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. Author manuscript; available in PMC: 2021 May 19.
Published in final edited form as: Eat Behav. 2021 Mar 29;41:101504. doi: 10.1016/j.eatbeh.2021.101504

Associations Between Weight-Based Teasing and Disordered Eating Behaviors Among Youth

Alex G Rubin 1, Natasha A Schvey 1,2, Lisa M Shank 1,3,4, Deborah R Altman 1,2, Taylor N Swanson 1,3,4, Eliana Ramirez 1, Nia A Moore 1, Manuela Jaramillo 1, Sophie Ramirez 1, Elisabeth K Davis 1, Miranda M Broadney 1, Sarah LeMay-Russell 1,2, Meghan E Byrne 1,2, Megan K Parker 1,2, Sheila M Brady 1, Nichole R Kelly 5, Marian Tanofsky-Kraff 1,2,3, Jack A Yanovski 1
PMCID: PMC8131258  NIHMSID: NIHMS1687600  PMID: 33831812

Abstract

Weight-based teasing (WBT) is commonly reported among youth and is associated with disinhibited and disordered eating. Specifically, youth who experience WBT may engage in disordered eating behaviors to cope with the resultant negative affect. Therefore, we examined associations between WBT and disordered eating behaviors among youth and assessed whether negative affect mediated these relationships. Two hundred one non-treatment seeking youth (8–17y) completed questionnaires assessing WBT, disinhibited eating, depression, and anxiety. Disordered eating and loss-of-control (LOC) eating were assessed via semi-structured interview. Analyses of covariance were conducted to examine relationships between WBT and eating-related variables, and bootstrapping mediation models were used to evaluate negative affect (a composite of depressive and anxiety symptoms) as a mediator of these associations. All models were adjusted for sex, race, age, and adiposity. Among 201 participants (13.1 ± 2.8y; 54.2% female; 30.3% Black; 32.8% with overweight/obesity), WBT was associated with emotional eating, eating in the absence of hunger, and disordered eating attitudes and behaviors (ps ≤ .02). These associations were all mediated by negative affect. WBT was also associated with a threefold greater likelihood of reporting a recent LOC eating episode (p= .049). Among boys and girls across weight strata, WBT was associated with multiple aspects of disordered eating and these relationships were mediated by negative affect. Longitudinal studies are needed to clarify the directionality of these associations and to identify subgroups of youth that may be particularly vulnerable to WBT and its sequelae.

Keywords: Children, adolescents, weight-based teasing, disordered eating, negative affect, loss-of-control eating

1. Introduction

Weight-based teasing (WBT) is one of the most prevalent forms of peer victimization among children and adolescents (Puhl, Luedicke, & Heuer, 2011). Up to 60–78% of youth with high weight – and up to 20% of those without – report weight- or shape-based teasing (e.g., Goldfield et al., 2010; Puhl, Peterson, & Luedicke, 2013; Schvey et al., 2019). WBT may persist for years (Griffiths, Wolke, Page, Horwood, & Team, 2006; Puhl & King, 2013; Puhl et al., 2013), is experienced across settings and from numerous sources (e.g., family, peers, healthcare providers) (Puhl & King, 2013; Puhl et al., 2013), and is associated with adverse psychological correlates, including low self-esteem, depression, and suicidality (Puhl & Lessard, 2020).

WBT may also place youth at-risk for disordered eating attitudes and behaviors, including disinhibited eating [an umbrella term for eating behaviors involving a lack of restraint, such as emotional eating (i.e., eating in response to negative mood states), eating in the absence of hunger (i.e., initiating or continuing to eat when one is not hungry), and loss-of-control (LOC) eating (i.e., the subjective feeling of being unable to control what or how much one is eating)]. These behaviors are associated with excess weight gain among children and adolescents (Shomaker, Tanofsky-Kraff, & Yanovski, 2011). Studies have shown that WBT is associated with increased risk of LOC eating, unhealthy weight control behaviors, and dieting frequency (Marla E Eisenberg, Neumark-Sztainer, Haines, & Wall, 2006; Puhl et al., 2017). WBT is also prospectively associated with weight and adiposity gain (Puhl et al., 2017; Schvey et al., 2019; Suelter et al., 2018).

Research is needed to elucidate mechanisms and risk factors for the adverse consequences of WBT. One potential mechanism is negative affect. Affect Theory posits that individuals may use food to cope with uncomfortable or distressing affective states (Heatherton & Baumeister, 1991; Kenardy, Arnow, & Agras, 1996). Negative affect has consistently been identified as a correlate of disinhibited eating (Jansen et al., 2008; Stice, Akutagawa, Gaggar, & Agras, 2000; Stice, Ng, & Shaw, 2010), and has been cross-sectionally linked to LOC eating (Glasofer et al., 2007; Haedt-Matt & Keel, 2011), disordered eating, and body image concerns among youth and adolescents (Rodgers, Paxton, & McLean, 2014). Research in adolescent girls suggests that negative affect mediates the relationship between WBT and self-reported binge-eating (Suisman, Slane, Burt, & Klump, 2008). Given these findings, the role of negative affect in the relationship between WBT and disordered eating warrants additional examination.

Previous studies of the relationship between WBT and disordered eating have primarily examined adolescents, particularly adolescent girls (e.g., Hunger & Tomiyama, 2018; Keery, Boutelle, van den Berg, & Thompson, 2005; Stice, Presnell, Shaw, & Rohde, 2005; Suisman et al., 2008); fewer have examined males who report similar rates of WBT from peers (Puhl et al., 2017), or younger children, who may show signs of disordered eating as early as eight years of age (Morgan et al., 2002; Tanofsky-Kraff, Faden, Yanovski, Wilfley, & Yanovski, 2005; Tanofsky-Kraff et al., 2004). Additionally, extant literature examining links between WBT and disordered eating has largely utilized self-report measures of eating pathology (Libbey, Story, Neumark-Sztainer, & Boutelle, 2008; Suisman et al., 2008) or has examined treatment-seeking populations (e.g., King, Puhl, Luedicke, & Peterson, 2013; Tomiyama et al., 2014). More research is needed in community-based samples of boys and girls, using well-validated measures of WBT and eating behaviors.

Therefore, the current study assessed associations between WBT and disinhibited and disordered eating among non-treatment seeking youth ages 8–17y, and whether negative affect mediated these relationships. It was hypothesized that youths reporting WBT would present with greater disinhibited (i.e., emotional eating, eating in the absence of hunger) and disordered eating, and would be more likely to report LOC eating, after adjusting for relevant covariates including adiposity. Further, it was hypothesized that these associations would be mediated by negative affect (Suisman et al., 2008).

2. Materials and Methods

2.1. Participants and Procedure.

The current study is a secondary, exploratory analysis of an ongoing longitudinal observational study which began recruiting in 2015; other findings have been reported (e.g., Shank et al., 2019). Participants were healthy youth between 8–17 years, with a BMI ≥ 5th percentile adjusted for age and sex (Kuczmarski et al., 2002), recruited through physicians’ offices, newspaper and online advertisements, and posted flyers. Exclusion criteria included major medical or psychiatric conditions, recent weight loss exceeding 5% of body weight, history of pregnancy or brain injury, and regular use of medications/substances known to impact eating and/or weight. Participants completed two baseline screening visits (within one month, on average) at the National Institutes of Health Hatfield Clinical Research Center. At both visits, participants completed interviews and questionnaires (each completed once); for the second visit, participants fasted overnight and anthropometric measurements were collected. Children and parents gave written assent and consent, respectively. The study procedure was approved by the institutional review board at the Eunice Kennedy Shriver National Institute of Child Health and Human Development.

2.2. Measures

2.2.1. Anthropometric measurements (Visit 2).

Fasting weight was measured on a calibrated scale to the nearest 0.1 kg, and height was measured in triplicate on a stadiometer to the nearest 0.1 cm. BMIz-scores and percentiles were calculated using CDC growth standards to adjust for age and sex (Kuczmarski et al., 2002). Dual-energy x-ray absorptiometry (GE Lunar iDXA, GE Healthcare, Madison WI; software GE enCore 15) was used to measure adiposity.

2.2.2. Weight-based teasing (Visit 2).

The Perception of Teasing Scale (POTS) is a 6-item self-report questionnaire assessing the frequency of WBT (Thompson, Cattarin, Fowler, & Fisher, 1995). Participants were asked to rate the frequency of various experiences (e.g., People made fun of you because you were heavy) on a scale from 1= ‘never’ to 5= ‘very often.’ Total scores range from 6 to 30; higher scores indicate greater lifetime frequency of WBT. The POTS has demonstrated validity among non-treatment seeking youth (Jensen & Steele, 2010) and had excellent internal consistency in the current sample (Cronbach’s α= .91).

2.2.3. Emotional eating (Visit 2).

The Emotional Eating Scale for Children and Adolescents (EES-C) (Tanofsky-Kraff et al., 2007) is a 25-item self-report questionnaire assessing the desire to eat in response to negative emotional states (e.g., stressed out, sad), designed for youths ages 8–18. Higher scores indicate greater emotional eating. The EES-C has demonstrated good convergent validity, discriminant validity, test-retest reliability, and construct validity (Tanofsky-Kraff et al., 2007). The total score, used in the current study, showed excellent internal consistency (α= .97).

2.2.4. Eating in the absence of hunger (Visit 2).

The Eating in the Absence of Hunger Questionnaire for Children and Adolescents (EAH-C) is a 14-item self-report questionnaire assessing the frequency with which a respondent begins or continues to eat due to various factors (e.g., food looks, tastes or smells so good) despite a lack of physical hunger (Tanofsky-Kraff et al., 2008). Higher scores indicate greater eating in the absence of hunger. This questionnaire has shown good convergent validity and temporal stability in children and adolescents across weight strata (Tanofsky-Kraff et al., 2008). The total score, used in the current study, showed excellent internal consistency (α= .94).

2.2.5. Disordered eating attitudes and behaviors (Visit 1).

The Eating Disorder Examination (EDE) (Fairburn, 1993) is a semi-structured clinical interview that assesses eating-related pathology, and yields four subscales (dietary restraint, and eating, shape, and weight concerns) in addition to a global eating pathology score (the average of the subscales) which was used for the present study. The EDE also assesses LOC eating within the past three months. Participants under 12 years were administered the child adaptation (Bryant-Waugh, Cooper, Taylor, & Lask, 1996); the adult and child interviews have been combined successfully in prior studies (e.g., Elliott et al., 2010). The EDE has demonstrated good inter-rater reliability and discriminant validity in youth across weight strata (Glasofer et al., 2007; Tanofsky-Kraff et al., 2004). In the current sample, internal consistency for the global score was excellent (Cronbach’s α= .91).

2.2.6. Depression (Visit 1).

The Children’s Depression Inventory (CDI) (Kovacs & Beck, 1977) is a widely used 27-item measure of depressive symptoms within the last two weeks for children ages 7–17. Each symptom is presented with three options (e.g., I am sad once in a while / many times / all the time); higher scores indicate greater depressive symptoms. The CDI has demonstrated good discriminant validity and reliability in children (Knight, Hensley, & Waters, 1988), and showed good internal consistency in the current sample (α= .85).

2.2.7. Anxiety (Visit 1).

The State-Trait Anxiety Inventory for Children (STAI-C) (Spielberger, Edwards, Lushene, Montuori, & Platzek, 1973) trait subscale is a widely used 20-item self-report measure designed for youths ages 6–14 and commonly used with youth and adolescents through age 18 (Muris, Merckelbach, Ollendick, King, & Bogie, 2002). Participants report the frequency with which they feel anxiety-related symptoms (e.g., I get a funny feeling in my stomach.). Total scores range from 20 – 60; higher values indicate greater anxiety. The STAI-C has demonstrated good internal consistency and test-retest reliability among non-treatment seeking children (Spielberger, 1972) and adolescents (Glasofer et al., 2007), and had good internal consistency in the current study (α= .88).

2.2.8. Negative Affect.

Scores on the CDI (depression) and STAI-C (anxiety) were standardized and averaged to create a composite negative affect score (Shank et al., 2017).

2.3. Statistical Analyses

Analyses were performed with IBM SPSS 25.0 (IBM Corp, Armonk, NY). Data were screened for normality and outliers. Scores on the EES-C, EAH-C, and EDE were log-transformed to improve normality, and percent adiposity was arcsine transformed. Extreme but plausible outliers, defined as at least three standard deviations from the mean (< 2% of data points), were recoded to three standard deviations from the mean. Given the relatively low prevalence of reported WBT and a lack of variability in frequency, POTS scores were dichotomized to indicate the presence (≥1 experience) or absence of WBT. Participant characteristics across WBT groups were examined using Chi-squares or one-way analyses of variance.

Three one-way analyses of covariance (ANCOVAs) were conducted to compare WBT groups (presence vs. absence) on emotional eating, eating in the absence of hunger, and global eating pathology, adjusting for age (years), sex (female= 0, male= 1), race (non-Hispanic white= 0, other= 1), and total adiposity (%). Height was considered as a covariate but not included in final analyses, given its high correlation with age (r= .81, p< .001). A logistic regression, accounting for previously specified covariates, was conducted to assess the association between WBT and LOC eating. Three mediation models were conducted using the PROCESS macro v 3.4 for SPSS (Hayes, 2017), adjusting for covariates specified above. The models used bootstrapping with 10,000 resamples to estimate the 95% bias-corrected confidence interval (CI) for indirect effects. Models included WBT status as the independent variable, negative affect composite score as the mediator, and either the EES, EAH-C, or EDE global score as the dependent variable. Significant mediation is demonstrated whenever the confidence interval of the indirect effect (labeled “ab”) does not include 0. All analyses were repeated adjusting for BMIz-score in lieu of adiposity. All tests were two-tailed, and differences were considered significant when p-values were < .05.

3. Results

3.1. Participant Demographics

A total of 201 youths (13.1 ± 2.8 years; 54% female; 30.3% Black/African American, 9.0% Hispanic/Latinx; 10.9% reporting recent LOC eating) participated in the study and completed the POTS. Fifteen percent of respondents reported WBT (31.8% of youths with overweight/obesity and 7.4% of youths without overweight/obesity). Youths reporting WBT were older (p= .01), had greater BMIz and adiposity (ps< .001), and more depressive and anxiety symptoms (ps≤ .001) than youth who did not report WBT; they were also more likely to report recent LOC eating (p= .004). There were no significant sex differences; WBT was reported by 15.2% of boys and 15.6% of girls (p= .94). There were pronounced racial differences in the prevalence of WBT, for instance, 23.0% of Black youths and 18.2% of Asian youths reported WBT compared to 11% of White youths, although these differences were not significant (ps> .05). Participant characteristics are shown in Table 1.

Table 1.

Participant Demographics by Reported Weight-Based Teasing Status

Total Sample (n=201) WBT Reported (n=31) WBT Not Reported (n=170) p
M (SD) M (SD) M (SD)
Age (years) 13.1 (2.8) 14.2 (2.9) 12.9 (2.7) .01
BMI percentile 63.8 (28.4) 85.8 (15.0) 59.8 (28.4) < .001
BMI z-score .56 (1.04) 1.42 (.80) .40 (1.00) < .001
Emotional eating 0.6 (0.6) 0.8 (0.7) 0.5 (0.6) .02
Eating in the absence of hunger 1.6 (0.5) 1.8 (0.6) 1.5 (0.4) .002
Global eating pathology 0.3 (0.4) 0.6 (0.6) 0.2 (0.3) < .001
Depressive symptoms 6.7 (5.7) 9.9 (5.6) 6.2 (5.5) < .001
Anxiety symptoms 31.12 (7.4) 35.03 (7.7) 30.40 (7.1) .001
Negative affect composite −0.01 (0.9) 0.61 (1.0) −0.12 (0.9) < .001
% (n) % (n) % (n)
Female 54.2 (109) 54.8 (17) 54.1 (92) .94
Race .21
 White 48.3 (97) 35.5 (11) 50.6 (86)
 Black/African American 30.3 (61) 45.2 (14) 27.6 (47)
 Asian 10.9 (22) 12.9 (4) 10.6 (18)
 Multiple/Other/Unknown 10.5 (21) 6.5 (2) 11.2 (19)
Hispanic/Latinx 9.0 (18) 6.5 (2) 9.6 (16) .57
Weight Status
 Lean 67.2 (135) 32.3 (10) 73.5 (125) < .001
 Overweight 14.9 (30) 29.0 (9) 12.3 (21)
 Obesity 17.9 (36) 38.7 (12) 14.1 (24)
Loss of control (LOC) eating 10.9 (22) 26.7 (8) 8.4 (14) .004
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Abbreviations: BMI, body mass index; BMI-z, body mass index adjusted for age and sex.

Tests conducted: chi-square or analysis of variance, as appropriate. Non-transformed means and standard deviations shown for transformed variables.

3.2. Associations Between WBT, Disinhibited Eating, and Disordered Eating

After adjusting for covariates, youths reporting WBT had greater emotional eating (p= .02), eating in the absence of hunger (p= .002), and global eating pathology (p< .001). Those with WBT were significantly more likely to report recent LOC eating compared to youths without WBT [25.8% vs. 8.2%; OR (95%CI): 3.1 (1.02 – 9.54), Table 2]. Pattern and significance of results remained the same when adjusting for BMIz-score instead of adiposity (full results available upon request).

Table 2.

Bivariate Correlations between Study Variables

Variable 1 2 3 4 5 6 7 8 9 10 11 12 13
1. Presence of WBT —
2. Age .17* —
3. Sex −.01 −.08 —
4. Race/Ethnicity .11 .04 −.16* —
5. Percent adiposity .31** −.01 −.38** .13 —
6. BMI z-score .36** .02 −.08 .14* .78** —
7. Emotional Eating .17* .07 −.12 .22** .20 −.04 —
8. Eating in the Absence of Hunger .20* .27** −.15** .09 .03 .003 .40** —
9. Global eating pathology .36** .18* −.11 .08 .37** .44** .15* .27** —
10. Presence of LOC .21** .07 −.13 .06 .17* .11 .17* .26** .36** —
11. Depressive symptoms .28** .11 −.1 .17* .16* .11 .21** .34** .31** .21** —
12. Anxiety symptoms .23** .07 −.19** .04 .20** .11 .23** .37** .33** .20** .71** —
13. Negative affect composite score .29** .11 −.18** .12 .21** .13 .22** .39** .37** .23** .93** .93** —
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Abbreviations: BMI-z, body mass index adjusted for age and sex; LOC, loss of control eating; WBT, weight-based teasing.

Test conducted: Pearson’s bivariate correlations

*:

p < .05;

**:

p < .001

3.3. Mediation Analyses

3.3.1. Emotional Eating.

WBT was significantly associated with negative affect (a= .64, SE= .19, p< .001) and negative affect was significantly associated with emotional eating (b= .06, SE= .03, p= .02). After adjusting for negative affect, the direct effect of WBT on emotional eating (c’= .13, SE= .07, p= .07) was not significant. The indirect effect of WBT on emotional eating through negative affect was significant (ab=.04, SE= .02, 95%CI: 0.001 – 0.09; Figure 1; Table 4), indicating that negative affect mediated the association between WBT and emotional eating.

Figure 1.

Figure 1.

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Conceptual mediation model examining the relationships between weight-based teasing, negative affect, and disinhibited and disordered eating

Table 4.

Mediation Analyses Examining Relationships Between Weight-Based Teasing, Negative Affect, and Disinhibited and Disordered Eating

Dependent Variable a b c’ ab
Coeff. SE p Coeff. SE p Coeff. SE p Coeff. SE 95% CI
Emotional Eating .64 .19 <.001 .06 .03 .02 .13 .07 .07 .04 .02 0.001 ‒ 0.09
Eating in the Absence of Hunger .64 .19 <.001 .10 .02 <.001 .07 .05 .21 .06 .03 0.02 ‒ 0.12
Global Eating Pathology .64 .19 <.001 .07 .02 <.001 .12 .05 .01 .04 .02 0.01 ‒ 0.08
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Abbreviations: Coeff, coefficient; CI, confidence interval; SE, standard error

Note: Models adjusted for age, sex, race, and percent adiposity. a= the effect of weight-based teasing on negative affect; b= the effect of negative affect on disordered eating variables; c’= the direct effect of weight-based teasing on disordered eating variables, adjusting for negative affect, ab= the indirect effect of weight-based teasing on disordered eating variables through negative affect.

3.3.2. Eating in the Absence of Hunger.

WBT was significantly associated with negative affect (a= .64, SE= .19, p< .001) and negative affect was significantly associated with eating in the absence of hunger (b= .10, SE= .02, p< .001). The direct effect of WBT on eating in the absence of hunger was non-significant (c’= .07, SE= .05, p= .21), and the indirect effect of WBT on eating in the absence of hunger was significant (ab= .06, SE= .03, 95%CI: 0.02 – 0.12; Table 4), indicating that negative affect mediated the association between WBT and eating in the absence of hunger.

3.3.3. Global Eating Pathology.

WBT was significantly associated with negative affect (a= .64, SE= .19, p< .001) and negative affect was significantly associated with global eating pathology (b= .07, SE= .02, p< .001). After adjusting for negative affect, the direct effect of WBT on eating pathology remained significant (c’= .12, SE= .05. p= .01). The indirect effect was also significant (ab= .04, SE= .02, 95%CI: 0.01 – 0.08; Table 4), indicating mediation of negative affect in the association between WBT and global eating pathology.

3.3.4. LOC Eating.

WBT was significantly associated with negative affect (a= .64, SE= .19, p< .001); however, negative affect was not associated with LOC eating (b= .46, SE= .24, p= .06), thus the mediation model was not further analyzed.

The pattern and significance of all mediation models remained unchanged when adjusting for BMIz in lieu of adiposity.

4. Discussion

In the current study, WBT was reported by 15% of youths. Boys and girls did not differ in the rate of WBT reported, and, though not significantly different, considerably more Black and Asian youths reported WBT compared to their White counterparts. WBT was associated with disinhibited and disordered eating, even after adjusting for relevant covariates, and these associations were significantly mediated by negative affect. Furthermore, those reporting WBT were three times more likely to report recent LOC eating. The current findings extend on previous research (e.g., Major, Hunger, Bunyan, & Miller, 2014; Neumark-Sztainer, Story, & Faibisch, 1998; Puhl et al., 2013; Suisman et al., 2008) with the use of a well-validated measure of WBT, a semi-structured interview to assess eating pathology, and inclusion of a diverse sample of boys and girls of a broad age and weight range.

Affect theory (e.g., Heatherton & Baumeister, 1991) may provide context for the current findings, such that negative affect mediated the associations between WBT and emotional eating, eating in the absence of hunger, and eating pathology. Though youths reporting WBT were three times more likely to experience LOC than those not reporting WBT, LOC was not associated with negative affect. Research is warranted to further elucidate how, and for whom, these eating behaviors may function as a coping strategy to mitigate aversive emotional states caused by WBT.

Study strengths include a diverse, non-clinical sample of boys and girls across age and weight strata. An additional strength was the use of multiple measures of eating pathology, including a semi-structured clinical interview which may yield more reliable data than questionnaires (Schvey, Eddy, & Tanofsky-Kraff, 2016), and the use of a well-validated measure to assess WBT.

Though the study employed well-validated questionnaires, these measures are not without limitations. The POTS assesses teasing due to high body weight and comprises relatively high-threshold items (e.g., “people snickered about your heaviness when you walked into a room alone”), which may be less salient to youths experiencing WBT in the absence of obesity. It also may not capture more subtle experiences, such as social exclusion or comments made on social media platforms. A more comprehensive measure of WBT may confer greater accuracy, as would a measure capturing chronicity of WBT experiences; research suggests chronic victimization contributes to greater psychological consequences (Kochenderfer-Ladd & Wardrop, 2001; Zarate-Garza et al., 2017).

Given that assessing WBT and its sequelae was not a primary aim of the original study, no a priori power estimates were made for the current study aims, thus, this study should be considered exploratory. However, modeling estimates suggest the current sample size should be adequate for detecting small-to-medium effects (Fritz & MacKinnon, 2007) and post-hoc power estimates (Schoemann, Boulton, & Short, 2020) indicated sufficient power for detecting the indirect effects in the current sample. Given the low frequency of WBT in the current sample, it is possible that the imbalance in our dichotomous predictor reduced power and influenced results; future research should seek to replicate findings in samples enriched for youths reporting WBT. In addition, the cross-sectional nature of the data precludes the temporal understanding of the relationships between WBT, negative affect, and disinhibited and disordered eating. As the current study comprised healthy non-treatment seeking youth, findings may not generalize to youth with more severe eating pathology or comorbid physical health conditions.

The frequency of WBT reported in this sample (15.4%) was lower than expected given the high prevalence demonstrated in the literature (Goldfield et al., 2010; Puhl & Luedicke, 2012; Schvey et al., 2019). This may partly be due to the POTS; as discussed previously, participants experiencing more subtle forms of teasing may not have endorsed WBT on this measure. The use of single item measures and instruments assessing teasing due to weight or shape broadly, and not explicitly due to high weight per se, may also capture more youths (Menzel et al., 2010). While WBT prevalence did not differ significantly by race/ethnicity in our sample, it was highest among Black and Asian youth (23.0% and 18.2%, respectively), compared to White youth (11.3%). Potential racial and ethnic disparities warrant further exploration in larger samples, particularly given the inconsistent findings observed in prior literature (Puhl & Lessard, 2020). Furthermore, girls were not more likely to report WBT than boys, which is in contrast to some (Eisenberg, Neumark-Sztainer, & Story, 2003; Neumark-Sztainer et al., 2002; Puhl et al., 2017) but not all (e.g., Griffiths et al., 2006) prior research. As sex differences may exist in both the perception of and reaction to WBT (Menzel et al., 2010), future research should further interrogate sex differences in the prevalence and sequelae of WBT in childhood and adolescence.

In conclusion, WBT was associated with disinhibited and disordered eating among healthy youths, and these associations were mediated by negative affect. Further, those reporting WBT were three times more likely to report recent LOC eating. Of note, these relationships were observed above and beyond the contributions of demographics and adiposity. Future research should seek to replicate findings and explore moderators, such as demographic variables, weight status, and developmental stage, in larger, adequately powered samples. This is especially indicated given the wide age range of the current sample; though WBT is reported by young children, elementary school-aged youths may not be exposed to the same frequency or severity of teasing as older youths, for whom social media and peers are more influential (Puhl & King, 2013). The strength of the observed associations may also increase across development, perhaps due to chronicity of weight stigma or longer duration of overweight/obesity. Further, adolescence is a vulnerable period for the onset and exacerbation of disinhibited and disordered eating (Stice, Marti, & Rohde, 2013). Given pronounced sex differences in the timing, nature, and correlates of pubertal development (Marcotte, Fortin, Potvin, & Papillon, 2002), the influence of the interaction between pubertal development and sex in the experience and correlates of WBT warrants further study. To establish temporal associations between teasing and eating behaviors, prospective research is warranted in larger, heterogeneous samples of youth across the weight spectrum. A more nuanced understanding of the mechanisms through which WBT contributes to adverse outcomes may facilitate the development of targeted interventions, particularly during the critical periods of childhood and adolescence. The current findings, alongside prior research, indicate that continued efforts to confront and reduce WBT are warranted. In conjunction, negative affect may also serve as a potentially modifiable therapeutic target for youths reporting WBT.

Table 3a.

Unadjusted Associations of WBT with Disinhibited and Disordered Eating

Emotional Eating Eating in the Absence of Hunger Global Eating Pathology LOC Eating Presence
F (df) p F (df) p F (df) p OR (95%CI) p
WBT 5.97 (1,199) .015 8.40 (1,199) .004 30.17 (1,198) <.001 3.95 (1.49 ‒ 10.49) .006
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Table 3b.

Adjusted Associations of WBT with Disinhibited and Disordered Eating

Emotional Eating Eating in the Absence of Hunger Global Eating Pathology LOC Eating Presence
F (df) p F (df) p F (df) p OR (95%CI) p
WBT 6.04 (1, 192) .015 5.97 (1, 192) .02 12.38 (1, 191) .001 3.07 (1.00 ‒ 9.38) .049
Age 0.04 (1, 192) .85 10.04 (1,192) .002 5.05 (1, 191) .03 1.03 (.87 ‒ 1.23) .73
Sex 3.06 (1, 192) .08 4.46 (1, 192) .04 0.02 (1, 191) .89 2.13 (.73 ‒ 6.22) .17
Race 7.53 (1, 192) .01 0.45 (1, 192) .51 0.00 (1, 191) .99 1.04 (.39 ‒ 2.78) .93
Fat (%) 2.69 (1, 192) .10 1.23 (1, 192) .27 17.42 (1, 191) <.001 15.39 (.096 ‒ 2472.17) .29
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Abbreviations: LOC, loss-of-control eating; OR, odds ratio; WBT, weight-based teasing.

Test conducted: ANOVA, ANCOVA or logistic regression, as appropriate.

Global Eating Pathology score and LOC Eating Presence were ascertained through EDE interview. Variables listed under WBT in Table 3b were included as covariates in the models. For the logistic regression (LOC Eating Presence), the reference group for sex was male and the reference group for race was non-Hispanic white.

Acknowledgments

This research was supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (ZIAHD00641 to JAY). The funding sources had no involvement in study design, in the collection, analysis and interpretation of data, in the writing of the report, or in the decision to submit the article for publication.

Footnotes

Publisher's Disclaimer: Disclaimers: The authors have no conflicts of interest to declare. The opinions and assertions expressed herein are those of the authors and are not to be construed as reflecting the views of Uniformed Services University or the United States Department of Defense.

Trial Registration: ClinicalTrials.gov ID#: NCT02390765

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