Association between body mass index and health outcomes among adolescents: the mediating role of traditional and cyber bullying victimization

Association between body mass index and health outcomes among adolescents: the mediating role of... Background: It is well-documented that obese children and adolescents tend to experience a variety of negative physical and psychological health consequences. Despite the association between obesity and physical and psychological well-being, few studies have examined the role of off-line and on-line forms of bullying victimization in this link. The main objective of the current study is to investigate the direct and mediating effects of traditional and cyber bullying victimization in explaining the relationship between the body mass index (BMI) and physical/psychological distress. Methods: A nationally representative sample of 10,160 school children (mean age = 12.95 ± 1.75) were collected from the 2009 Health Behavior in School-aged Children (HBSC) study. Data were collected on body mass index, physical and psychological health, bullying victimization experience, and demographic information. A seemingly unrelated regression (SUR) was employed to assess and compare the indirect effects in multiple mediation models. Results: While a significant direct association was found between BMI and both physical and psychological health, the indirect effect of BMI on physical distress was significant only via traditional bullying victimization. Both forms of bullying victimization had a mediating impact between BMI and psychological distress. However, the indirect effect on psychological distress was manifested through a negative mediating role of cyberbullying victimization. The negative relation between cyberbullying victimization and psychological distress warrants further exploration. Conclusions: Obesity represents a serious risk to adolescent health and well-being, both physically and psychologically. If becoming a victim of traditional bullying mediates (specifically exacerbates) the level of physical and psychological distress among obese and overweight adolescents, health professionals need to focus on raising awareness of the importance of weight-based victimization for children and adolescents with obesity. School administrators and teachers could increase the efforts to identify school-age children who are stigmatized for their weight and recommend coping strategies for distressed victims of traditional and cyberbullying. Keywords: Obesity, Body mass index, Physical distress, Psychological distress, Traditional bullying victimization, Cyberbullying victimization, Weight-based victimization * Correspondence: sjjeong@uta.edu University of Texas at Arlington, 701 S. Nedderman Drive, Arlington, TX 76019, USA Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Lee et al. BMC Public Health (2018) 18:674 Page 2 of 12 Background significant relationship between being obese and the odds of Obesity is one of the leading public health concerns in being bullied among sixth grade children, after controlling the United States, presenting a considerable threat to for sociodemographic characteristics [19]. Given the wide- the well-being and health of school-aged youth. Recent spread bias towards obesity, overweight children were more statistics illustrate that obesity rate remains high among likely to experience weight-specific teasing perpetrated by children and adolescents: while about 1 in 5 reported to peers in general compared to non-overweight children [29]. be obese or overweight based on the body mass index More specifically, children have witnessed their over- (BMI), hereafter referred to as BMI, those aged from 12 weight or obese peers to experience teasing in public to 19 years with extreme obesity increased to slightly area and during physical activities, exclusion from social over 9% during the past two decades [1]. Such preva- activities, spreading of negative rumors, verbal threats lence of obesity may lead to deleterious health problems, and physical harassment [30–32]. This appears to be physically [2, 3] and psychosocially [4–6]. consistent across gender; both obese boys and girls had Obesity in childhood and adolescence has been linked a higher probability of becoming victims of overt forms to a wide array of physical health outcomes. Specifically, of bullying (e.g. hitting, shoving, name-calling) than their obesity-related physical health symptoms include, but not average weight peers [33]. However, other research has limited to, headaches, stomachaches, somatic complaints, revealed that while females were primarily victims of sleep difficulties, and school/social functioning [7–9]. verbal and relational bullying, males were more likely to School children and adolescents with obesity also suffer be victims of all types (including verbal, physical, social from psychological and emotional problems such as exclusion, rumor spreading, and cyber bullying) [34]. depression [10], anxiety [11], low self-esteem [12], and Despite only a few empirical findings, the stigmatization lack of emotional support and cognitive stimulation [13]. of being obese or overweight and risk for peer victimization Further, obesity during childhood and adolescence has are evident in cyberspace. In a study using a sample of been shown to be stigmatizing and likely to result in school adolescents seeking weight loss treatment, more social adversity. There is a strong bias and prejudice than half of the participants reported that they experienced towards school children with obesity [14]. Obese children weight-based cyberbullying victimization via computers or are perceived as the least favorable classmates by their cell phones [28]. While 61% of these youth have encoun- peers in school [15] and often labeled with various tered on-line posting of embarrassing content, 59% have negative stereotypes [16]. The weight-based prejudice from received mean text messages, e-mails, or instant messages. peers may be formed as early as three years of age [17]. According to a more recent study of patients in residential Upon entering elementary school, obese and overweight facilities for severe obesity, obese adolescents were signifi- youth are likely to experience weight-related judgement cantly more likely to be bullied via the Internet compared and social outcomes such as rejection from peers or loss to their normally weighted peers [29]. Furthermore, body of friends [18–20]. In addition, research indicates that dissatisfaction is correlated with cyberbullying victimization; stigma and attitude based on weight bias could originate youth who are victims of cyberbullying are twice as likely to from educators such as teachers [21, 22]orparents and perceive one’s body to be ‘too fat’ compared to those who siblings [23]. have not been victimized [30]. Given the stigma and bias The weight-based stigma and hostility is also pervasive associated with obesity and the greater visibility of offensive in the on-line domain. A qualitative analysis of social comments or images via social media [25, 31, 32], weight- media content (e.g. Twitter) illustrates a prominent theme based victimization in online settings can be detrimental to of offensive and prejudiced attitude and perception the psychological and physical health of adolescents. towards the notion of obesity [24]. Among a wide range of Prior studies have shown that adverse outcomes and stigmatizing content, obese individuals are perceived responses are associated with weight-based victimization largely as gluttonous, unattractive, and sedentary [25]. among school children. While adolescents who have been Based on a person’s weight or body size, youthful victims victims of weight-based teasing or bullying tend to feel are stereotyped in a discriminatory, biased manner. depressed, sad, angry, afraid, and dissatisfied with their body, In addition to biased perceptions of one’s weight, prior some are more likely to have negative reactions in and research suggests that being obese or overweight contributes outside school such as avoidance strategies, binge eating, to the likelihood of becoming a victim of traditional bullying skipping schools, poor academic performance in the event [26]. Prior studies examining the impact of BMI on peer of teasing or bullying by peers [33]. Traditional bullying victimization found that overweight and obese children were victimization is found to be associated with poor physical more likely to be victimized by specific forms of bullying health, including somatic symptoms and withdrawn (verbal, relational, physical) compared to those with normal behaviors [34, 35]. Similarly, cyberbullying negatively weight [27, 28]. A related study, based on reports from impacts the emotional and psychosocial well-being of those teachers, mothers, and student themselves, showed a who are victimized. Specifically, victims of cyberbullying can Lee et al. BMC Public Health (2018) 18:674 Page 3 of 12 suffer from social anxiety [36], depressive symptoms [37], Children (HBSC) survey as the key source of our ana- decreased self-esteem [38], suicidal thoughts [39], emotional lysis. This nationally representative data, collected from distress [40], sadness [41], and angry feelings [42]. Moreover, 42 countries in collaboration with the World Health being victimized on-line undermines one’s academic Organization, provides detailed information on health- performance in school [43], and further triggers problematic and school violence-related behaviors [53]. Of the behaviors such as truancy [38], alcohol use and weapon respondents, the mean age was 12.9, whereas 51.4% were carrying [44]. Furthermore, obese adolescents who have been boys and 48.8% were white. It must be noted that some victims of cyberbullying showed a higher level of suicidal of the variables in our analysis had 4 to 5% of missing ideation compared to their peers with normal weight [29]. responses. Missing values must be properly dealt with Notwithstanding findings indicating a strong relationship due to the fact that improper handling could yield biased between bullying victimization and physical or psycho- coefficients [54]. Following an analysis of missing data, logical health, only a handful of studies have examined the the results confirmed that the missing observations for longitudinal relationship between these factors. Involve- most of the key measures under study are missing not at ment in traditional and cyber forms of bullying was found random. Instead of a multiple imputation to generate to be related to mental health and psychosocial problems probable responses, cases with missing data were listwise such as depressive and emotional symptoms, social anxiety, deleted. Among the 12,642 respondents who completed ADHD symptoms, and lower levels of well-being [45–50]. the survey through multi-stage sampling, 2482 were Similarly, minimal attention has been devoted to the lon- excluded based on missing information. The final sample gitudinal investigation of obesity and overweight with yielded 10,160 children. bullying behaviors. While a significant association between childhood obesity and the likelihood of being bullied was Measures observed [19] among sixth grade children, bullying Physical and psychological distress victimization during adolescence was linked to an in- We focused on two health related measures as out- creased risk of obesity and higher BMI when reaching comes: i) physical distress and ii) psychological distress. young adulthood [51, 52]. The question emerging from The physical distress scale (α = .65) consists of three these longitudinal findings concerns whether bullying items that measure the extent of various pain related victimization could be mediating the relationship between physical conditions in the last six months: (1) “How weight status and physical and psychological outcomes. often have you had the headaches,” (2) “How often have To date, no studies have examined the mediating role you had the stomachaches,” and (3) “How often have of bullying victimization in the relationship between you had the backaches.” Additionally, the psychological obesity and both physical and psychological distress. distress scale (α = .75) was created by summing five Considering that adolescent obesity is correlated with a items that reflect respondents’ psychological health in greater likelihood of being victimized, understanding the the last six months. These items are: (1) “How often effect of victimization, both off-line and on-line, on one’s have you had the feeling low?” (2) “How often have you level of physical and psychological distress would be of had the irritability or bad temper?” (3) “How often have particular value in developing treatments for victims to you had the feeling nervous?” (4) “How often have you cope with their distress. The current study addresses the had the difficulties in getting to sleep?” and (5) “How following research questions. often have you had the feeling dizzy?” Response options for each of these items ranged from 0 (rarely or never) 1) To what extent do overweight and obese youth to 4 (about every day) during the last six months. Both experience traditional and cyberbullying physical and psychological distress scales were coded so victimization, compared to normal weight youth? that a higher score indicates a lower level of physical / 2) To what extent do overweight and obese victims psychological distress in the last six months. of traditional or cyberbullying experience physical and psychological distress compared to normal Traditional and cyber bullying victimization (mediator variables) weight youth? The current study examines the indirect effects of obesity 3) Does becoming a victim of either traditional or on health-related outcomes by investigating the mediating cyberbullying mediate the relationship between influence of traditional and cyberbullying victimization. BMI and physical / psychological distress? First, traditional bullying victimization is a seven-item measure (α = .93) that assesses the aspects of physical and Methods emotional victimization. These measures were adopted Data collection from the previous [55]. Respondents indicated how often Data used in the current study was collected from the they have been bullied at school during the past couple 2009 U.S. version of the Health Behavior in School-Aged months: (1) “I was called mean names, was made fun of, Lee et al. BMC Public Health (2018) 18:674 Page 4 of 12 or teased in a hurtful way,” (2) “Other students left me out Gender (male = 1), age (in years), ethnicity (Hispanic = 1), of things on purpose, excluded me from their group of and race (White = 1) were included in this study. The five friends, or completely,” (3) “I was hit, kicked, pushed, categories – African-American (17.1%), Asian (3.7%), shoved around, or locked indoors,” (4) “Other students American Indian or Alaska Native (1.8%), Native Hawaiian told lies or spread false rumors about me and tried to or Other Pacific Islander (0.9%), two or more races (6.5%), make others dislike me,” (5) “I was bullied with mean and other (18.9%) – were collapsed into non-White. Mean names and comments about my race or color,” (6) “I was scores, standard deviations, and ranges for all variables are bullied with mean names and comments about my presented in Table 1. religion,” and (7) “Other students made sexual jokes, comments or gestures to me.” The traditional bullying Statistical analysis victimization scale was created using the items above and The overarching aim of this study was to explore the im- coded so that a higher score indicates a higher frequency pact of overweight and obesity on physical and psycho- of victimization at school. Second, cyberbullying victimization logical distress and whether these weight-based effects was a four-item measure (α = .90) assessing an individual’s occur indirectly through traditional and cyberbullying victimization experience using a computer-mediated com- victimization. A seemingly unrelated regression (SUR) munication. These measures were adopted from a study of was used to simultaneously assess and compare the Olweus [56]. Respondents were asked to indicate how mediating effects of two types of bullying victimization frequently they have been bullied during the past couple in the link between obesity and both physical and months: (1) “I was bullied at school using a computer or e- psychological distress. The aforementioned relationships mail messages or pictures,” (2) “I was bullied at school using will be empirically tested using multiple mediator a cell phone,” (3) “I was bullied outside of school using a models [57]. Since independent variables differ from one computer or e-mail messages or pictures,” and (4) “Iwas equation to the next, the use of SUR, allowing to bullied outside of school using a cell phone.” Each measure compare multiple equations simultaneously, ensures statis- of victimization was based on a five-point Likert scale tical efficiency in the current research [58]. Furthermore, response ranging from (1) none during the past several SUR is well suited for estimating and comparing indirect months to (5) several times a week. For the purpose of the effects in multiple categories (i.e., BMI categories) [59]. current study, the cyberbullying victimization scale was cre- ated by summing four items and coded so that a higher score Table 1 Descriptive Statistics of Study Variables (n = 10,160) indicates a more frequent victimization via the Internet. Variable Range or Mean or Standard Frequency Percentage Deviation Body mass index (BMI) Dependent Variables As an indicator of obesity, body mass index (BMI) was a a a Physical Distress 0~12 2.95 2.87 computed based on self-reported measures of height and a a a Psychological Distress 0~20 5.39 4.75 weight for each respondent [55]. The BMI percentiles were computed based on the formula [Weight(lbs)/ Independent Variables [Height(inches)*Heights(inches)] * 703. Given that the BMI (Body Mass Index) (%) formula was mainly aimed to compute the adult BMI, b b Healthy Weight 6465 63.63 BMI percentiles were calculated by taking into account b b the respondent’s gender and age for accurate interpretation. Underweight 432 4.25 b b BMI percentiles were then coded into four categories based Overweight 1855 18.26 on the criteria established by the Center for Disease b b Obese 1408 13.86 Control: (1) underweight – less than 5th percentile; (2) healthy weight – between 5th and 85th percentile; (3) at Mediate Variables risk of overweight – between 85th and 95th percentile; and a a a Traditional Victimization 0~28 2.69 4.79 (4) overweight – greater than 95th percentile. For the a a a Cyber Victimization 0~16 .58 2.18 current analyses, the healthy weight between 5th and 85th percentile was used as a reference category to explore the Control Variables effect of overweight and obesity. b b Gender (1=Male) (%) 5227 51.45 a a a Age 10~17 12.95 1.75 School-related and demographic characteristics b b As demonstrated by prior research that social-demographic Ethnicity (1=Hispanic) (%) 2916 28.70 b b characteristics are significant indicators of bullying Race (1=White) (%) 4961 48.83 victimization and school-life related factors, we also a Note. The range, mean, and standard deviation are reported incorporated demographic variables as control variables. The frequency and percentage are reported Lee et al. BMC Public Health (2018) 18:674 Page 5 of 12 Specifically, we estimated four sets of models: (1) the effect CFI > .95 were used to identify a satisfactory or acceptable of BMI on the outcome measures (i.e., physical and psycho- model fit. After we set all structural paths with covariance logical distress); (2) the effect of BMI on the mediators (i.e., and mediators, the fit for this model was: SRMR = .013; traditional and cyber bullying victimization); (3) the effect of RMSEA = .036 (p-value = .85; 90% C.I. = .030~.043); the mediators on outcome measures; and (4) the indirect CFI = .990. The examination of model fit indices effects of BMI on outcome measures. Additionally, Sobel- suggested that the model fitted the data well. Goodman tests was applied to statistically test for the pres- ence of mediation. To generate standard errors and signifi- Results cance levels of the indirect effects, we utilized 1000 bootstrap Descriptives replications. All analyses were performed using Stata SE 13 We report summary statistics for physical and psycho- to estimate our seemingly unrelated models. Although the ef- logical distress, traditional and cyber bullying victimization, fects of BMI on bullying victimization and negative conse- and other control variables used in the current study (See quences of bullying victimizations are well-documented, very Table 1). The mean physical distress score was 2.95 few studies to date have investigated the mediating effects of (sd = 2.87) and the mean psychological distress score bullying victimization (traditional and cyber) among school was 5.39 (sd = 4.75). Among the study participants in children with obesity in the context of distress. our analytic sample, 63.6% (n = 6465) were categorized as healthy weight, 4.3% (n = 432) as underweight, 18.3% Additional analysis (n = 1855) as overweight, and 13.9% (n = 1408) as obese. To simultaneously examine the empirical relationships With regards to bullying victimization, the mean score for among the variables under investigation, structural traditional victimization score was 2.69 (sd = 4.79), and equation modeling (SEM) was also employed by using the mean score for cyber victimization was .58 (sd = 2.18). maximum-likelihood-estimation in Stata 13.1 [60]. We However, these two mean scores reflected a relatively carefully examined a number of different model fit indices lower degree of victimization compared to other studies. to assess identification and stability. Since chi-square statis- Concerning demographic covariates, the final sample of tics assessing the fit between the matrix of observations 10,160 students showed a mean age of 12.95 years and the matrix generated by the model is sensitively influ- (sd = 1.75). While the majority of the sampled students enced by large sample size [61], we paid less attention. were non-Hispanics (71.3%), males accounted for 51.5%. Instead, we considered: standardized root-mean-square residual (SRMR); root-mean-square-error of approximation Bivariate correlations (RMSEA) with 90% confidence interval [62]; and compara- As a preliminary analysis, we conducted a bivariate tive fit index (CFI) [63]. For study criterion, the combin- correlation analysis (See Table 2). As expected, BMI was ation of SRMR < .08; RMSEA < .08 with p-value > .05; and significantly related to both physical and psychological Table 2 Correlations of Covariates (n = 10,160) 12 34 56 78 9 Dependent Variables 1. Physical Distress 1 2. Psychological Distress .62*** 1 Independent Variables 3. BMI (Body Mass Index) .06*** .06*** 1 Mediate Variables 4. Traditional Victimization .22*** .29*** .06*** 1 5. Cyber Victimization .12*** .13*** .02** .61*** 1 Control Variables 6. Gender (1=Male) (%) −.16*** −.15*** .08*** −.01 −.01 1 7. Age .11*** .10*** −.05*** −.06*** .02*** .04*** 1 8. Ethnicity (1=Hispanic) −.05*** −.02 .07*** .02 .04*** .01 −.01 1 9. Race (1=White) .05*** −.01 −.09*** −.04*** −.04*** .02 −.03*** −.41*** 1 Note. **p < .05. ***p < .01 Lee et al. BMC Public Health (2018) 18:674 Page 6 of 12 distress (r = .06 and .06, respectively). Additionally, with both physical and psychological distress (b = .15 and traditional bullying victimization and cyber bullying .36, p < .01, respectively). victimization were negatively correlated with physical distress (r = .22 and .12, respectively) and psychological Mediating effect of bullying victimization distress (r = .29 and .13, respectively). Notably, BMI was The SUR estimations with traditional and cyber bullying positively related to both traditional and cyber victimization as mediators are presented in Table 4.The victimization (r = .06 and .02, respectively). mediation results showed a significant indirect effect of the overweight (b = .07, p < .01) and obesity (b = .10, p < .01) on Hypothesized mediation models physical distress through traditional bullying victimization, Impact of BMI on victimization and distress but not through cyberbullying victimization. For the Table 3 indicates the main direct effects of BMI on psychological distress, we did see a significant indirect effect mediator variables (i.e., traditional victimization and cyber of the overweight (b = .17, p <.01) and obesity (b = .27, victimization) and outcome variables (i.e., physical distress p < .01) on psychological distress through traditional and psychological distress) using seemingly unrelated bullying victimization. Unexpectedly, while there was no regression models. First, we examined whether weight indirect effect of the weight status on physical distress status predicts the probability of bullying victimization. through cyberbullying victimization, we found a mediating The results indicated that overweight children have a higher effect (b = −.02, p < .05) for psychological distress. As risk than healthy weight children of becoming a victim of shown in Table 4, the significance of the indirect effects of traditional bullying (b = .47, p <.01). Similarly, obesity was traditional and cyber bullying victimization were examined positively associated with risk of being a victim of traditional using Sobel-Goodman tests [64]. These tests indicated that bullying (b = .70, p < .01). Next, we examined whether the indirect effects linking weight status with physical weight status predicts physical and psychological distress. distress through traditional bullying victimization were The results revealed that obese and overweight children significant (z = 5.90, p < .01), accounting for 24% of the have been shown to have poorer physical and psychological effect of weight status on physical distress. For psycho- distress than healthy weight children (b = .27 and .38, logical distress, Sobel-Goodman tests also indicated that p < .01, respectively). Moreover, obesity has been found to the indirect paths linking weight status with psychological be positively associated with physical and psychological distress via traditional bullying victimization were signifi- distress (b = .56 and .67, p < .01, respectively). Finally, cant (z = 6.13, p < .01), accounting for 36% of the effect of traditional bullying victimization was positively associated weight status on psychological distress. Table 3 Direct Effects SUR (n = 10,160) Model 1 Traditional Victimization Cyber Victimization Physical Distress Psychological Distress b (S.E.) b (S.E.) b (S.E.) b (S.E.) Independent Variables BMI (Body Mass Index) Underweight .50(.24)** −.01(.11) −.17(.15) .23(.25) Overweight .47(.12)*** .06(.05) .27(.08)*** .38(.13)*** Obese .70(.14)*** .11(.06) .56(.09)*** .67(.14)*** Mediate Variables Traditional Victimization .15(.01)*** .36(.01)*** Cyber Victimization −.02(.02) −.17(03)*** Control Variables Gender (1=Male) −1.10(.06)*** −1.76(.09)*** Age .23(.02)*** .33(.03)*** Ethnicity (1=Hispanic) −.12(.07) .08(.12) Race (1=White) .34(.06)*** .18(.10) Note. a. Healthy weight is the reference category **p < .05. ***p < .01 Lee et al. BMC Public Health (2018) 18:674 Page 7 of 12 Table 4 Direct and Indirect Effects Comparisons SUR (n = 10,160) Physical Distress Psychological Distress b S.E. z Sobel z (% of total effect) b S.E. z Sobel z (% of total effect) Direct Effects BMI (Body Mass Index) Underweight −.17 .15 −1.15 .23 .25 .93 Overweight .27*** .08 3.61 .38*** .13 2.99 Obese .56*** .09 6.56 .67*** .14 4.76 Bullying Victimization Traditional .15*** .01 18.32 .36*** .01 27.53 Cyber .02 .02 −1.05 −.17*** .03 −5.66 Indirect Effects BMI on Distress through Traditional Victimization 5.90*** (24%) 6.13*** (36%) Underweight .08** .04 2.03 .15 .09 1.62 Overweight .07*** .02 3.72 .17*** .05 3.67 Obese .10*** .02 4.80 .27*** .05 5.15 BMI on Distress through Cyber Victimization 2.33** (5%) 2.49** (7%) Underweight .01 .01 .06 .01 .02 .40 Overweight −.01 .01 −.75 −.01 .01 −.87 Obese −.01 .01 −.90 −.02** .01 −1.99 Note. a. Healthy weight is the reference category **p < .05. ***p < .01 SEM results models, all of the estimates were in the same direction Following the initial SUR analysis and inspection of the and of similar magnitude. model fit indices for our models, we used SEM to examine As can be seen in Figs. 1 and 2, the test of mediation the direct relationship between BMI, physical distress, showed a significant indirect effect of BMI on psycho- psychological distress, and two mediators. Similar to the logical distress through victimization of both traditional SUR analysis, the SEM results indicated that significant and cyber bullying (total indirect = .08; total direct = .30; correlations were in the same direction. After the initial z = 6.81; p < .01) and these indirect effects accounted for direct effect analysis, we examined the indirect effects – 27% of the effect of BMI on psychological distress. As il- whether BMI leads to psychological and physical distress lustrated in Figs. 3 and 4, the results also showed that through increases in the risk of traditional and cyber the indirect effects of traditional and cyber bullying bullying victimization. Consistent with the SUR mediation victimization were significant; therefore, bullying Fig. 1 Traditional/Cyber Victimization Mediators of Obesity and Physical Distress Lee et al. BMC Public Health (2018) 18:674 Page 8 of 12 Fig. 2 Traditional/Cyber Victimization Mediators of Obesity and Psychological Distress victimization significantly mediated the association be- research shows that children with obesity had a greater tween BMI and physical distress (total indirect = .03; likelihood of exhibiting poor physical and psychological total direct = .19; z = 7.47; p < .01), while the model ex- health outcomes [2, 7, 8, 12, 13, 67]. Regarding the plained 16% of variance in physical distress. impact of victimization on distress, traditional bullying victimization was positively linked to physical and Discussion psychological forms of distress. This is consistent with A number of findings emerged from the current study. previous research and suggests that youth who have First, obesity, measured by BMI, showed a significant been victims of traditional bullying are more likely to direct effect on one of the two types of victimization – experience a variety of physical and psychological symp- traditional bullying. In line with prior research [26–28, toms [33–35]. Yet, an unexpected finding is the negative 65, 66], obese or overweight youth are significantly more effect of cyberbullying victimization on psychological likely to be victimized by bullying compared to those distress. Unlike prior studies [36, 40, 41], our study who are not obese. Contrary to the earlier findings found that youth who have been a victim of cyberbullying suggesting a positive association between obesity and are less likely to experience psychosocial distress. One cyberbullying victimization [28, 29], there was not a possible explanation may be that individuals may be significant effect of BMI on the probability of being involved as both victims and perpetrators of cyberbullying bullied on-line. and also engage in aggressive behavior as a coping or In light of previous research documenting the effect of defense strategy [68–70]. This may contribute to lower obesity on physical and psychological distress, statistical levels of psychological distress. Moreover, youth with high evidence was found for a significant link between BMI levels of self-control showed greater levels of resiliency and both forms of distress. In general, prior obesity and lower levels of distress in response to real world or Fig. 3 SEM: Direct and Indirect Effects of BMI on Physical Distress; The figure shows that the proportion of total “BMI” effect mediated via “Traditional” and “Cyber” Victimization was .16. Circles represent observed variables, and straight arrows connect the observed variables. Bold lines represent significant paths, and dotted lines represent nonsignificant paths. All significant parameters are significant at the p <.001 level Lee et al. BMC Public Health (2018) 18:674 Page 9 of 12 Fig. 4 SEM: Direct and Indirect Effects of BMI on Psychological Distress; The figure shows that the proportion of total “BMI” effect mediated via “Traditional” and “Cyber” Victimization was .27. Circles represent observed variables, and straight arrows connect the observed variables. Bold lines represent significant paths, and dotted lines represent nonsignificant paths. All significant parameters are significant at the p < .001 level cyberbullying [71]. Finally, peers may serve as a protective to) the negative content made by others, which may be role in buffering the negative link between cyberbullying accompanied by reduced distress. Finally, the children in victimization and distress [72]. the current sample may not be considered “pure” victims. Notably, mediating effects of bullying victimization were Since physical dominance is less visible in on-line observed using the SUR approach. Only traditional bully- interactions, it is possible that victims of traditional ing victimization mediated the link between BMI and bullying could engage in aggressive behaviors towards physical distress. In addition, the association between BMI those who have bullied them via electronic means in and psychological distress among youth was mediated by seeking retribution [75, 76]. both forms of victimization. While traditional bullying victimization had a positive mediating effect on the BMI- Strengths and limitations distress link, cyberbullying victimization indicated a nega- The current study has a number of limitations. First, the tive effect in the analysis. These indirect effects imply that results do not allow to draw causal inferences due to the obese or overweight youth who have been victims of trad- cross-sectional nature of this study. Longitudinal studies itional bullying would justifiably experience a higher level are needed to disentangle the temporal relationship of physical and psychological distress. Overall, these re- between the variables under study. Second, the measure sults offer evidence that there may be further mediating for cyberbullying victimization may not accurately repre- link between BMI, bullying victimization and distress, sent the ways in which an individual may be harassed or which warrants further exploration. bullied via the Internet. Cyberbullying could be facili- The negative mediating effect of cyber victimization tated via a wide range of on-line platforms such as chat on the association between BMI and psychological rooms, emails, text messages, mobile phone call, photo distress could be explained in several ways. First, the or video clip, and social media [77–79]. Future research measures for cyberbullying victimization may not fully should consider a more comprehensive measure of cyber capture the intricacies of how technology could be victimization to allow for a thorough evaluation of the subverted to damage a victim’s reputation, self-esteem, on-line victimization experience. At the same time, there or friendship. Rather, it merely reflects the location of is need to establish a commonly agreed definition of bullying using a computer or cell phone. Moreover, cyber victimization for ensuring reliability to some victimization may not necessarily lead to emotional degree [80]. In addition, since the current study focused distress if it takes place in virtual realm [73]. Given the only on victims of weight-based bulling, future research unique properties of online environments [74], it is could benefit from exploring the subgroup of bully- plausible that obese or overweight victims may receive victims, who have been found to be more common in social support from bystanders via social media (e.g. cyberbullying [81] as opposed to traditional bullying [82, Facebook), which, in turn, could neutralize negative 83]. Lastly, the present study utilized self-reported ques- comments from peers during weight-based cyberbullying tionnaire and hence is subject to response bias. incidents [31]. For instance, if a youth receive a demeaning Our study offers several strengths. First, the dataset used message or image related to obesity or overweight, an in this study consists of a nationally representative sample empathetic bystander could dissent (rather than conform of U.S. youth, which enhances generalizability and Lee et al. BMC Public Health (2018) 18:674 Page 10 of 12 statistical power and lessens selection bias. Second, despite Endnotes its deficiency, BMI is considered to be well-validated and Participants were given a definition of “being bullied” as widely used by obesity researchers, and further proven follows: A student is being bullied when another student, to be of good predictive value [84–86]. Third, the use or a group of students, say or do nasty or unpleasant things of seemingly unrelated regression (SUR) and Sobel- to him or her. It is also bullying when a student is teased Goodman tests allows one to assess the extent and repeatedly in a way he or she does not like or when they significance of the mediating effects of traditional and are deliberately left out of things. But it is not bullying cyber victimization in the link between weight status when two students of about the same strength or power and both types of distress. Furthermore, the present argue or fight. It is also not bullying when a student is findings offer useful insights into the mechanism teased in a friendly and playful way. indirectly linking indicators of obesity to physical and psy- According to the Center for Disease Control’s BMI chological distress via victimization. Yet, future research is category, the raw BMI score for boys and girls is different. needed to untangle the impact of on-line victimization on However, the CDC adjust raw BMI score into BMI the link between obesity and psychological distress. categories based upon centralized-percentiles cutoffs regardless of participants’ sex. (See BMI-for-age charts). Therefore, the interpretation of BMI is not different. Conclusions Abbreviations The primary aim of this study was to examine the direct ADHD: Attention Deficit Hyperactivity Disorder; BMI: Body Mass Index; and indirect effect of obesity on two forms of distress CFI: Comparative Fit Index; RMSEA: Root Mean Square Error of Approximation; SD: Standard Deviation; SEM: Structural Equation Modeling; SRMR: Standardized (physical and psychological) among U.S. youth. Our Root Mean Square Residual; SUR: Seemingly Unrelated Regression findings affirm that obese and overweight adolescents are more likely to be victims of traditional victimization and Acknowledgements Not applicable. also more likely to experience physical and psychological distress compared to those with healthy weight. As an Funding additional finding, victimization can exacerbate the effect of Not applicable. obesity on the level of distress, suggesting traditional Availability of data and materials victimization as an important mediator in the association The datasets generated and/or analyzed during the current study are between obesity and physical/psychological distress. The available in the ICPSR repository: http://www.icpsr.umich.edu/icpsrweb/ current findings underscore the need to raise awareness for NAHDAP/studies/34792 the detrimental impact of victimization occurring off-line in Authors’ contributions school classrooms or playgrounds on the physical and BL has made substantial contributions to the conception and design of the psychological distress among obese and overweight youth. study and has taken an active role in drafting and revising the manuscript critically for important intellectual content. SJ was in charge of the analysis Bullying victimization represents a risk factor for youths’ and interpretation of data, and MR provided valuable insights into the psychosocial well-being. Parents and school administrators interpretation of the results. All authors read and approved the final can develop educational interventions to raise the aware- manuscript. ness on weight stigma and stereotypes as well as adverse Ethics approval and consent to participate consequences of weight-based bullying. Given that weight- This study is based on secondary data and no contact was made with any related stigma and teasing occur in school settings among individuals. In addition, all names and any other personally identifying peers, school-based interventions can be implemented to information was removed from the original research team. Rather, they randomly assign case number and it does not allow linkage to any name or reduce thestigmaand bias associated with obesity and identifying information. Hence, the data is anonymous and consent form is overweight and address the ways in which families and not required. This study complies with national guidelines and provide a communities can come together to educate children to be reference which supports this. A local ethics committee ruled that no formal ethics approval was required in this particular study. tolerant of differences in weight and body size. In line with this, youths’ attitudes toward body image have been found Consent for publication to be influenced by social norms [87]. Efforts to reduce Not applicable. weight stigma and discrimination should focus on class- Competing interests room instructions to improve adolescents’ attitudes toward The authors declare that they have no competing interests. peers with obesity, school policies prohibiting weight-based bullying, and programs to promote an environment that Publisher’sNote recognizes and supports the diversity of cultural foodways Springer Nature remains neutral with regard to jurisdictional claims in [88]. Hence, a comprehensive school-wide approach is published maps and institutional affiliations. necessary to adequately address the ongoing challenges that Author details are faced in the prevention of weight-based victimization 1 Central Connecticut State University, 1615 Stanley Street, New Britain, CT, among youth. USA. University of Texas at Arlington, 701 S. Nedderman Drive, Arlington, TX Lee et al. BMC Public Health (2018) 18:674 Page 11 of 12 76019, USA. Texas A&M University - San Antonio, One University way, San 27. Janssen I, Katzmarzyk P, Ross R. Waist circumference and not body Antonio, TX 78224, USA. mass index explains obesity-related health risk. The Amer J Clin Nutri. 2004;79:379–84. Received: 4 August 2017 Accepted: 28 March 2018 28. Puhl R, Peterson J, Luedicke J. Weight-based victimization: bullying experiences of weight loss treatment–seeking youth. Pediatrics. 2013;131:1–9. 29. Desmet A, Deforche B, Hublet A, Tanghe A, Stremersch E, De Bourdeaudhuij I. 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Association between body mass index and health outcomes among adolescents: the mediating role of traditional and cyber bullying victimization

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Abstract

Background: It is well-documented that obese children and adolescents tend to experience a variety of negative physical and psychological health consequences. Despite the association between obesity and physical and psychological well-being, few studies have examined the role of off-line and on-line forms of bullying victimization in this link. The main objective of the current study is to investigate the direct and mediating effects of traditional and cyber bullying victimization in explaining the relationship between the body mass index (BMI) and physical/psychological distress. Methods: A nationally representative sample of 10,160 school children (mean age = 12.95 ± 1.75) were collected from the 2009 Health Behavior in School-aged Children (HBSC) study. Data were collected on body mass index, physical and psychological health, bullying victimization experience, and demographic information. A seemingly unrelated regression (SUR) was employed to assess and compare the indirect effects in multiple mediation models. Results: While a significant direct association was found between BMI and both physical and psychological health, the indirect effect of BMI on physical distress was significant only via traditional bullying victimization. Both forms of bullying victimization had a mediating impact between BMI and psychological distress. However, the indirect effect on psychological distress was manifested through a negative mediating role of cyberbullying victimization. The negative relation between cyberbullying victimization and psychological distress warrants further exploration. Conclusions: Obesity represents a serious risk to adolescent health and well-being, both physically and psychologically. If becoming a victim of traditional bullying mediates (specifically exacerbates) the level of physical and psychological distress among obese and overweight adolescents, health professionals need to focus on raising awareness of the importance of weight-based victimization for children and adolescents with obesity. School administrators and teachers could increase the efforts to identify school-age children who are stigmatized for their weight and recommend coping strategies for distressed victims of traditional and cyberbullying. Keywords: Obesity, Body mass index, Physical distress, Psychological distress, Traditional bullying victimization, Cyberbullying victimization, Weight-based victimization * Correspondence: sjjeong@uta.edu University of Texas at Arlington, 701 S. Nedderman Drive, Arlington, TX 76019, USA Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Lee et al. BMC Public Health (2018) 18:674 Page 2 of 12 Background significant relationship between being obese and the odds of Obesity is one of the leading public health concerns in being bullied among sixth grade children, after controlling the United States, presenting a considerable threat to for sociodemographic characteristics [19]. Given the wide- the well-being and health of school-aged youth. Recent spread bias towards obesity, overweight children were more statistics illustrate that obesity rate remains high among likely to experience weight-specific teasing perpetrated by children and adolescents: while about 1 in 5 reported to peers in general compared to non-overweight children [29]. be obese or overweight based on the body mass index More specifically, children have witnessed their over- (BMI), hereafter referred to as BMI, those aged from 12 weight or obese peers to experience teasing in public to 19 years with extreme obesity increased to slightly area and during physical activities, exclusion from social over 9% during the past two decades [1]. Such preva- activities, spreading of negative rumors, verbal threats lence of obesity may lead to deleterious health problems, and physical harassment [30–32]. This appears to be physically [2, 3] and psychosocially [4–6]. consistent across gender; both obese boys and girls had Obesity in childhood and adolescence has been linked a higher probability of becoming victims of overt forms to a wide array of physical health outcomes. Specifically, of bullying (e.g. hitting, shoving, name-calling) than their obesity-related physical health symptoms include, but not average weight peers [33]. However, other research has limited to, headaches, stomachaches, somatic complaints, revealed that while females were primarily victims of sleep difficulties, and school/social functioning [7–9]. verbal and relational bullying, males were more likely to School children and adolescents with obesity also suffer be victims of all types (including verbal, physical, social from psychological and emotional problems such as exclusion, rumor spreading, and cyber bullying) [34]. depression [10], anxiety [11], low self-esteem [12], and Despite only a few empirical findings, the stigmatization lack of emotional support and cognitive stimulation [13]. of being obese or overweight and risk for peer victimization Further, obesity during childhood and adolescence has are evident in cyberspace. In a study using a sample of been shown to be stigmatizing and likely to result in school adolescents seeking weight loss treatment, more social adversity. There is a strong bias and prejudice than half of the participants reported that they experienced towards school children with obesity [14]. Obese children weight-based cyberbullying victimization via computers or are perceived as the least favorable classmates by their cell phones [28]. While 61% of these youth have encoun- peers in school [15] and often labeled with various tered on-line posting of embarrassing content, 59% have negative stereotypes [16]. The weight-based prejudice from received mean text messages, e-mails, or instant messages. peers may be formed as early as three years of age [17]. According to a more recent study of patients in residential Upon entering elementary school, obese and overweight facilities for severe obesity, obese adolescents were signifi- youth are likely to experience weight-related judgement cantly more likely to be bullied via the Internet compared and social outcomes such as rejection from peers or loss to their normally weighted peers [29]. Furthermore, body of friends [18–20]. In addition, research indicates that dissatisfaction is correlated with cyberbullying victimization; stigma and attitude based on weight bias could originate youth who are victims of cyberbullying are twice as likely to from educators such as teachers [21, 22]orparents and perceive one’s body to be ‘too fat’ compared to those who siblings [23]. have not been victimized [30]. Given the stigma and bias The weight-based stigma and hostility is also pervasive associated with obesity and the greater visibility of offensive in the on-line domain. A qualitative analysis of social comments or images via social media [25, 31, 32], weight- media content (e.g. Twitter) illustrates a prominent theme based victimization in online settings can be detrimental to of offensive and prejudiced attitude and perception the psychological and physical health of adolescents. towards the notion of obesity [24]. Among a wide range of Prior studies have shown that adverse outcomes and stigmatizing content, obese individuals are perceived responses are associated with weight-based victimization largely as gluttonous, unattractive, and sedentary [25]. among school children. While adolescents who have been Based on a person’s weight or body size, youthful victims victims of weight-based teasing or bullying tend to feel are stereotyped in a discriminatory, biased manner. depressed, sad, angry, afraid, and dissatisfied with their body, In addition to biased perceptions of one’s weight, prior some are more likely to have negative reactions in and research suggests that being obese or overweight contributes outside school such as avoidance strategies, binge eating, to the likelihood of becoming a victim of traditional bullying skipping schools, poor academic performance in the event [26]. Prior studies examining the impact of BMI on peer of teasing or bullying by peers [33]. Traditional bullying victimization found that overweight and obese children were victimization is found to be associated with poor physical more likely to be victimized by specific forms of bullying health, including somatic symptoms and withdrawn (verbal, relational, physical) compared to those with normal behaviors [34, 35]. Similarly, cyberbullying negatively weight [27, 28]. A related study, based on reports from impacts the emotional and psychosocial well-being of those teachers, mothers, and student themselves, showed a who are victimized. Specifically, victims of cyberbullying can Lee et al. BMC Public Health (2018) 18:674 Page 3 of 12 suffer from social anxiety [36], depressive symptoms [37], Children (HBSC) survey as the key source of our ana- decreased self-esteem [38], suicidal thoughts [39], emotional lysis. This nationally representative data, collected from distress [40], sadness [41], and angry feelings [42]. Moreover, 42 countries in collaboration with the World Health being victimized on-line undermines one’s academic Organization, provides detailed information on health- performance in school [43], and further triggers problematic and school violence-related behaviors [53]. Of the behaviors such as truancy [38], alcohol use and weapon respondents, the mean age was 12.9, whereas 51.4% were carrying [44]. Furthermore, obese adolescents who have been boys and 48.8% were white. It must be noted that some victims of cyberbullying showed a higher level of suicidal of the variables in our analysis had 4 to 5% of missing ideation compared to their peers with normal weight [29]. responses. Missing values must be properly dealt with Notwithstanding findings indicating a strong relationship due to the fact that improper handling could yield biased between bullying victimization and physical or psycho- coefficients [54]. Following an analysis of missing data, logical health, only a handful of studies have examined the the results confirmed that the missing observations for longitudinal relationship between these factors. Involve- most of the key measures under study are missing not at ment in traditional and cyber forms of bullying was found random. Instead of a multiple imputation to generate to be related to mental health and psychosocial problems probable responses, cases with missing data were listwise such as depressive and emotional symptoms, social anxiety, deleted. Among the 12,642 respondents who completed ADHD symptoms, and lower levels of well-being [45–50]. the survey through multi-stage sampling, 2482 were Similarly, minimal attention has been devoted to the lon- excluded based on missing information. The final sample gitudinal investigation of obesity and overweight with yielded 10,160 children. bullying behaviors. While a significant association between childhood obesity and the likelihood of being bullied was Measures observed [19] among sixth grade children, bullying Physical and psychological distress victimization during adolescence was linked to an in- We focused on two health related measures as out- creased risk of obesity and higher BMI when reaching comes: i) physical distress and ii) psychological distress. young adulthood [51, 52]. The question emerging from The physical distress scale (α = .65) consists of three these longitudinal findings concerns whether bullying items that measure the extent of various pain related victimization could be mediating the relationship between physical conditions in the last six months: (1) “How weight status and physical and psychological outcomes. often have you had the headaches,” (2) “How often have To date, no studies have examined the mediating role you had the stomachaches,” and (3) “How often have of bullying victimization in the relationship between you had the backaches.” Additionally, the psychological obesity and both physical and psychological distress. distress scale (α = .75) was created by summing five Considering that adolescent obesity is correlated with a items that reflect respondents’ psychological health in greater likelihood of being victimized, understanding the the last six months. These items are: (1) “How often effect of victimization, both off-line and on-line, on one’s have you had the feeling low?” (2) “How often have you level of physical and psychological distress would be of had the irritability or bad temper?” (3) “How often have particular value in developing treatments for victims to you had the feeling nervous?” (4) “How often have you cope with their distress. The current study addresses the had the difficulties in getting to sleep?” and (5) “How following research questions. often have you had the feeling dizzy?” Response options for each of these items ranged from 0 (rarely or never) 1) To what extent do overweight and obese youth to 4 (about every day) during the last six months. Both experience traditional and cyberbullying physical and psychological distress scales were coded so victimization, compared to normal weight youth? that a higher score indicates a lower level of physical / 2) To what extent do overweight and obese victims psychological distress in the last six months. of traditional or cyberbullying experience physical and psychological distress compared to normal Traditional and cyber bullying victimization (mediator variables) weight youth? The current study examines the indirect effects of obesity 3) Does becoming a victim of either traditional or on health-related outcomes by investigating the mediating cyberbullying mediate the relationship between influence of traditional and cyberbullying victimization. BMI and physical / psychological distress? First, traditional bullying victimization is a seven-item measure (α = .93) that assesses the aspects of physical and Methods emotional victimization. These measures were adopted Data collection from the previous [55]. Respondents indicated how often Data used in the current study was collected from the they have been bullied at school during the past couple 2009 U.S. version of the Health Behavior in School-Aged months: (1) “I was called mean names, was made fun of, Lee et al. BMC Public Health (2018) 18:674 Page 4 of 12 or teased in a hurtful way,” (2) “Other students left me out Gender (male = 1), age (in years), ethnicity (Hispanic = 1), of things on purpose, excluded me from their group of and race (White = 1) were included in this study. The five friends, or completely,” (3) “I was hit, kicked, pushed, categories – African-American (17.1%), Asian (3.7%), shoved around, or locked indoors,” (4) “Other students American Indian or Alaska Native (1.8%), Native Hawaiian told lies or spread false rumors about me and tried to or Other Pacific Islander (0.9%), two or more races (6.5%), make others dislike me,” (5) “I was bullied with mean and other (18.9%) – were collapsed into non-White. Mean names and comments about my race or color,” (6) “I was scores, standard deviations, and ranges for all variables are bullied with mean names and comments about my presented in Table 1. religion,” and (7) “Other students made sexual jokes, comments or gestures to me.” The traditional bullying Statistical analysis victimization scale was created using the items above and The overarching aim of this study was to explore the im- coded so that a higher score indicates a higher frequency pact of overweight and obesity on physical and psycho- of victimization at school. Second, cyberbullying victimization logical distress and whether these weight-based effects was a four-item measure (α = .90) assessing an individual’s occur indirectly through traditional and cyberbullying victimization experience using a computer-mediated com- victimization. A seemingly unrelated regression (SUR) munication. These measures were adopted from a study of was used to simultaneously assess and compare the Olweus [56]. Respondents were asked to indicate how mediating effects of two types of bullying victimization frequently they have been bullied during the past couple in the link between obesity and both physical and months: (1) “I was bullied at school using a computer or e- psychological distress. The aforementioned relationships mail messages or pictures,” (2) “I was bullied at school using will be empirically tested using multiple mediator a cell phone,” (3) “I was bullied outside of school using a models [57]. Since independent variables differ from one computer or e-mail messages or pictures,” and (4) “Iwas equation to the next, the use of SUR, allowing to bullied outside of school using a cell phone.” Each measure compare multiple equations simultaneously, ensures statis- of victimization was based on a five-point Likert scale tical efficiency in the current research [58]. Furthermore, response ranging from (1) none during the past several SUR is well suited for estimating and comparing indirect months to (5) several times a week. For the purpose of the effects in multiple categories (i.e., BMI categories) [59]. current study, the cyberbullying victimization scale was cre- ated by summing four items and coded so that a higher score Table 1 Descriptive Statistics of Study Variables (n = 10,160) indicates a more frequent victimization via the Internet. Variable Range or Mean or Standard Frequency Percentage Deviation Body mass index (BMI) Dependent Variables As an indicator of obesity, body mass index (BMI) was a a a Physical Distress 0~12 2.95 2.87 computed based on self-reported measures of height and a a a Psychological Distress 0~20 5.39 4.75 weight for each respondent [55]. The BMI percentiles were computed based on the formula [Weight(lbs)/ Independent Variables [Height(inches)*Heights(inches)] * 703. Given that the BMI (Body Mass Index) (%) formula was mainly aimed to compute the adult BMI, b b Healthy Weight 6465 63.63 BMI percentiles were calculated by taking into account b b the respondent’s gender and age for accurate interpretation. Underweight 432 4.25 b b BMI percentiles were then coded into four categories based Overweight 1855 18.26 on the criteria established by the Center for Disease b b Obese 1408 13.86 Control: (1) underweight – less than 5th percentile; (2) healthy weight – between 5th and 85th percentile; (3) at Mediate Variables risk of overweight – between 85th and 95th percentile; and a a a Traditional Victimization 0~28 2.69 4.79 (4) overweight – greater than 95th percentile. For the a a a Cyber Victimization 0~16 .58 2.18 current analyses, the healthy weight between 5th and 85th percentile was used as a reference category to explore the Control Variables effect of overweight and obesity. b b Gender (1=Male) (%) 5227 51.45 a a a Age 10~17 12.95 1.75 School-related and demographic characteristics b b As demonstrated by prior research that social-demographic Ethnicity (1=Hispanic) (%) 2916 28.70 b b characteristics are significant indicators of bullying Race (1=White) (%) 4961 48.83 victimization and school-life related factors, we also a Note. The range, mean, and standard deviation are reported incorporated demographic variables as control variables. The frequency and percentage are reported Lee et al. BMC Public Health (2018) 18:674 Page 5 of 12 Specifically, we estimated four sets of models: (1) the effect CFI > .95 were used to identify a satisfactory or acceptable of BMI on the outcome measures (i.e., physical and psycho- model fit. After we set all structural paths with covariance logical distress); (2) the effect of BMI on the mediators (i.e., and mediators, the fit for this model was: SRMR = .013; traditional and cyber bullying victimization); (3) the effect of RMSEA = .036 (p-value = .85; 90% C.I. = .030~.043); the mediators on outcome measures; and (4) the indirect CFI = .990. The examination of model fit indices effects of BMI on outcome measures. Additionally, Sobel- suggested that the model fitted the data well. Goodman tests was applied to statistically test for the pres- ence of mediation. To generate standard errors and signifi- Results cance levels of the indirect effects, we utilized 1000 bootstrap Descriptives replications. All analyses were performed using Stata SE 13 We report summary statistics for physical and psycho- to estimate our seemingly unrelated models. Although the ef- logical distress, traditional and cyber bullying victimization, fects of BMI on bullying victimization and negative conse- and other control variables used in the current study (See quences of bullying victimizations are well-documented, very Table 1). The mean physical distress score was 2.95 few studies to date have investigated the mediating effects of (sd = 2.87) and the mean psychological distress score bullying victimization (traditional and cyber) among school was 5.39 (sd = 4.75). Among the study participants in children with obesity in the context of distress. our analytic sample, 63.6% (n = 6465) were categorized as healthy weight, 4.3% (n = 432) as underweight, 18.3% Additional analysis (n = 1855) as overweight, and 13.9% (n = 1408) as obese. To simultaneously examine the empirical relationships With regards to bullying victimization, the mean score for among the variables under investigation, structural traditional victimization score was 2.69 (sd = 4.79), and equation modeling (SEM) was also employed by using the mean score for cyber victimization was .58 (sd = 2.18). maximum-likelihood-estimation in Stata 13.1 [60]. We However, these two mean scores reflected a relatively carefully examined a number of different model fit indices lower degree of victimization compared to other studies. to assess identification and stability. Since chi-square statis- Concerning demographic covariates, the final sample of tics assessing the fit between the matrix of observations 10,160 students showed a mean age of 12.95 years and the matrix generated by the model is sensitively influ- (sd = 1.75). While the majority of the sampled students enced by large sample size [61], we paid less attention. were non-Hispanics (71.3%), males accounted for 51.5%. Instead, we considered: standardized root-mean-square residual (SRMR); root-mean-square-error of approximation Bivariate correlations (RMSEA) with 90% confidence interval [62]; and compara- As a preliminary analysis, we conducted a bivariate tive fit index (CFI) [63]. For study criterion, the combin- correlation analysis (See Table 2). As expected, BMI was ation of SRMR < .08; RMSEA < .08 with p-value > .05; and significantly related to both physical and psychological Table 2 Correlations of Covariates (n = 10,160) 12 34 56 78 9 Dependent Variables 1. Physical Distress 1 2. Psychological Distress .62*** 1 Independent Variables 3. BMI (Body Mass Index) .06*** .06*** 1 Mediate Variables 4. Traditional Victimization .22*** .29*** .06*** 1 5. Cyber Victimization .12*** .13*** .02** .61*** 1 Control Variables 6. Gender (1=Male) (%) −.16*** −.15*** .08*** −.01 −.01 1 7. Age .11*** .10*** −.05*** −.06*** .02*** .04*** 1 8. Ethnicity (1=Hispanic) −.05*** −.02 .07*** .02 .04*** .01 −.01 1 9. Race (1=White) .05*** −.01 −.09*** −.04*** −.04*** .02 −.03*** −.41*** 1 Note. **p < .05. ***p < .01 Lee et al. BMC Public Health (2018) 18:674 Page 6 of 12 distress (r = .06 and .06, respectively). Additionally, with both physical and psychological distress (b = .15 and traditional bullying victimization and cyber bullying .36, p < .01, respectively). victimization were negatively correlated with physical distress (r = .22 and .12, respectively) and psychological Mediating effect of bullying victimization distress (r = .29 and .13, respectively). Notably, BMI was The SUR estimations with traditional and cyber bullying positively related to both traditional and cyber victimization as mediators are presented in Table 4.The victimization (r = .06 and .02, respectively). mediation results showed a significant indirect effect of the overweight (b = .07, p < .01) and obesity (b = .10, p < .01) on Hypothesized mediation models physical distress through traditional bullying victimization, Impact of BMI on victimization and distress but not through cyberbullying victimization. For the Table 3 indicates the main direct effects of BMI on psychological distress, we did see a significant indirect effect mediator variables (i.e., traditional victimization and cyber of the overweight (b = .17, p <.01) and obesity (b = .27, victimization) and outcome variables (i.e., physical distress p < .01) on psychological distress through traditional and psychological distress) using seemingly unrelated bullying victimization. Unexpectedly, while there was no regression models. First, we examined whether weight indirect effect of the weight status on physical distress status predicts the probability of bullying victimization. through cyberbullying victimization, we found a mediating The results indicated that overweight children have a higher effect (b = −.02, p < .05) for psychological distress. As risk than healthy weight children of becoming a victim of shown in Table 4, the significance of the indirect effects of traditional bullying (b = .47, p <.01). Similarly, obesity was traditional and cyber bullying victimization were examined positively associated with risk of being a victim of traditional using Sobel-Goodman tests [64]. These tests indicated that bullying (b = .70, p < .01). Next, we examined whether the indirect effects linking weight status with physical weight status predicts physical and psychological distress. distress through traditional bullying victimization were The results revealed that obese and overweight children significant (z = 5.90, p < .01), accounting for 24% of the have been shown to have poorer physical and psychological effect of weight status on physical distress. For psycho- distress than healthy weight children (b = .27 and .38, logical distress, Sobel-Goodman tests also indicated that p < .01, respectively). Moreover, obesity has been found to the indirect paths linking weight status with psychological be positively associated with physical and psychological distress via traditional bullying victimization were signifi- distress (b = .56 and .67, p < .01, respectively). Finally, cant (z = 6.13, p < .01), accounting for 36% of the effect of traditional bullying victimization was positively associated weight status on psychological distress. Table 3 Direct Effects SUR (n = 10,160) Model 1 Traditional Victimization Cyber Victimization Physical Distress Psychological Distress b (S.E.) b (S.E.) b (S.E.) b (S.E.) Independent Variables BMI (Body Mass Index) Underweight .50(.24)** −.01(.11) −.17(.15) .23(.25) Overweight .47(.12)*** .06(.05) .27(.08)*** .38(.13)*** Obese .70(.14)*** .11(.06) .56(.09)*** .67(.14)*** Mediate Variables Traditional Victimization .15(.01)*** .36(.01)*** Cyber Victimization −.02(.02) −.17(03)*** Control Variables Gender (1=Male) −1.10(.06)*** −1.76(.09)*** Age .23(.02)*** .33(.03)*** Ethnicity (1=Hispanic) −.12(.07) .08(.12) Race (1=White) .34(.06)*** .18(.10) Note. a. Healthy weight is the reference category **p < .05. ***p < .01 Lee et al. BMC Public Health (2018) 18:674 Page 7 of 12 Table 4 Direct and Indirect Effects Comparisons SUR (n = 10,160) Physical Distress Psychological Distress b S.E. z Sobel z (% of total effect) b S.E. z Sobel z (% of total effect) Direct Effects BMI (Body Mass Index) Underweight −.17 .15 −1.15 .23 .25 .93 Overweight .27*** .08 3.61 .38*** .13 2.99 Obese .56*** .09 6.56 .67*** .14 4.76 Bullying Victimization Traditional .15*** .01 18.32 .36*** .01 27.53 Cyber .02 .02 −1.05 −.17*** .03 −5.66 Indirect Effects BMI on Distress through Traditional Victimization 5.90*** (24%) 6.13*** (36%) Underweight .08** .04 2.03 .15 .09 1.62 Overweight .07*** .02 3.72 .17*** .05 3.67 Obese .10*** .02 4.80 .27*** .05 5.15 BMI on Distress through Cyber Victimization 2.33** (5%) 2.49** (7%) Underweight .01 .01 .06 .01 .02 .40 Overweight −.01 .01 −.75 −.01 .01 −.87 Obese −.01 .01 −.90 −.02** .01 −1.99 Note. a. Healthy weight is the reference category **p < .05. ***p < .01 SEM results models, all of the estimates were in the same direction Following the initial SUR analysis and inspection of the and of similar magnitude. model fit indices for our models, we used SEM to examine As can be seen in Figs. 1 and 2, the test of mediation the direct relationship between BMI, physical distress, showed a significant indirect effect of BMI on psycho- psychological distress, and two mediators. Similar to the logical distress through victimization of both traditional SUR analysis, the SEM results indicated that significant and cyber bullying (total indirect = .08; total direct = .30; correlations were in the same direction. After the initial z = 6.81; p < .01) and these indirect effects accounted for direct effect analysis, we examined the indirect effects – 27% of the effect of BMI on psychological distress. As il- whether BMI leads to psychological and physical distress lustrated in Figs. 3 and 4, the results also showed that through increases in the risk of traditional and cyber the indirect effects of traditional and cyber bullying bullying victimization. Consistent with the SUR mediation victimization were significant; therefore, bullying Fig. 1 Traditional/Cyber Victimization Mediators of Obesity and Physical Distress Lee et al. BMC Public Health (2018) 18:674 Page 8 of 12 Fig. 2 Traditional/Cyber Victimization Mediators of Obesity and Psychological Distress victimization significantly mediated the association be- research shows that children with obesity had a greater tween BMI and physical distress (total indirect = .03; likelihood of exhibiting poor physical and psychological total direct = .19; z = 7.47; p < .01), while the model ex- health outcomes [2, 7, 8, 12, 13, 67]. Regarding the plained 16% of variance in physical distress. impact of victimization on distress, traditional bullying victimization was positively linked to physical and Discussion psychological forms of distress. This is consistent with A number of findings emerged from the current study. previous research and suggests that youth who have First, obesity, measured by BMI, showed a significant been victims of traditional bullying are more likely to direct effect on one of the two types of victimization – experience a variety of physical and psychological symp- traditional bullying. In line with prior research [26–28, toms [33–35]. Yet, an unexpected finding is the negative 65, 66], obese or overweight youth are significantly more effect of cyberbullying victimization on psychological likely to be victimized by bullying compared to those distress. Unlike prior studies [36, 40, 41], our study who are not obese. Contrary to the earlier findings found that youth who have been a victim of cyberbullying suggesting a positive association between obesity and are less likely to experience psychosocial distress. One cyberbullying victimization [28, 29], there was not a possible explanation may be that individuals may be significant effect of BMI on the probability of being involved as both victims and perpetrators of cyberbullying bullied on-line. and also engage in aggressive behavior as a coping or In light of previous research documenting the effect of defense strategy [68–70]. This may contribute to lower obesity on physical and psychological distress, statistical levels of psychological distress. Moreover, youth with high evidence was found for a significant link between BMI levels of self-control showed greater levels of resiliency and both forms of distress. In general, prior obesity and lower levels of distress in response to real world or Fig. 3 SEM: Direct and Indirect Effects of BMI on Physical Distress; The figure shows that the proportion of total “BMI” effect mediated via “Traditional” and “Cyber” Victimization was .16. Circles represent observed variables, and straight arrows connect the observed variables. Bold lines represent significant paths, and dotted lines represent nonsignificant paths. All significant parameters are significant at the p <.001 level Lee et al. BMC Public Health (2018) 18:674 Page 9 of 12 Fig. 4 SEM: Direct and Indirect Effects of BMI on Psychological Distress; The figure shows that the proportion of total “BMI” effect mediated via “Traditional” and “Cyber” Victimization was .27. Circles represent observed variables, and straight arrows connect the observed variables. Bold lines represent significant paths, and dotted lines represent nonsignificant paths. All significant parameters are significant at the p < .001 level cyberbullying [71]. Finally, peers may serve as a protective to) the negative content made by others, which may be role in buffering the negative link between cyberbullying accompanied by reduced distress. Finally, the children in victimization and distress [72]. the current sample may not be considered “pure” victims. Notably, mediating effects of bullying victimization were Since physical dominance is less visible in on-line observed using the SUR approach. Only traditional bully- interactions, it is possible that victims of traditional ing victimization mediated the link between BMI and bullying could engage in aggressive behaviors towards physical distress. In addition, the association between BMI those who have bullied them via electronic means in and psychological distress among youth was mediated by seeking retribution [75, 76]. both forms of victimization. While traditional bullying victimization had a positive mediating effect on the BMI- Strengths and limitations distress link, cyberbullying victimization indicated a nega- The current study has a number of limitations. First, the tive effect in the analysis. These indirect effects imply that results do not allow to draw causal inferences due to the obese or overweight youth who have been victims of trad- cross-sectional nature of this study. Longitudinal studies itional bullying would justifiably experience a higher level are needed to disentangle the temporal relationship of physical and psychological distress. Overall, these re- between the variables under study. Second, the measure sults offer evidence that there may be further mediating for cyberbullying victimization may not accurately repre- link between BMI, bullying victimization and distress, sent the ways in which an individual may be harassed or which warrants further exploration. bullied via the Internet. Cyberbullying could be facili- The negative mediating effect of cyber victimization tated via a wide range of on-line platforms such as chat on the association between BMI and psychological rooms, emails, text messages, mobile phone call, photo distress could be explained in several ways. First, the or video clip, and social media [77–79]. Future research measures for cyberbullying victimization may not fully should consider a more comprehensive measure of cyber capture the intricacies of how technology could be victimization to allow for a thorough evaluation of the subverted to damage a victim’s reputation, self-esteem, on-line victimization experience. At the same time, there or friendship. Rather, it merely reflects the location of is need to establish a commonly agreed definition of bullying using a computer or cell phone. Moreover, cyber victimization for ensuring reliability to some victimization may not necessarily lead to emotional degree [80]. In addition, since the current study focused distress if it takes place in virtual realm [73]. Given the only on victims of weight-based bulling, future research unique properties of online environments [74], it is could benefit from exploring the subgroup of bully- plausible that obese or overweight victims may receive victims, who have been found to be more common in social support from bystanders via social media (e.g. cyberbullying [81] as opposed to traditional bullying [82, Facebook), which, in turn, could neutralize negative 83]. Lastly, the present study utilized self-reported ques- comments from peers during weight-based cyberbullying tionnaire and hence is subject to response bias. incidents [31]. For instance, if a youth receive a demeaning Our study offers several strengths. First, the dataset used message or image related to obesity or overweight, an in this study consists of a nationally representative sample empathetic bystander could dissent (rather than conform of U.S. youth, which enhances generalizability and Lee et al. BMC Public Health (2018) 18:674 Page 10 of 12 statistical power and lessens selection bias. Second, despite Endnotes its deficiency, BMI is considered to be well-validated and Participants were given a definition of “being bullied” as widely used by obesity researchers, and further proven follows: A student is being bullied when another student, to be of good predictive value [84–86]. Third, the use or a group of students, say or do nasty or unpleasant things of seemingly unrelated regression (SUR) and Sobel- to him or her. It is also bullying when a student is teased Goodman tests allows one to assess the extent and repeatedly in a way he or she does not like or when they significance of the mediating effects of traditional and are deliberately left out of things. But it is not bullying cyber victimization in the link between weight status when two students of about the same strength or power and both types of distress. Furthermore, the present argue or fight. It is also not bullying when a student is findings offer useful insights into the mechanism teased in a friendly and playful way. indirectly linking indicators of obesity to physical and psy- According to the Center for Disease Control’s BMI chological distress via victimization. Yet, future research is category, the raw BMI score for boys and girls is different. needed to untangle the impact of on-line victimization on However, the CDC adjust raw BMI score into BMI the link between obesity and psychological distress. categories based upon centralized-percentiles cutoffs regardless of participants’ sex. (See BMI-for-age charts). Therefore, the interpretation of BMI is not different. Conclusions Abbreviations The primary aim of this study was to examine the direct ADHD: Attention Deficit Hyperactivity Disorder; BMI: Body Mass Index; and indirect effect of obesity on two forms of distress CFI: Comparative Fit Index; RMSEA: Root Mean Square Error of Approximation; SD: Standard Deviation; SEM: Structural Equation Modeling; SRMR: Standardized (physical and psychological) among U.S. youth. Our Root Mean Square Residual; SUR: Seemingly Unrelated Regression findings affirm that obese and overweight adolescents are more likely to be victims of traditional victimization and Acknowledgements Not applicable. also more likely to experience physical and psychological distress compared to those with healthy weight. As an Funding additional finding, victimization can exacerbate the effect of Not applicable. obesity on the level of distress, suggesting traditional Availability of data and materials victimization as an important mediator in the association The datasets generated and/or analyzed during the current study are between obesity and physical/psychological distress. The available in the ICPSR repository: http://www.icpsr.umich.edu/icpsrweb/ current findings underscore the need to raise awareness for NAHDAP/studies/34792 the detrimental impact of victimization occurring off-line in Authors’ contributions school classrooms or playgrounds on the physical and BL has made substantial contributions to the conception and design of the psychological distress among obese and overweight youth. study and has taken an active role in drafting and revising the manuscript critically for important intellectual content. SJ was in charge of the analysis Bullying victimization represents a risk factor for youths’ and interpretation of data, and MR provided valuable insights into the psychosocial well-being. Parents and school administrators interpretation of the results. All authors read and approved the final can develop educational interventions to raise the aware- manuscript. ness on weight stigma and stereotypes as well as adverse Ethics approval and consent to participate consequences of weight-based bullying. Given that weight- This study is based on secondary data and no contact was made with any related stigma and teasing occur in school settings among individuals. In addition, all names and any other personally identifying peers, school-based interventions can be implemented to information was removed from the original research team. Rather, they randomly assign case number and it does not allow linkage to any name or reduce thestigmaand bias associated with obesity and identifying information. Hence, the data is anonymous and consent form is overweight and address the ways in which families and not required. This study complies with national guidelines and provide a communities can come together to educate children to be reference which supports this. A local ethics committee ruled that no formal ethics approval was required in this particular study. tolerant of differences in weight and body size. In line with this, youths’ attitudes toward body image have been found Consent for publication to be influenced by social norms [87]. Efforts to reduce Not applicable. weight stigma and discrimination should focus on class- Competing interests room instructions to improve adolescents’ attitudes toward The authors declare that they have no competing interests. peers with obesity, school policies prohibiting weight-based bullying, and programs to promote an environment that Publisher’sNote recognizes and supports the diversity of cultural foodways Springer Nature remains neutral with regard to jurisdictional claims in [88]. 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School � Our selector tool helps you to find the most relevant journal Psych Internat. 2009;30:383–402. � We provide round the clock customer support 78. O'Keeffe G, Clarke-Pearson K. The impact of social media on children, � Convenient online submission adolescents, and families. Pediatrics. 2011;127:800–4. 79. Slonje R, Smith P. Cyberbullying: another main type of bullying? Scand J � Thorough peer review Psych. 2008;49:147–54. � Inclusion in PubMed and all major indexing services 80. Fridh M, Lindström M, Rosval M. Subjective health complaints in adolescent � Maximum visibility for your research victims of cyber harassment: moderation through support from parents/ friends - a Swedish population-based study. BMC Public Health. 2015;15: Submit your manuscript at 949–60. www.biomedcentral.com/submit

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