE-Q – Eating concern | +/0 | ||||
| Shape concern | ChEDE-Q – Shape concern | + | ||||
| Weight concern | ChEDE-Q – Weight concern | + | ||||
| Binge eating | ChEDE-Q | + | ||||
| Lieberman (2001) | LONG | Experienced | Peer Pressure and Eating Scale; Self-reported teasing (yes/no) and Peer Report of teasing | Disordered eating | ChEAT | + |
| Body Esteem | BES-Revised | - | ||||
| Lin et al. (2023) | CS | Experienced | Coded qualitative interviews and retrospective chart reviews | Eating Disorder Triggers | Coding qualitative interviews and retrospective chart reviews | + |
| Matthews et al. (2022) | CS | Experienced | Author created | Disordered eating | EDE-Q | +/0 |
| Restraint | EDE-Q - Restraint | 0 | ||||
| Shape concern | EDE-Q – Shape concern | +/0 | ||||
| Weight concern | EDE-Q – Weight concern | +/0 | ||||
| Eating concern | EDE-Q – Eating concern | + | ||||
| Pearlman et al. (2019) | CS | Experienced | Modified Weight-Based Victimization Scale | Shape Concern | EDE-Q – Shape concern | + |
| Weight Concern | EDE-Q – Weight concern | + | ||||
| Eating Concern | EDE-Q – Eating concern | + | ||||
| Restraint | EDE-Q - Restraint | 0 | ||||
| Eating pathology | EDE-Q | + | ||||
| Rubin et al. (2021) | LONG | Experienced | POTS - WT | Eating in the absence of hunger | EAH for Children and Adolescents | 0 |
| Disordered eating | C-EDE | + | ||||
CS = Cross sectional; LONG = Longitudinal; EXP = Experimental
“+” = significant positive relationship; “−” = significant negative relationship; “0” = no significant relationship
ASI = Appearance Schemas Inventory; BAAS - Beliefs About Appearance Scale; BAQ = Ben-Tovim Walker Body Attitudes Questionnaire; BAS = Body Appreciation Scale; BES = Body Esteem Scale; BESAA = Body Esteem Scale for Adolescents and Adults; BISS = Body Image States Scale; BSQ = Body Shape Questionnaire; BSSS = Body Shape Satisfaction Scale; BULIT = The Bulimia Test; CFRS = Collin’s Figure Rating Scales; ChEAT = Child Eating Attitudes Test; ChEDE = Child Eating Disorder Examination; ChEDE-Q = Child Eating Disorder Examination Questionnaire; CWSS = Coping with Weight Stigma Scale; DEBQ = Dutch Eating Behaviour Questionnaire; DEBS = Disordered Eating Behavior Scale; EAH = Eating in the Absence of Hunger; EAT = Eating Attitudes Test; EDDS = Eating Disorder Diagnostic Scale; EDE = Eating Disorder Examination; EDE-Q = Eating Disorder Examination Questionnaire; EDE-Q-BSV = Eating Disorder Examination Questionnaire Bariatric Surgery Version; EDE-Q-S = Eating Disorder Examination Questionnaire Short Version; EDI-DT = Eating Disorders Inventory Drive for Thinness subscale; EDI-BD = Eating Disorders Inventory Body Dissatisfaction subscale; EDI-BUL = Eating Disorders Inventory Bulimia subscale; EDI = Eating Disorders Inventory; EDS =Everyday Discrimination Scale; EPSI = Eating Pathology Symptoms Inventory; FRS = Figure Rating Scale; GUTS = Question from the Growing Up Today Study; MBSRQ = Multidimensional Body-Self Relations Questionnaire; MEBBIE = Male Eating Behavior and Body Image Evaluation; MEBS = Minnesota Eating Behavior Survey; MRFS = McKnight Risk Factor Survey; PARTS = Physical Appearance Related Teasing Scale; POTS = Perception of Teasing Scale; Project Eat = Question from the Project Eat study; QEWP - Questionnaire of Eating and Weight Patterns; SCOFF = Sick, Control, One stone, Fat, Food; SIBID = Situational Inventory of Body Image Dysphoria; SIQYA = Self Image Questionnaire for Young Adolescents; SSI = Stigmatizing Situations Inventory; TFEQ = Three Factor Eating Questionnaire; VCAS = Verbal Commentary on Appearance Scale; WBIS = Internalized Scale; WRAQ - Weight-Related Abuse Questionnaire; WSSQ = Weight Self Stigma Questionnaire
3.3. Adult Samples
3.3.1. Nonclinical Samples
3.3.1.1. Experienced Weight Stigma and Internalized Weight Bias
3.3.1.1.1. Body image.
Overall, findings from the identified articles suggest that, among nonclinical samples, weight teasing and other weight stigma experiences across developmental periods significantly correlated with worse adult body image, higher body dissatisfaction, and lower body esteem (e.g., Annis et al., 2004; Farrow & Tarrant, 2009; Friedman et al., 2008; Kerr, 2008; Schuster et al., 2013). Similarly, we broadly found that articles identified a significant relation between higher internalized weight bias and more body image concerns (e.g., Austen et al., 2020; Durso et al., 2016; Pearl et al., 2021; Purton et al., 2019; Selensky & Carels, 2021).
The addition of certain covariates either strengthened or weakened the relation between weight stigma and body dissatisfaction. For example, Hall and colleagues (2020) found that after controlling for race/ethnicity, gender, income, dieting status, exercise status, ED status, sexuality, and age, weight discrimination was significantly and negatively correlated with body acceptance. On the other hand, Cohen and colleagues (1998) found that the relation between weight teasing and body dissatisfaction was no longer significant after controlling for depression, perception of childhood weight, age, and income.
A few studies also explored mechanisms of the relation between experienced weight stigma and body image disturbances. For example, Heijens and colleagues (2012) found that the internalization of weight bias as a result of weight teasing mediated the relation between weight teasing and increased body dissatisfaction.
3.3.1.1.2. Binge eating.
Studies on weight stigma and binge eating in nonclinical samples broadly found significant correlations between higher levels of weight stigma and increased binge eating in adults (e.g., Ashmore et al., 2008; Douglas, 2020; Gerke, 2008; Wellman, et al., 2019; Wu et al., 2020). When comparing adults with binge eating disorder (BED) and no BED, those with BED experienced significantly more peer and family weight teasing, as well as more general weight/size teasing (Eipe, 2005). However, some studies did not find a relationship between weight stigma and binge eating. For example, Puhl and Brownell (2006) found that those that met BED diagnostic criteria did not report significantly more weight stigma or perpetrators of weight stigma than those that did not meet BED diagnostic criteria, and there was not a significant correlation between weight stigma and BED behaviors. Studies also found that weight bias internalization was also higher among individuals who endorsed binge eating (e.g., Burmeister & Carels, 2014; Douglas, 2020; Mehak et al., 2018; Palmeira et al., 2018).
Regarding mechanisms facilitating the weight stigma-binge eating relation, studies found that mediators of the relationship between weight stigma and binge eating include depression (Wellman et al., 2019) and negative affect (Womble et al., 2001). Variables such as disinhibition (Souillard et al., 2021a), hunger, (Souillard et al., 2021b), and appearance anxiety and body shame (Mehak et al., 2018) were examples of mediators of the weight bias internalization-binge eating relation found in the studies.
3.3.1.1.3. Disordered eating cognitions and behaviors.
Studies using nonclinical samples found that experienced weight stigma (including weight-based teasing and discrimination) is associated with general disordered eating tendencies (e.g., Gerke, 2008; Himmelstein et al., 2020; Lee et al., 2021; Mason et al., 2017), weight and shape concerns (e.g., Bardone-Cone et al., 2008), drive for thinness (e.g., Berman, 2006; DeFeciani, 2011), dietary restriction (e.g., Hubner et al., 2016; Williamson et al., 2021) and bulimia symptoms (Berman, 2006). Some studies were notable exceptions and found the addition of certain covariates resulted in non-significant correlations between weight stigma and disordered eating thoughts and behaviors. For example, Hall (2020) found that weight discrimination and disordered eating attitudes did not have a significant relation after controlling for race/ethnicity, gender, income, dieting status, exercise status, eating disorder status, sexuality, and age. Relatedly, weight bias internalization was associated with increased disordered eating behaviors and cognitions (Himmelstein et al., 2020), disinhibited eating (Soulliard et al., 2021a), restraint, and eating, shape, and weight concerns (Boswell & White, 2015; Schvey & White, 2015).
Mediators of the relationship between experienced weight stigma and disordered eating include BMI (Leet et al., 2021), weight bias internalization (Remmert et al., 2019), social support (Mason et al., 2017), social anxiety (Mason et al., 2017), negative self-perception (Salwen, 2016), psychological distress (Gan et al., 2012), and personal self-esteem, public collective self-esteem, and private collective self-esteem (Locker, 2015). When testing weight discrimination as a mediator of the relationship between BMI and disordered eating, Hall (2020) found that BMI was significantly related to disordered eating through weight discrimination. However, some studies found that potential mechanisms did not emerge as significant mediators or moderators (e.g., Douglas, 2020; Gerke, 2008). For example, Douglas (2020) found that internalized weight bias did not mediate the relationship between weight stigmatizing and binge eating, and Gerke (2008) found that depressive symptoms and self-esteem did not mediate or moderate, respectively, the relationship between weight-related teasing and disordered eating. Regarding weight bias internalization, variables such as drive for thinness and body image avoidance emerged as mediators of the relation between internalized weight bias and disordered eating (Marshall et al., 2020).
3.3.1.2. Anticipated Weight Stigma
Very few articles in our review empirically examined anticipated weight stigma and disordered eating in adult samples. Two articles have examined anticipated weight stigma through the lens of stigma consciousness (i.e., the tendency to expect being stereotyped; Pinel, 1999). These studies found that weight stigma consciousness was associated with greater binge eating among men but not women (Wellman et al., 2019) and was also associated with greater disordered eating behavior (Concepcion, 2008). Similarly, two articles have examined anticipated weight stigma from the perspective of social identity threat, characterized as anticipating devaluation, stereotyping, and discrimination because of a stigmatized identity (Hunger et al., 2015). In one correlational study, anticipated stigma mediated the association between weight-based discrimination and eating, shape, and weight concern, as well as restraint (Hunger et al., 2020). Additionally, Hunger et al. (2020) found that anticipated weight stigma was a mediator of the relationships between experienced weight stigma and restraint, eating concern, shape concern, weight concern, use of unhealthy weight control behaviors, binge eating, and global disordered eating. Clearly there is a need for further research on anticipated weight stigma and disordered eating moving forward, a topic we return to in the discussion section.
3.3.2. Clinical Samples
Of the studies on adults, 5 used clinical samples. One study, Messinger et al. (2021), included both adolescent and adult participants. These studies found that weight stigma and teasing overall related to disordered eating symptoms (Durso et al., 2012), worse body image and higher appearance evaluation (Grilo, et al., 1994). Lawson and colleagues (2020) found that weight bias internalization also related to general disordered eating, dissatisfaction with weight and shape, overvaluation of weight and shape, and with frequency of loss-of-control eating episodes. Interestingly, one study found that patients with bulimia nervosa (BN) report experiencing higher levels of weight and size teasing when compared to BED patients (Jackson et al., 2002). Alternatively, one study found that weight teasing was not related with disordered eating or body dissatisfaction among patients with BED or BN (Jackson et al., 2000).
3.4. Children and Adolescent Samples
3.4.1. Nonclinical Samples
3.4.1.1. Experienced Weight Stigma and Internalized Weight Bias
3.4.1.1.1. Body Image.
Studies found that overall, among children and adolescents, a significant correlation emerged between weight teasing/stigma and body image concerns in nonclinical samples (e.g., Forney et al., 2019; Rosewall et al., 2018, Turker et al., 2012). On a school-wide level, greater school-level prevalence of weight-related teasing was associated with lower self-esteem and greater body fat dissatisfaction in girls, over and above individual-level weight-related teasing (Lampard et al., 2014). Both family and peer-related weight-based teasing related to body image dissatisfaction (e.g., Eisenberg et al., 2003; Keery et al., 2005; Neumark-Sztainer et al., 2010; Phares et al., 2004; Quick et al., 2013). Longitudinal studies also found that childhood weight teasing often related to adult body dissatisfaction (e.g., Hunger & Tomiyama, 2018).
3.4.1.1.2. Binge Eating.
Weight teasing was overall related to binge eating among adolescents (e.g., Haines et al., 2006; King et al., 2013). Both family and peer weight-teasing were associated with binge eating in both adolescents and children (e.g., Haines et al., 2010; Neumark-Sztainer et al., 2010; Olvera et al., 2013). With regard to weight bias internalization, only one study examined this construct and binge eating in a child/adolescent sample. Puhl and Himmelstein (2018) found that weight bias internalization was significantly higher among adolescents who reported binge.
3.4.1.1.3. Disordered Eating Cognitions and Behaviors.
Adolescents who experienced weight-based victimization had a higher level of unhealthy weight control behaviors compared to youth with no history of weight-based victimization (e.g., King et al., 2013). Longitudinal studies found that weight teasing at younger ages was related with disordered eating, drive for thinness and bulimia symptoms (Hooper et al., 2021; Hunger & Tomiyama, 2018). Weight teasing from both family and peers were each associated with disordered eating behaviors such as drive for thinness, bulimic behaviors, and higher use of unhealthy and extreme weight control behaviors (e.g., Eisenberg et al., 2012; Keery et al., 2005; Madowitz et al., 2012; Phares et al., 2004). Roberto et al. (2012) found that among adolescents, weight bias internalization was correlated with eating, shape, and weight concerns.
However, the literature does show mixed results. For example, Cattarin and Thompson (1994) found that weight teasing did not significantly predict body dissatisfaction, drive for thinness, or bulimia symptoms. Further, Haines et al. (2006) found that frequent weight teasing was not predictive of incident unhealthy weight-control behaviors among female adolescents but was predictive of these behaviors among male adolescents.
Several variables emerged as significant mechanisms facilitating the relation between weight teasing and disordered eating in non-clinical samples, such as being upset about teasing (Gerke et al., 2013), body dissatisfaction (Jendrzyca & Warschburger, 2016; Munir & Dawood, 2021; Rodgers et al., 2021), drive for thinness (Rojo-Moreno et al., 2013), and negative affect (Rubin et al., 2021).
3.4.1.2. Anticipated Weight Stigma.
No articles examining the relationship between anticipated weight stigma and disordered eating cognitions and behaviors in adolescent samples were captured by our search terms.
3.4.2. Clinical Samples
Only two studies using adolescent samples were conducted with a clinical sample. As mentioned above, one study included both adolescent and adult participants. Pearlman et al. (2020) found that, adjusting for age, sex, race, BMIz, elevated anxiety status and presence of loss-of-control eating in the past three months, the presence of family weight-based teasing was significantly associated with greater eating concern, shape concern, weight concern, as well as global eating pathology for adolescents enrolled in a binge-eating and obesity prevention program. Additionally, Lieberman (2001) found that in a clinical sample of female adolescents, body and shape-based teasing was related to disordered eating behaviors and lower body esteem.
4. Discussion
Based on our systematic review of the literature, there was a clear link between weight stigma and disordered eating cognitions and behaviors. Indeed, all three dimensions of weight stigma were associated with a host of disordered eating outcomes, although the evidence base is considerably smaller for anticipated stigma than it is for both experienced and internalized stigma. These relationships were also fairly consistent across the disordered eating outcomes. This relationship emerged across clinical and non-clinical samples and across development from early adolescence to adulthood. Importantly, and justifying the need for an updated review, our search yielded 242 articles. In contrast, the reviews by Zhu et al. (2022), Emmer et al. (2020), Mason et al. (2020), and Vartanian and Porter (2016) reviewed 105 articles or fewer. We attribute this to recent increased attention being given to weight stigma as a driver of disordered eating, as well as our search terms that comprehensively captured dimensions of weight stigma and outcomes related to disordered eating. Although this existing literature is not without its limitations, which we address in detail below, it nevertheless paints a sobering picture of the impact that weight stigma can have on disordered eating cognitions and behaviors.
The sample sizes of the reviewed articles varied widely from 40 (Grilo et al., 1994) to as large as 57,997 (Rojo-Moreno, et al., 2013). In general, the sample sizes in this literature have increased over time. Impressively, the median sample size among articles published in 2023 thus far (N = 39) was over 700, and 19 studies – including 4 leveraging longitudinal designs – had over 1000 participants. These larger sample sizes may be a result of the broader discussion regarding sample size and replicability in the behavioral sciences (e.g., Nosek et al., 2022). However, these samples also likely reflect a growing consideration of weight stigma in large-scale cohort datasets (e.g., Pearlman et al., 2023; Raffoul et al., 2023; Rodgers et al. 2021) and a trend among researchers in psychology to deliberately employ census-matched and related quota-sampling approaches (e.g., Lee et al., 2021, Wetzel & Himelstein, 2023, Gerend et al., 2023). These recent well-powered studies provide insight into the magnitude of the relationship between weight stigma and disordered eating outcomes. For example, Lee and colleagues (2021) found that a combined measure of anticipated and experienced weight stigma was strongly correlated (r = .54) with global disordered eating, and Wetzel and Himmelstein (2023) showed that internalized stigma was moderately correlated (r = .36) with greater binge eating. Likewise, in a large study that oversampled racial and sexual minorities, Gerend and colleagues (2023) found that experienced weight stigma was associated (ß = .26) with greater use of unhealthy weight control behaviors, even when controlling for a host of demographic characteristics. These exemplars are consistent with relevant meta-analyses in the field, which have found medium effect sizes for the association between weight stigma and disordered eating outcomes (Emmer et al., 2020; Mason et al., 2020; Zhu et al., 2022).
In addition to highlighting a trend toward larger and more nationally-representative samples, the articles published in 2023 underscore emerging global diversity in sample populations within this literature, including numerous large studies from the Global South including Brazil (Macêdo et al., 2023a, 2023b), China (Barnhart et al., 2023; Chen et al., 2023; Liu et al., 2023) and Taiwan (Chen et al., 2023). We are also seeing an increasing use of diverse methods, including a movement away from cross-sectional survey designs. Indeed, over a quarter of the articles published in 2023 were longitudinal in nature, and others employed daily diary (Romano & Herron, 2023) experimental (Hopkins, 2023), and dyadic designs (West et al., 2023). Both regional and methodological diversity are welcome and directly address pressing limitations in the field discussed in greater detail below. Should these trends persist, the weight stigma and disordered eating literature stands to continue building a robust and rigorous body of evidence.
Our review revealed a few weaknesses in this body of research. For example, much of the evidence is limited by correlational designs, and to fully understand this relationship, the field needs more longitudinal and experimental research. Although these designs often require more time and resources, they can also provide vital insights into causal mechanisms linking weight stigma and disordered eating. The diversity of samples can also be improved. Indeed, about 18% of the studies had samples that were predominantly women, and about 31% included exclusively women. Yet, emerging research finds that weight stigma is highly prevalent in boys and men (Himmelstein et al. 2018; Himmelstein et al., 2019), and the impact of weight stigma on disordered eating seems to be consistent across men and women (Lee et al., 2021). Further, almost all articles reported gender in a binary, excluding those who may not identify as a man or woman, and limiting our understanding of the consequences of weight stigma among gender minorities. Specifically, most articles in our review appear to presume all individuals in their sample are cisgender or do not provide detailed information on gender (e.g., reporting the percentage of only one gender). There is a clear need for future studies to more comprehensively assess sexual and gender identities, and differentiate between sexual and gender minority individuals. This is important as transgender individuals are particularly understudied in the weight stigma literature, and LGBTQ+ broadly are particularly at-risk for weight-based victimization and eating disorder symptoms (Roberts et al., 2022; Leonard et al., 2023). Finally, many samples were also overwhelming white, a persistent issue in the disorder eating field (Egbert et al., 2022). There is a clear need for future research to ensure richer diversity in its samples.
Our review also identified a wide array of conceptualizations and measures for weight stigma, including many that have not undergone psychometric evaluation. Although by no means an issue unique to this area of weight stigma research, using a variety of terms (e.g., weight teasing, weight-based victimization, weight-based discrimination) to capture similar phenomena may contribute to confusion and limit our ability for synthesis across sub-literatures using a particular term or measure. As such, there is a pressing need to develop a unified theoretical and methodological approach to weight stigma assessment, including rigorous psychometric evaluation of measures in this domain. Our review also highlighted the diversity of measurement approaches used for disordered eating cognitions and behaviors. Although in most cases this reflects the numerous psychometrically-sound tools we have at our disposal, many studies did rely on items or measures that have not been subjected to psychometric evaluation. Future research should leverage the wealth of available measures to ensure that findings can more readily compared and integrated across studies. Finally, the field would benefit from a deeper exploration of anticipated weight stigma and disordered eating, as our review only identified 5 such articles. Experienced and internalized weight stigma are clearly important, but recent experimental research also highlights the role of anticipated weight stigma in weight loss motivation and the willingness to engage in disordered eating behaviors (Major et al., 2020).
4.1. Limitations of the Present Review
Some articles investigating similar constructs to those in this review were excluded for the sake of conceptual specificity. For example, we did not consider constructs such as “pressure to be thin,” “encouragement to diet,” or “appearance teasing” in our conceptualization of weight stigma. Although constructs such as appearance teasing can (and frequently do) include weight-related teasing, we excluded these to ensure that future work building on this review – including efforts at intervention – can be assured that the focal predictor is clearly a dimension of weight stigma. We also did not consider constructs such as “thin ideal internalization” and “fear of fat” as weight bias internalization. Finally, to avoid pathologizing what many may consider common behaviors or coping responses, we did not consider overeating or emotional eating as part of our disordered eating outcomes. Although scholarly perspectives are mixed regarding emotional eating being inherently disordered or negative, intuitive eating and weight neutral dietitians and weight stigma awareness advocates such as Virginia Sole-Smith, Ayana Habtemariam, and Rachel Hartley have noted that food inherently can have emotional value for humans. Hence, categorizing emotional eating as an inherently negative construct could pathologize potentially normal behaviors. For example, increased emotional eating was observed as a result of COVID-19 related lockdowns, and emerged as a potentially necessary affect regulation strategy in the midst of increased stress and uncertainty (Cecchetto et al., 2021). Indeed, it is not unusual for people to crave certain foods in different emotional states, and emotional eating to regulate affect is used as a strategy by healthy individuals as well as people with disordered eating (Spoor et al., 2007). The exclusion criteria set should not be seen as indicative of the importance of these constructs, but rather our attempt to ensure that the review could speak confidently to the relationship between weight stigma and outcomes related to disordered eating. Our field would benefit greatly from future work that not only reviews how these adjacent constructs are associated with disordered eating outcomes, but also engages with deep theoretical integration between those literatures and the weight stigma literature more broadly.
In our review, we observed considerable variability in how demographic information was presented (and thus presumably collected). For example, the number of options and particular descriptors used for race and ethnicity varied widely, and often information was only presented for the group in the numerical majority (e.g., only indicating “90 non-Hispanic white”). Not only does this approach lack precision when describing the racial and ethnic composition of a study, it may also inadvertently signal linguistic exclusion (Rosenberger & Claypool, 2023). Likewise, the reporting of information related to sex and gender was often unclear or vague. In many cases, only the frequency of a single category was reported. This again is imprecise, potentially signals linguistic exclusion, and in this case may reflect measurement approaches rooted in the assumption that participants are cisgender and/or identify within the gender binary. In general, researchers (not just those working in this particular subfield) would benefit from adopting an approach to demographic measurement that is clear, comprehensive, and inclusive. Although ensuring inclusive demographics should be a larger ongoing process, there are existing resources and recommendations related to race and ethnicity (e.g., Lett et al., 2022), as well as sex, gender, and sexual orientation (e.g., Bates et al., 2022).
4.2. Clinical and Public Health Implications
Our findings highlight weight stigma as a concerning predictor of disordered eating among both clinical and nonclinical samples cutting across adolescence and adulthood. This suggests that weight stigma could be a meaningful target for both prevention efforts as well as a target within treatment contexts. As such, eating disorder clinicians should consider assessing for weight stigma as it could relate to increased severity of disordered eating symptoms and shape the course of treatment. Assessing and addressing anticipated and internalized weight stigma in the clinical context may be particularly helpful for heavier clients, although further research is warranted. Some studies have found that the relationship between measures of weight stigma and measures of disordered eating were stronger for higher-weight individuals (e.g., Wetzel & Himmelstein, 2023; Raffoul et al., 2023; Neumark-Sztainer et al., 2002), however, others found no such differences (e.g., Hunger & Tomiyama, 2018). Regardless, heavier individuals report more weight stigma (Leeet al., 2021; Prunty et al., 2020), and bear the brunt of structural anti-fatness (e.g., a lack of discrimination protections), and therefore clinicians may find it beneficial to engage with these topics in the clinical context. In a related vein, scholars have increasingly critiqued the prevalence of weight stigma within the eating disorder field and made a call to action for stigma reduction within both research and practice (Alberga et al., 2016; McEntee et al., 2023). Our findings align with and underscore the urgency of this call. Additionally, public health initiatives to reduce weight stigma could also reduce the incidence and severity of disordered eating in the population. Potential interventions could include developmentally appropriate psychoeducation around the harms of weight stigma beginning in K-12 education, or efforts to increase body diversity and positive portrayals of larger individuals in media.
4.3. Conclusion
From our comprehensive review of the literature, it is clear that weight stigma impacts disordered eating cognitions and behaviors. Although there are certainly pressing avenues for future research, this impact warrants immediate attention. Indeed, as we work to improve research in this area, simultaneous efforts should be made to eliminate weight stigma at all levels. This includes educating individuals on the harms of weight stigma, as well as enacting legal protections from weight discrimination in important contexts such as employment, education, and medicine. Given the far-reaching impact of weight stigma, efforts to eliminate it are not solely a pressing public health issue, but a critical social justice one as well.
Supplementary Material
Footnotes
Declarations of interest: none
This decision was made post-registration on Prospero.
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