Self-Consciousness Mitigates Weight Gain related to Internalized Weight Bias: Cross-Cultural Survey and Brain Imaging

Self-Consciousness Mitigates Weight Gain related to Internalized Weight Bias: Cross-Cultural Survey and Brain Imaging | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Self-Consciousness Mitigates Weight Gain related to Internalized Weight Bias: Cross-Cultural Survey and Brain Imaging Yuko Nakamura, Karin Hayashi, Norihide Maikusa This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6390971/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Weight bias internalization (WBI), where individuals adopt negative stereotypes about excess weight, is linked to adverse health outcomes. Although prior research indicates associations between WBI, weight status, and psychological factors linked to self-consciousness, these relationships remain unclear. Thus, this study examined these associations and the relationship between brain characteristics and WBI or self-consciousness. An online survey was conducted in Japan (n = 1946), South Korea (n = 500), Germany (n = 598), and the United States (n = 580) to assess WBI, self-consciousness, and body mass index (BMI). In Japanese samples, associations between brain structural (n = 120) or functional (n = 30) characteristics and WBI or self-consciousness were explored. Self-consciousness negatively mediated the influence of WBI on BMI, varying across countries. Gray matter volume in the precuneus correlated positively with self-consciousness, while the subgenual anterior cingulate cortex (sACC) response to food reward correlated positively with WBI. Functional connectivity between the precuneus and sACC was positively associated with self-consciousness. Therefore, self-consciousness may reduce the impact of WBI on BMI by modulating connectivity between the sACC and precuneus, providing further insight into the interactions between WBI and self-consciousness. Biological sciences/Psychology Biological sciences/Psychology/Human behaviour Biological sciences/Neuroscience Biological sciences/Neuroscience/Feeding behaviour weight bias internalization self-consciousness body mass index subgenual anterior cingulate cortex precuneus Figures Figure 1 Figure 2 Introduction The prevalence of obesity has increased worldwide 1 , with global adult obesity more than doubling in the last 30 years. The rapid rise in the prevalence of obesity has led to more research on the adverse effects of weight bias and weight bias internalization (WBI) 2 . Weight bias is defined as holding negative stereotypes about people with higher weights, such as being lazy, lacking willpower, or having poor eating habits, and the resulting negative attitudes toward these individuals 3 . When individuals apply negative weight stereotypes to themselves and denigrate themselves because of their body weight, WBI occurs 4 . WBI tends to be more pronounced in women 5 and individuals with higher body weights 6 . WBI is associated with poor psychosocial (e.g., negative mental health), physical (e.g., health-related quality of life), and behavioral (e.g., disordered eating) health 7 . The associations between WBI and body mass index (BMI) or weight change have been well studied 2 . For instance, higher WBI is associated with greater BMI even in a predominantly healthy weight population (n = 1454) 8 . Additionally, WBI is negatively associated with weight loss 9 and positively associated with weight gain 10 . WBI is also associated with various psychological factors, such as poor body image 10 , elevated body dissatisfaction 11 , and psychological distress 12 , all of which are related to self-consciousness 13 – 15 . Self-consciousness is defined as the awareness of oneself, including one's body, actions, and thoughts, and how others perceive them 16 . The concept of self-consciousness encompasses both private and public dimensions. Private self-consciousness is defined as the awareness of one's personal inner feelings, while public self-consciousness is the concern about how one is perceived by others 17 . Thus, WBI, which involves the process of being aware of weight stigma, applying it to oneself, and devaluing one's self-worth, is likely related to self-consciousness. In fact, self-consciousness is believed to be linked to stigma consciousness, which refers to a focus on one's stereotyped status 18 . Self-consciousness also influences weight management 19 and eating behavior 20 , thereby potentially influencing the association between WBI and BMI. Moreover, given that WBI is reported in individuals across the weight spectrum 21 , excess weight may not be its sole cause, as self-consciousness could also contribute to WBI. However, the associations among WBI, BMI, and self-consciousness remain unclear. Therefore, the current study aims to examine the effect of self-consciousness on the relationship between WBI and BMI. The current study also examined cultural differences in the associations among WBI, BMI, and self-consciousness across four countries (Japan, South Korea, Germany, and the United States). Cultural differences in self-consciousness have long been studied 22 , 23 and are related to eating habits. For example, the association between public self-consciousness and the intention to eat a healthy diet was modulated by cultural differences 24 . Additionally, as the majority of WBI research has been conducted in the United States among women with higher BMI 2 , undertaking research in diverse cultures could provide a better understanding of WBI. Furthermore, the current study examined the associations between WBI or self-consciousness and the brain properties to investigate the neural mechanisms underlining WBI, considering the subgenual anterior cingulate cortex (sACC) as the region of interest (ROI). The sACC is a subregion of the cingulate cortex and has a wide-ranging neural connection with limbic, prefrontal, parietal, and mesiotemporal areas 25 . The sACC contributes to the modulation of emotional behavior 26 and food-reward processing 27 ; self-awareness, encompassing the reflection of one's recent behavioral history 28 ; and social decision-making, specifically the processing of prediction errors in social interactions (i.e., social prediction errors), such as the calculation of differences between actual and predicted intentions of others 29 , 30 . Thus, the sACC could play a significant role in self-consciousness by monitoring one's thoughts and speculating on how others perceive them. Furthermore, given its involvement in observation-driven social learning 31 , sACC could be associated with WBI by facilitating learning weight stigma and internalizing it. Therefore, using the sACC as the ROI, magnetic resonance imaging (MRI) measurements of brain structure and responses to food reward were conducted as preliminary research in a Japanese sample. It was hypothesized that greater WBI would be linked to heightened self-consciousness, as self-consciousness focuses on one's body and how others see it 16 . Since self-consciousness is involved in maladaptive eating 20 , it could positively mediate the association between WBI and weight status. Due to cultural differences in self-consciousness 22 , 23 , its mediating effect would differ across countries. Furthermore, the sACC could contribute to increasing WBI by playing a role in self-awareness 28 and predicting the intentions of others 29 , 30 . Methods Experimental design First, an online survey was administered to assess WBI, self-consciousness, and BMI in Japan, South Korea, Germany, and the United States. Then, structural and functional MRI (fMRI) measures were performed on Japanese young adults. All studies were approved by the Ethics Committee of the Department of Arts and Sciences, University of Tokyo (Approval No. 812-2). This study adhered to the principles of the Declaration of Helsinki. Participants Online survey Participants aged 18–45 who had lived in the same country for more than 10 years were included in the online survey. Commercial survey sampling and administration companies were contracted to recruit participants and administer the online survey. After excluding those who failed to enter their responses, a total of 1946 participants from Japan, 500 from South Korea, 598 from Germany, and 580 from the United States were included in the statistical analyses (Table 1 , 2 ) (Supplementary Information). Before beginning the online survey, participants were asked to provide their consent to contribute their data for research purposes; those who consented to participate in this research were included. Participants provided their age, gender, weight, and height, and completed questionnaires about WBI and self-consciousness. Table 1 Demographic characteristics of the participants in the Japanese sample. Total (n = 1946) Men (n = 689) Women (n = 1257) Gender difference P-value* Age (years) Mean ± SD (Range) 35.38 ± 6.90 (18–45) 36.43 ± 6.79 (18–45) 34.81 ± 6.89 (18–45) < 0.001 Body mass index (kg/m2) Mean ± SD (Range) 21.53 ± 3.62 (13.79–42.24) 22.72 ± 3.65 (14.87–42.24) 20.88 ± 3.43 (13.79–41.40) < 0.001 Weight Self-Stigma Questionnaire Self-devaluation Mean ± SD (Range) 15.91 ± 6.35 (6–30) 14.66 ± 5.97 (6–30) 16.60 ± 6.44 (6–30) < 0.001 Fear of enacted stigma Mean ± SD (Range) 14.23 ± 4.68 (6–30) 13.71 ± 4.29 (6–27) 14.52 ± 4.86 (6–30) 0.002 Self-Consciousness Scale Public self-consciousness Mean ± SD (Range) 51.12 ± 13.29 (11–77) 47.07 ± 13.51 (11–77) 53.34 ± 12.64 (11–77) < 0.001 Private self-consciousness Mean ± SD (Range) 45.28 ± 10.79 (10–70) 43.51 ± 11.12 (10–70) 46.25 ± 10.48 (10–70) < 0.001 *Wilcoxon rank-sum test. SD: Standard deviation Table 2 Demographic characteristics of the participants in the samples of three countries. South Korea Total (n = 500) Men (n = 245) Women (n = 255) Other ( n = 0) Gender difference (men vs women) P-value* Age (years) Mean ± SD (Range) 34.15 ± 7.48 (15–45) 35.01 ± 7.29 (18–45) 33.32 ± 7.58 (18–45) - 0.011 Body mass index (kg/m2) Mean ± SD (Range) 22.92 ± 3.74 (14.78–41.89) 24.33 ± 3.42 (15.54–41.89) 21.56 ± 3.53 (14.78–36.13) - < 0.001 Race Asian: 489 White/Caucasian: 7 Black/African American: 1 Prefer not to answer/Don't know: 3 Asian: 243 White/Caucasian: 1 Black/African American: 1 Prefer not to answer/Don't know: 0 Asian: 246 White/Caucasian: 6 Black/African American: 0 Prefer not to answer/Don't know: 3 - - Weight Self-Stigma Questionnaire Self-devaluation Mean ± SD (Range) 17.89 ± 5.05 (6–30) 17.56 ± 4.86 (6–30) 18.21 ± 5.22 (6–30) - 0.239 Fear of enacted stigma Mean ± SD (Range) 15.14 ± 5.47 (6–30) 14.97 ± 5.35 (6–30) 15.30 ± 5.58 (6–30) - 0.584 Self-Consciousness Scale Public self-consciousness Mean ± SD (Range) 24.85 ± 5.20 (7–35) 24.66 ± 5.35 (7–35) 25.04 ± 5.06 (9–35) - 0.388 Private self-consciousness Mean ± SD (Range) 34.35 ± 5.84 (10–50) 34.51 ± 5.77 (10–50) 34.20 ± 5.92 (16–48) - 0.375 Germany Total (n = 598) Men (n = 284) Women (n = 249) Other ( n = 4) P-value* Age (years) Mean ± SD (Range) 30.37 ± 8.08 (18–45) 31.74 ± 7.19 (18–45) 29.16± 8.05 (18–45) 26.25 ± 8.10 (20–38) < 0.001 Body mass index (kg/m2) Mean ± SD (Range) 24.79 ± 5.39 (15.00–53.33) 25.42 ± 5.33 (16.07–53.33) 24.20 ± 5.33 (15.00–52.47) 26.60 ± 9.81 (18.94–40.75) < 0.001 Race Asian: 22 White/Caucasian: 517 Black/African American: 17 Hispanic/Latino: 11 Native American: 1 Prefer not to answer/Don't know: 30 Asian: 5 White/Caucasian: 257 Black/African American: 9 Hispanic/Latino: 4 Native American:0 Prefer not to answer/Don't know: 9 Asian: 17 White/Caucasian: 259 Black/African American: 8 Hispanic/Latino: 6 Native American:1 Prefer not to answer/Don't know: 19 Asian: 0 White/Caucasian: 1 Black/African American: 0 Hispanic/Latino: 1 Native American:0 Prefer not to answer/Don't know: 2 - Weight Self-Stigma Questionnaire Self-devaluation Mean ± SD (Range) 15.43 ± 6.18 (6–30) 15.99 ± 5.77 (6–30) 14.98 ± 6.50 (6–30) 11.50 ± 6.81 (6–20) 0.031 Fear of enacted stigma Mean ± SD (Range) 14.24 ± 6.18 (6–30) 14.87 ± 6.07 (6–30) 13.68± 6.24 (6–30) 13.50 ± 7.55 (6–20) 0.010 Self-Consciousness Scale Public self-consciousness Mean ± SD (Range) 22.46 ± 5.72 (7–35) 21.99 ± 5.43 (7–35) 22.90± 5.90 (7–35) 22.25 ± 10.37 (7–30) 0.077 Private self-consciousness Mean ± SD (Range) 32.11 ± 6.16 (16–50) 32.13 ± 6.03 (16–47) 15.50 ± 5.21 (17–50) 30.50± 9.54 (18–41) 0.989 United States Total (n = 580) Men (n = 282) Women (n = 296) Other ( n = 2) P-value* Age (years) Mean ± SD (Range) 33.79± 7.19 (18–45) 33.33 ± 7.18 (18–45) 32.11 ± 6.16 (16–50) 23.00 ± 5.66 (19–27) 0.089 Body mass index (kg/m2) Mean ± SD (Range) 27.24± 6.98 (12.37–58.27) 26.38 ± 6.32 (12.37–58.24) 28.10 ± 7.47 (16.12–58.27) 20.01± 0.31 (19.79–20.23) 0.008 Race Asian: 25 White/Caucasian: 314 Black/African American: 164 Hispanic/Latino: 59 Native American:12 Prefer not to answer/Don't know: 6 Asian: 17 White/Caucasian: 139 Black/African American: 84 Hispanic/Latino: 32 Native American: 7 Prefer not to answer/Don't know: 3 Asian: 7 White/Caucasian: 175 Black/African American: 79 Hispanic/Latino: 27 Native American:5 Prefer not to answer/Don't know: 3 Asian: 1 White/Caucasian: 0 Black/African American: 1 Hispanic/Latino: 0 Native American:0 Prefer not to answer/Don't know: 0 Weight Self-Stigma Questionnaire Self-devaluation Mean ± SD (Range) 15.63± 6.32 (6–30) 14.99 ± 6.01 (6–30) 16.23 ± 6.58 (6–30) 15.50 ± 3.54 (13–18) 0.021 Fear of enacted stigma Mean ± SD (Range) 15.63± 6.59 (6–30) 15.12 ± 6.49 (6–30) 16.14 ± 6.67 (6–30) 11.50 ± 3.54 (9–14) 0.079 Self-Consciousness Scale Public self-consciousness Mean ± SD (Range) 22.80 ± 6.23 (7–35) 22.26 ± 6.36 (7–35) 23.31± 6.08 (7–35) 24.50 ± 2.12 (23–26) 0.073 Private self-consciousness Mean ± SD (Range) 33.53 ± 6.22 (18–49) 33.41 ± 6.49 (18–49) 33.62 ± 5.97 (18–49) 37.50 ± 4.95 (34–41) 0.622 *Wilcoxon rank-sum test. SD: Standard deviation Brain measurements A total of 120 Japanese participants were included (Table 3 ). All participants provided written informed consent. Those with a history of neurological injury; known genetic or medical disorders; previous or current use of psychotropic medications, tobacco, cigarettes, electronic cigarettes; and any MRI exclusion criteria were excluded from the study. Of the participants included in the brain structural measurements, 30 underwent the fMRI experiment (Table 3 ). Table 3 Demographic characteristics of the participants who completed brain measurements. Structural MRI measurement Total (n = 120) Men (n = 60) Women (n = 60) Gender difference (men vs women) P-value* Age (years) Mean ± SD (Range) 24.88 ± 5.65 (20–44) 24.77 ± 5.54 (20–40) 25.00 ± 5.81 (20–44) 0.661 Body mass index (kg/m2) Mean ± SD (Range) 21.27± 2.81 (16.85–30.96) 21.09 ± 2.79 (16.94–30.96) 21.45 ± 2.83 (16.85–28.32) 0.442 Weight Self-Stigma Questionnaire Self-devaluation Mean ± SD (Range) 13.99 ± 6.10 (6–27) 17.03 ± 5.22 (7–27) 10.95 ± 5.39 (6–27) < 0.001 Fear of enacted stigma Mean ± SD (Range) 11.15 ± 3.96 (6–25) 12.90 ± 4.29 (6–25) 9.40 ± 2.64 (6–16) < 0.001 Self-Consciousness Scale Public self-consciousness Mean ± SD (Range) 54.46± 10.46 (27–74) 55.82 ± 11.28 (28–74) 53.10 ± 9.47 (27–70) 0.065 Private self-consciousness Mean ± SD (Range) 50.75± 9.27 (21–70) 50.40 ± 9.38 (25–70) 51.10 ± 9.23 (21–68) 0.592 Functional MRI measurement Total (n = 30) Men (n = 20) Women (n = 10) Gender difference(men vs women) P-value $ Age (years) Mean ± SD (Range) 24.77 ± 5.04 (20–36) 24.30 ± 4.40 (20–36) 25.70 ± 6.29 (20–35) 0.982* Body mass index (kg/m2) Mean ± SD (Range) 21.26 ± 2.72 (16.85–28.32) 21.32 ± 3.09 (16.85–28.32) 21.13 ± 1.91 (18.85–25.07) 0.859 Weight Self-Stigma Questionnaire Self-devaluation Mean ± SD (Range) 12.47 ± 5.83 (6–27) 10.75 ± 5.32 (6–27) 15.90 ± 5.49 (7–25) 0.020 Fear of enacted stigma Mean ± SD (Range) 10.67 ± 2.90 (6–18) 10.00 ± 2.53 (6–16) 12.00 ± 3.27 (7–18) 0.075 Self-Consciousness Scale Public self-consciousness Mean ± SD (Range) 56.00 ± 9.54 (31–71) 56.70 ± 7.95 (39–68) 54.50 ± 12.50 (31–71) 0.561 Private self-consciousness Mean ± SD (Range) 52.03 ± 7.70 (40–68) 52.90 ± 8.08 (40–68) 50.30 ± 6.93 (41–62) 0.393 *Wilcoxon rank-sum test. $ =Tow-sample t-test MRI: magnetic resonance imaging; SD: Standard deviation Measurements Measurements for WBI and self-consciousness To assess WBI, the weight self-stigma questionnaire (WSSQ) 32 was used (Table S1 ). The WSSQ comprises two subscales: self-devaluation (negative thoughts about being overweight) and fear of enacted stigma (the perception of being discriminated and identification with a stigmatized group). To assess public- and private self-consciousness, the self-consciousness scale (SCS) 17 was used (Table S2) (Supplementary Information). Brain imaging Structural MRI measurement: All structural images were collected using a MAGNETOM Prisma 3.0 Tesla scanner (Siemens Healthineers, Erlangen, Germany). Detailed acquisition protocols can be found in the Supplementary Information. Functional MRI measurement: Detailed procedures of the fMRI experiment are provided in the Supplementary Information 33 . Briefly, participants were instructed to consume a small amount of commercially available palatable juice during the fMRI scan (Figure S1 , Table S3). Statistics Online survey data First, in Japanese samples, the gender differences in the WSSQ, SCS, age, and BMI were assessed (Table 1 ). Then, a generalized linear mixed models (GLMM) tested associations between WBI, self-consciousness, and BMI. In the GLMM, BMI was set as a dependent variable, and self-devaluation, fear of enacted stigma, public- and private SCS, and age were set as predictor variables, and gender was set as a random effect (Supplementary Information). The generalized linear model (GLM), without the random effect from the GLMM, was developed in men and women separately. Based on the results of GLMM, a model comparison was performed to investigate the relationships between BMI, self-devaluation, and public SCS (Figure S2) using a cross-validation analysis. A cross-validation analysis was conducted with the cvsem package in R 34 , 35 using k = 10 folds to evaluate the performance of two mediation models based on the Kullback-Leibler Divergence (KL-D). In Model 1, self-devaluation was set as a predictor of public SCS, public SCS was set as a predictor of BMI, and self-devaluation was set as a predictor of BMI. The mediation effect of public SCS on the path from self-devaluation to BMI was also estimated. In Model 2, BMI was set as a predictor of public SCS, and public SCS as well as BMI were set as predictors of self-devaluation. The mediation effect of public SCS on the path from BMI to self-devaluation was also estimated. In Model 1 and 2, the effect of gender was controlled. Next, the mediation effect of public SCS on the association between BMI and self-devaluation was examined using the best model suggested by the model comparison. A mediation analysis using the lavaan package in R 36 with 5,000 bootstrapped samples was conducted to assess the mediation effect of self-devaluation on BMI through public SCS, controlling for the effect of gender. For this analysis, all numeric variables were centered. In South Korea, Germany, and the United States, the gender differences in the WSSQ, SCS, age, and BMI were assessed (Table 2 ). Then, the same GLMM and GLM used in Japanese samples were fitted for data from each country. Subsequently, multi-group structural equation modeling (SEM) examined whether the mediation effect of public SCS differed in the four countries. Multi-group SEM was conducted using the lavaan package in R 36 . For this analysis, numeric variables, except public SCS, were centered across the four countries. The Japanese version of the SCS was rated using a 7-point Likert scale, although the Korean, German, and original SCS were rated using a 5-point Likert scale. Thus, public SCS was centered and divided by the SD to normalize data across the four countries. First, in each country, a simple mediation model controlling for gender was estimated. Then, the constrained model was estimated. This model enforced equality of all regression paths and the residual variances across countries to test for uniformity in mediation effects of public SCS. Bootstrapping with 5,000 samples was used to estimate standard errors. Subsequently, a chi-squared difference test was employed to compare these two (constrained and unconstrained) models. The same multi-group SEM was performed in men and women separately, without controlling for the effect of gender. Additionally, the correlation coefficients between BMI and self-devaluation and those between BMI and public SCS were compared between Japan and the other countries. The statistical significance threshold for this comparison was set at p < 0.016 (0.05/3) using the Bonferroni adjustment. Brain imaging data For structural images, voxel-based morphometry (VBM) was applied. Conventional preprocessing, including skull-strapping, segmentation, normalization, and smoothing, was performed. Subsequently, a voxel-wise general linear model (GLM) including preprocessed grey matter images as a dependent variable, self-devaluation or public SCS as explanatory variables, and BMI and estimated total intracranial volume as nuisance variables was applied. The predicted effect of these analyses was tested using an ROI approach. For the ROI, a sphere with a radius of 10 mm centered on [x, y, z] = [-1, 27, -2.3] in the sACC was set based on previous studies 28 , 30 . The unpredicted effects were tested using whole brain analysis (Supplementary Information). Detailed analysis procedures for functional images were provided in the Supplementary Information. Briefly, conventional preprocessing, including slice-timing correction, field map correction, realigning and unwarping, normalization onto the standard Montreal Neurological Institute space, and smoothing, were performed. At the individual level, the condition-specific effects at each voxel of preprocessed images were estimated using a GLM. Then, a group-level voxel-wise GLM analysis with self-devaluation or public SCS as a covariate-of-interest and gender as a covariate-of-no-interest was performed on individual brain response to palatable liquid consumption estimated at the individual level. The predicted effect of these analyses was tested using the ROI approach. The unpredicted effects were tested using whole brain analysis. Then, the generalized psychophysiological interaction (gPPI) analysis was conducted to test the association between whole brain functional connectivity of the sACC and self-devaluation or public SCS. Results Associations among WBI, BMI, and self-consciousness BMI was positively associated with self-devaluation (β = 0.30, p < 0.001) and age (β = 0.02, p = 0.038), and negatively associated with public SCS (β = -0.04, p < 0.001) (Table S4). In men, BMI was positively associated with self-devaluation (β = 0.35, p < 0.001) and age (β = 0.04, p = 0.028), and negatively associated with public SCS (β = -0.04, p = 0.001) (Table S4). In women, BMI was positively associated with self-devaluation (β = 0.28, 95% p < 0.001) and negatively associated with public SCS (β = -0.04, p < 0.001) (Table S4). The model comparison showed that Model 1 demonstrated a significantly lower average KL-D of 0.07 (Standard Error (SE) = 0.03), indicating that it better approximated the true distribution of the data than did Model 2, which had a KL-D of 3.14 (SE = 0.25). This suggested that Model 1 was more effective in explaining the data. A significant indirect effect of self-devaluation on BMI through public SCS, with an estimate of -0.007 (SE = 0.002, 95% confidence interval (CI) = [-0.012, -0.004], p = 0.001) (Fig. 1 ) was observed. The overall model fit was adequate, with a comparative fit index (CFI) = 1.000, root mean square error of approximation (RMSEA) = 0.00, and standardized root mean square residual (SRMR) = 0.00, as values above 0.95 for CFI, below 0.08 for SRMR, and below 0.06 for RMSEA are acceptable 37 . In men, the indirect effect of self-devaluation was not significant, with an estimate of -0.012 (SE = 0.007, 95% CI = [-0.029, -0.003], p = 0.062) demonstrating an overall adequate model fit, with a CFI = 1.000, RMSEA = 0.00, and SRMR = 0.00 (Figure S3a). In women, a significant indirect effect of self-devaluation was observed, with an estimate of -0.023 (SE = 0.007, 95% CI = [-0.038, -0.012], p < 0.001) demonstrating an overall adequate model fit, with a CFI = 1.000, RMSEA = 0.00, and SRMR = 0.00 (Figure S3b). Cultural differences in associations among WBI, BMI, and self-consciousness In South Korea, BMI was positively associated with self-devaluation (β = 0.23, p < 0.001) and age (β = 0.05, p = 0.023) and negatively associated with public SCS (β = -0.10, p = 0.008). In Germany, BMI was positively associated with self-devaluation (β = 0.19, p < 0.001) and age (β = 0.14, p < 0.001). In the United States, BMI was positively associated with self-devaluation (β = 0.24, p < 0.001), private SCS (β = 0.15, p = 0.020), and age (β = 0.14, p = 0.023), and negatively associated with public SCS (β = -0.20, p = 0.004) (Table S4). In men and women, GLM revealed varied associations among BMI, WBI, and self-consciousness. Detailed results can be found in Table S4. The mediation effects of public SCS significantly differed across countries in total (Δχ²(12) = 980.59, p < 0.001) (Table 4 , Fig. 1 ), in men (Δχ²(6) = 298.92, p < 0.001) (Table 4 , Figure S3a) and in women (Δχ²(6) = 568.48, p < 0.001) (Table 4 , Figure S3b). Table 4 The standardized indirect effects of public self-consciousness on BMI through self-devaluation β Standard error 95% confidence interval (lower, upper) z-value p-value Total (men and women) Japan -0.007 0.002 -0.012, -0.004 -3.396 0.001 South Korea -0.014 0.008 -0.034, -0.003 -1.913 0.056 Germany -0.025 0.012 -0.050, -0.002 -2.031 0.042 United States -0.031 0.015 0.064, -0.004 -2.097 0.036 Men Japan -0.009 0.006 -0.023, -0.001 -1.612 0.107 South Korea -0.003 0.007 -0.027, 0.004 -0.527 0.598 Germany -0.029 0.018 -0.072, 0.002 -1.589 0.112 United States -0.020 0.027 -0.082, 0.024 -0.751 0.453 Women Japan -0.016 0.005 -0.028, -0.007 -2.991 0.003 South Korea -0.031 0.016 -0.070, -0.008 -2.002 0.045 Germany -0.022 0.016 -0.059, 0.007 -1.332 0.183 United States -0.034 0.018 -0.078, -0.006 -1.880 0.060 The correlation coefficient between BMI and self-devaluation, after adjusting for gender, was markedly higher in Japan (r = 0.46, p < 0.001) than in South Korea (r = 0.28, p < 0.001), Germany (r = 0.20, p < 0.001), and the United States (r = 0.21, p < 0.001). The differences in correlation coefficients were statistically significant: z = 1.51, p < 0.001 (South Korea vs. Japan); z = 8.01, p < 0.001 (Germany vs. Japan); z = 7.70, p 0.45). In men and women, the correlation coefficients between BMI and self-devaluation were significantly different in Japan than in other countries. In men, the correlation coefficient between BMI and self-devaluation was significantly greater in Japan (r = 0.53, p < 0.001) than in South Korea (r = 0.36, p < 0.001), Germany (r = 0.12, p = 0.049), and the United States (r = 0.11, p = 0.057). The differences in correlation coefficients were statistically significant: z = 2.77, p = 0.006 (South Korea vs Japan); z = 6.64, p < 0.001(Germany vs Japan); z = 6.67, p 0.63). In women, the correlation coefficient between BMI and self-devaluation was significantly greater in Japan (r = 0.51, p < 0.001) than in South Korea (r = 0.30, p < 0.001), Germany (r = 0.25, p < 0.001), and the United States (r = 0.27, p < 0.001). The differences in correlation coefficients were statistically significant: z = 3.64, p < 0.001(South Korea vs. Japan); z = 7.79, p < 0.001 (Germany vs Japan); z = 4.46, p 0.33). Associations among brain structural properties, WBI, and self-consciousness No significant associations between self-devaluation or public SCS and gray matter volumes were observed in the predicted ROI. Whole brain analysis showed public SCS was positively associated with gray matter volumes in the lateral occipital cortex ([x, y, z] = [-26, -78, 42], z = 4.02, cluster size = 155 voxels, p family−wise error rate (FWE)−corrected = 0.036) and precuneus ([x, y, z] = [20, -54, 26], z = 4.30, cluster size = 16 voxels, p FWE−corrected = 0.043) (Fig. 2 a). No association was found between gray matter volumes and self-devaluation. After adjusting for multiple comparisons due to the testing of gray matter volumes in relation to two variables, significance of associations between gray matter volumes in the lateral occipital cortex or precuneus and public SCS were at a trend level (p FWE−corrected = 0.072 and 0.086, respectively). Associations among brain response to palatable liquid consumption, WBI, and self-consciousness Greater self-devaluation was positively associated with sACC response ([x, y, z] = [8, 32, -6], z = 3.72, p FWE−corrected = 0.011, cluster size = 15 voxels) (Fig. 2 b), although public SCS did not reveal any significant association with sACC. After adjusting for multiple comparisons due to the testing of brain response in relation to two variables, the observed associations between sACC response and self-devaluation remained statistically significant (p FWE−corrected = 0.022). Whole brain analysis showed no association between brain response and self-devaluation or public SCS. The gPPI analysis showed that, in contrast to the tasteless condition, a significantly greater association was observed between the public SCS and the connectivity between the sACC and the cluster in the post cingulate cortex (PCC)/precuneus region ([x, y, z] = [-4, -38, 32], t = 3.69, p false discovery rata(FDR)− corrected < 0.001, cluster size = 84 voxels) in the gustatory condition (Fig. 2 c). No association was found between connectivity with the sACC and self-devaluation. Discussion The current study examined the associations among WBI, self-consciousness, and BMI in Japan, South Korea, Germany, and the United States. Additionally, the study explored the associations between WBI or self-consciousness, and the brain’s structural and functional properties. As indicated in a previous study 8 , self-devaluation demonstrated a positive association with BMI in Japan and the other countries, among both men and women, except for men in Germany. WBI was significantly associated with dysregulated eating behaviors, such as overeating 7 , that were used to cope with WBI’s negative psychological effects 21 , which could potentially cause weight gain 7 or weight regain 10 . Contrary to the hypothesis, public self-consciousness was negatively associated with BMI in Japan, South Korea, and the United States. A significant preference for thinness exists in Asian and Western countries 38 , and there is a common belief that weight can be controlled through diet and exercise 6 , and that individuals who lack the willpower to control these habits are significantly susceptible to weight gain 21 . Thus, given that public self-consciousness is the awareness of the self as a social and public object 17 , individuals with greater public self-consciousness may be more sensitive to the pressure to remain thin for both aesthetic and social reasons. Furthermore, since public self-consciousness denotes attentiveness to the self as viewed by others 17 , it would help individuals recognize themselves objectively. Thus, in the same way that keeping a daily food diary helps to objectively recognize one's own eating habits, change eating behavior, and lead to significant weight loss 39 , public self-consciousness would help to objectively monitor individuals’ eating habits and maintain healthy diet. Additionally, as the results of GLMM or GLM and model comparison analysis revealed, self-devaluation could cause weight gain, whereas public self-consciousness demonstrated a mediation effect, mitigating the weight gain driven by self-devaluation in the Japanese. Overall, self-devaluation could be a causative agent rather than a consequence of weight gain, whereas public self-consciousness may attenuate the positive impact of self-devaluation on weight gain. Since the majority of previous studies on WBI have been conducted in the United States with women with excess weight 2 , conducting WBI studies in other regions with populations that have a wider range of BMI seemed crucial. Thus, the present study was conducted in four countries among individuals with wide-ranging BMI. The multi-group SEM analysis revealed that the mediation effect of public self-consciousness on the relationship between self-devaluation and BMI significantly varied across Japan, South Korea, Germany, and the United States. Previous studies reveal cultural differences in public self-consciousness 22 . For example, power distance—the distance a person feels or maintains between themselves and a person in a position of power 40 , which is pronounced in Asian countries 41 —positively affected public self-consciousness, which in turn positively influenced consumers’ intention to eat healthfully 24 . Moreover, because our data revealed significant mediating effects of public self-consciousness among women from Asian countries (South Korea and Japan), a gender effect on cultural differences in the mediating effect of public self-consciousness is plausible. Public self-consciousness had a more substantial influence on the internalization of ideal appearance among South Korean females than among German females 23 . Thus, Asian women may be more affected by public self-consciousness, which can lead to an internalization of a preference for thinness. Consequently, the positive effect of self-devaluation on BMI may be mitigated. In fact, from 1990 to 2022, although the prevalence of underweight people declined in the majority of the 200 countries for both men and women, South Korea and Japan were the sole regions to exhibit an epidemiologically significant increase in prevalence of being underweight among women, notwithstanding their classification as high-income nations 1 . Additionally, in comparison to the other three studied countries, self-devaluation exhibited a stronger positive correlation with BMI in Japan, despite Japan having the lowest BMI among them. Thus, public self-consciousness likely exerts a more pronounced negative mediating effect on the relationship between self-devaluation and BMI in Japanese women. Consequently, the negative moderating effect of public self-consciousness on BMI may vary across countries and is particularly pronounced among women in Japan although there are cultural and regional variations in factors influencing weight maintenance, such as genetic, biological, and environmental elements. Structural brain imaging data showed that public self-consciousness was positively associated with gray matter volume in the lateral occipital cortex and precuneus, and these results are consistent with a previous MRI study 42 . The precuneus and its surrounding regions, including the PCC, could play significant roles in self-awareness, mental representations related to oneself 43 , and speculating or understanding how others perceive one's physical and personality traits (e.g., "I think my friend thinks I am selfish") 44 . Consequently, the precuneus and the lateral occipital cortex may play a role in self-recognition by considering how others judge an individual. Subsequently, the sACC response was positively related with self-devaluation, and greater sACC–PCC/precuneus connectivity was positively related to public self-consciousness. The sACC has a wide range of neural connections with various regions including the precuneus 25 , and is involved with food-reward processing 27 , social prediction errors 29 , 30 , and observation-driven social learning 31 . Social approval prediction errors, which were calculated as the difference between the feedback received from others (e.g., how likable the person was) and the participants' expected social feedback, were significantly associated with the sACC 30 . Such prediction errors in the sACC could be used for observation-driven social learning through direct experience or by observing the action and outcome of another person 31 . Thus, the sACC could play a role in internalizing negative stereotypes about people with higher weights. The sACC is also involved in food reward processing 27 . Therefore, during palatable liquid consumption, the sACC might evaluate food reward under the influence of the degree of WBI. Furthermore, greater sACC–precuneus/PCC connectivity was positively associated with public self-consciousness. Alterations in sACC and precuneus/PCC connection have been linked to eating disorders 45 and depression 46 , which is characterized by a lack of motivation and anhedonia. Thus, this neural connection could play a role in processing food-reward value. Overall, public self-consciousness exhibited a negative mediating effect on the positive impact of self-devaluation on BMI, and greater public self-consciousness was associated with increased gray matter volumes in the precuneus and greater sACC–precuneus/PCC functional connectivity, suggesting that public self-consciousness may exert a negative mediating effect on the positive effect of self-devaluation on BMI by modulating the sACC–precuneus/PCC connectivity. This study has some limitations. First, although the online survey suggests that self-devaluation is a cause rather than a consequence of weight gain, the causal relationship between weight gain and self-devaluation should be confirmed by longitudinal studies. Second, this study focused on WBI, BMI, and self-consciousness, ignoring factors like socioeconomic status 5 , which significantly influence WBI. Future studies should consider other factors to better understand WBI. Third, public self-consciousness was linked to gray matter volume in the precuneus, but this region doesn't overlap with the precuneus/PCC cluster seen in the connectivity analysis. Since the precuneus may exhibit enhanced connectivity with nearby areas as well as intra-hemispheric connectivity 47 , the current findings would indicate that public self-consciousness is controlled across the precuneus and adjacent regions. However, it is important to note that differences in participant or brain imaging techniques between structural and functional brain imaging could potentially account for the observed discrepancies in brain imaging findings. Finally, brain measures were performed on Japanese samples only. Cultural differences found among WBI, BMI, and public self-consciousness make a cross-cultural brain imaging comparison essential for future studies. Conclusion The current study has found that public self-consciousness would negatively mediate the positive effect of self-devaluation on BMI, and its mediating effect varied across different cultures. Furthermore, brain measurements have indicated that public self-consciousness attenuates the positive association between BMI and self-devaluation by modulating the sACC–precuneus/PCC connectivity. Although excessive public self-consciousness would be associated with maladaptive eating 20 , proper adjustment of public self-consciousness would be a potential therapeutic target to mitigate the negative health consequences of WBI. Declarations Acknowledgments We would like to thank all those involved for participating in this study. Author contributions Y.N.: Conceptualization, Data collection, Data analysis, Writing original draft. K.H and N.M: Review & editing. All authors reviewed and approved the manuscript. Funding This work was funded by the Grant-in-Aid for Transformative Research Areas (A) of Japan Society for the Promotion of Science (JP21H05172). Data availability statement Data and codes for analysis are available indefinitely at https://doi.org/10.17605/OSF.IO/UTKVE Competing interests The authors declare no competing interests. References Phelps, N. H. et al. Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults. Lancet 403 , 1027–1050. 10.1016/S0140-6736(23)02750-2 (2024). Nutter, S., Saunders, J. F. & Waugh, R. Current trends and future directions in internalized weight stigma research: a scoping review and synthesis of the literature. J. Eat. Disord . 12 , 98. 10.1186/s40337-024-01058-0 (2024). Alberga, A. S., Russell-Mayhew, S., von Ranson, K. M. & McLaren, L. Weight bias: a call to action. J. Eat. Disord . 4 , 34. 10.1186/s40337-016-0112-4 (2016). Pearl, R. L. & Puhl, R. M. Weight bias internalization and health: a systematic review. Obes. Rev. 19 , 1141–1163. 10.1111/obr.12701 (2018). Hughes, A. M. et al. Demographic, socioeconomic and life-course risk factors for internalized weight stigma in adulthood: evidence from an English birth cohort study. Lancet Reg. Health Eur. 40 , 100895. 10.1016/j.lanepe.2024.100895 (2024). Forouhar, V., Edache, I. Y., Salas, X. R. & Alberga, A. S. Weight bias internalization and beliefs about the causes of obesity among the Canadian public. BMC Public. Health . 23 , 1621. 10.1186/s12889-023-16454-5 (2023). Romano, K. A. et al. Weight Bias Internalization and Psychosocial, Physical, and Behavioral Health: A Meta-Analysis of Cross-Sectional and Prospective Associations. Behav. Ther. 54 , 539–556. https://doi.org/10.1016/j.beth.2022.12.003 (2023). Nakamura, Y. & Asano, M. Developing and validating a Japanese version of the Weight Self-Stigma Questionnaire. Eat. Weight Disord . 28 , 44. 10.1007/s40519-023-01573-0 (2023). Feig, E. H. et al. Weight bias internalization and its association with health behaviour adherence after bariatric surgery. Clin. Obes. 10 , e12361. 10.1111/cob.12361 (2020). Pearl, R. L., Puhl, R. M., Lessard, L. M., Himmelstein, M. S. & Foster, G. D. Prevalence and correlates of weight bias internalization in weight management: A multinational study. SSM Popul. Health . 13 , 100755. 10.1016/j.ssmph.2021.100755 (2021). Romano, K. A., Heron, K. E. & Henson, J. M. Examining associations among weight stigma, weight bias internalization, body dissatisfaction, and eating disorder symptoms: Does weight status matter? Body Image . 37 , 38–49. 10.1016/j.bodyim.2021.01.006 (2021). Macho, S., Andrés, A. & Saldaña, C. Weight discrimination, BMI, or weight bias internalization? Testing the best predictor of psychological distress and body dissatisfaction. Obes. (Silver Spring) . 31 , 2178–2188. 10.1002/oby.23802 (2023). Theron, W. H., Nel, E. M. & Lubbe, A. J. Relationship between body-image and self-consciousness. Percept. Mot Skills . 73 , 979–983. 10.2466/pms.1991.73.3.979 (1991). Panayiotou, G. & Kokkinos, C. M. Self-consciousness and psychological distress: A study using the Greek SCS. Pers. Indiv. Differ. 41 , 83–93. https://doi.org/10.1016/j.paid.2005.10.025 (2006). Kanamoto, M. & Kanamoto, M. Relationship between body-consciousness and self-consciousness in male and female adolescents. Hum. Perform. Meas. 2 , 57–64. 10.14859/jjtehpe.2.57 (2002). DaSilveira, A., DeSouza, M. L. & Gomes, W. B. Self-consciousness concept and assessment in self-report measures. Front. Psychol. 6 , 930. 10.3389/fpsyg.2015.00930 (2015). Fenigstein, A., Scheier, M. F. & Buss, A. H. Public and private self-consciousness: Assessment and theory. J. Consult. Clin. Psychol. 43 , 522–527. 10.1037/h0076760 (1975). Pinel, E. C. You're Just Saying That Because I'm a Woman: Stigma Consciousness and Attributions to Discrimination. Self Identity . 3 , 39–51. 10.1080/13576500342000031 (2004). Sun, Q., Wang, N., Li, S. & Zhou, H. Local spatial obesity analysis and estimation using online social network sensors. J. Biomed. Inf. 83 , 54–62. 10.1016/j.jbi.2018.03.010 (2018). Jostes, A., Pook, M. & Florin, I. Public and private self-consciousness as specific psychopathological features. Pers. Indiv. Differ. 27 , 1285–1295. https://doi.org/10.1016/S0191-8869(99)00077-X (1999). Pearl, R. L. Internalization of weight bias and stigma: Scientific challenges and opportunities. Am. Psychol. 79 , 1308–1319. 10.1037/amp0001455 (2024). Delvecchio, E., Mabilia, D., Miconi, D., Chirico, I. & Li, J. B. Self-consciousness in Chinese and Italian adolescents: An exploratory cross-cultural study using the ASC. Curr. Psychology: J. Diverse Perspect. Diverse Psychol. Issues . 34 , 140–153. 10.1007/s12144-014-9247-0 (2015). Hong, K. H. A cross-cultural study on the influence of public self-consciousness and sociocultural pressure over ideal appearance attitude and body shame. J. Korean Soc. Cloth. Text. 34 , 1731–1741. 10.5850/jksct.2010.34.10.1731 (2010). Sun, T., Horn, M. & Merritt, D. Impacts of cultural dimensions on healthy diet through public self-consciousness. J. Consumer Mark. 26 , 241–250. 10.1108/07363760910965846 (2009). Vergani, F. et al. Anatomic Connections of the Subgenual Cingulate Region. Neurosurgery 79 , 465–472. 10.1227/neu.0000000000001315 (2016). Drevets, W. C., Savitz, J. & Trimble, M. The subgenual anterior cingulate cortex in mood disorders. CNS Spectr. 13 , 663–681. 10.1017/s1092852900013754 (2008). Bore, M. C. et al. Distinct neurofunctional alterations during motivational and hedonic processing of natural and monetary rewards in depression – a neuroimaging meta-analysis. Psychol. Med. 54 , 639–651. 10.1017/S0033291723003410 (2024). Wittmann, M. K. et al. Self-Other Mergence in the Frontal Cortex during Cooperation and Competition. Neuron 91 , 482–493. 10.1016/j.neuron.2016.06.022 (2016). Lockwood, P. L. & Wittmann, M. K. Ventral anterior cingulate cortex and social decision-making. Neurosci. Biobehav Rev. 92 , 187–191. 10.1016/j.neubiorev.2018.05.030 (2018). Will, G. J., Rutledge, R. B., Moutoussis, M. & Dolan, R. J. Neural and computational processes underlying dynamic changes in self-esteem. Elife 6 10.7554/eLife.28098 (2017). Joiner, J., Piva, M., Turrin, C. & Chang, S. W. C. Social learning through prediction error in the brain. NPJ Sci. Learn. 2 , 8. 10.1038/s41539-017-0009-2 (2017). Lillis, J., Luoma, J. B., Levin, M. E. & Hayes, S. C. Measuring weight self-stigma: the weight self-stigma questionnaire. Obes. (Silver Spring) . 18 , 971–976. 10.1038/oby.2009.353 (2010). Nakamura, Y. & Ishida, T. The effect of multiband sequences on statistical outcome measures in functional magnetic resonance imaging using a gustatory stimulus. NeuroImage 300 , 120867. https://doi.org/10.1016/j.neuroimage.2024.120867 (2024). Browne, M. W. & Cudeck, R. Alternative Ways of Assessing Model Fit. Sociol. Methods Res. 21 , 230–258. 10.1177/0049124192021002005 (1992). Cudeck, R. A. & Browne, M. W. Cross-Validation Of Covariance Structures. Multivar. Behav. Res. 18 2 , 147–167 (1983). Rosseel, Y. & Lavaan An R package for structural equation modeling and more. Version 0.5–12 (BETA). J. Stat. Softw. 48 http://doi.org/10.18637/jss.v048.i02 (2012). Hu, L. & Bentler, P. M. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct. Equation Modeling: Multidisciplinary J. 6 , 1–55. 10.1080/10705519909540118 (1999). Swami, V. Cultural influences on body size ideals: Unpacking the impact of Westernization and modernization. Eur. Psychol. 20 , 44–51. 10.1027/1016-9040/a000150 (2015). Hollis, J. F. et al. Weight loss during the intensive intervention phase of the weight-loss maintenance trial. Am. J. Prev. Med. 35 , 118–126. 10.1016/j.amepre.2008.04.013 (2008). Hofstede, G. Culture's Consequences: International Differences in Work-Related Values (SAGE, 1984). Witt, M. A. & Redding, G. Asian business systems: institutional comparison, clusters and implications for varieties of capitalism and business systems theory. Socio-Economic Rev. 11 , 265–300. 10.1093/ser/mwt002 (2013). Morita, T., Asada, M. & Naito, E. Gray-Matter Expansion of Social Brain Networks in Individuals High in Public Self-Consciousness. Brain Sci. 11 , 374 (2021). Cavanna, A. E. & Trimble, M. R. The precuneus: a review of its functional anatomy and behavioural correlates. Brain 129 , 564–583. 10.1093/brain/awl004 (2006). McAdams, C. J. & Krawczyk, D. C. Who am I? How do I look? Neural differences in self-identity in anorexia nervosa. Soc. Cogn. Affect. Neurosci. 9 , 12–21. 10.1093/scan/nss093 (2014). Datta, N., Hughes, A., Modafferi, M. & Klabunde, M. An FMRI meta-analysis of interoception in eating disorders. NeuroImage 305 , 120933. https://doi.org/10.1016/j.neuroimage.2024.120933 (2025). Zhu, Z. et al. Hyperconnectivity between the posterior cingulate and middle frontal and temporal gyrus in depression: Based on functional connectivity meta-analyses. Brain Imaging Behav. 16 , 1538–1551. 10.1007/s11682-022-00628-7 (2022). Jitsuishi, T. & Yamaguchi, A. Characteristic cortico-cortical connection profile of human precuneus revealed by probabilistic tractography. Scientific Reports 13, (1936). 10.1038/s41598-023-29251-2 (2023). Additional Declarations No competing interests reported. Supplementary Files SupplementaryInformation.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6390971","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":456391810,"identity":"3e668bae-b2cb-48d9-a588-d38dff85e891","order_by":0,"name":"Yuko Nakamura","email":"data:image/png;base64,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","orcid":"","institution":"The University of Tokyo","correspondingAuthor":true,"prefix":"","firstName":"Yuko","middleName":"","lastName":"Nakamura","suffix":""},{"id":456391811,"identity":"e88b22d6-0b09-4669-9610-d7ccb6e6eda5","order_by":1,"name":"Karin Hayashi","email":"","orcid":"","institution":"Toho University Sakura Medical Center, Shimoshizu Sakura","correspondingAuthor":false,"prefix":"","firstName":"Karin","middleName":"","lastName":"Hayashi","suffix":""},{"id":456391812,"identity":"865be04c-8d20-4281-8f97-ce9590715571","order_by":2,"name":"Norihide Maikusa","email":"","orcid":"","institution":"The University of Tokyo","correspondingAuthor":false,"prefix":"","firstName":"Norihide","middleName":"","lastName":"Maikusa","suffix":""}],"badges":[],"createdAt":"2025-04-07 06:53:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6390971/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6390971/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82889475,"identity":"d9af6d63-4402-4a70-8885-66575117236c","added_by":"auto","created_at":"2025-05-16 12:06:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":21612,"visible":true,"origin":"","legend":"\u003cp\u003eAssociations among self-devaluation of the Weight Self-Stigma Questionnaire, public self-consciousness of the Self-Consciousness Scale (public SCS), and body mass index (BMI) in Japan, South Korea, Germany, and the United States. The standardized regression coefficients for the relationships are presented on the paths. The standardized regression coefficient between self-devaluation and BMI (direct effect), controlling for public self-consciousness and gender, is provided in parentheses. Dashed line paths indicate non-significance, p = 0.05 or more. Solid line paths indicate significance, p \u0026lt; 0.05. BMI: body mass index; Public SCS: public self-consciousness of the self-conscious scale.\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6390971/v1/63f29974b817875a5cd65ac4.png"},{"id":82889473,"identity":"e0603d27-258a-4683-bbf2-17fe1d475d0f","added_by":"auto","created_at":"2025-05-16 12:06:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":63785,"visible":true,"origin":"","legend":"\u003cp\u003eAssociations between brain images and self-devaluation of the Weight Self-Stigma Questionnaire or public self-consciousness of the Self-Consciousness Scale. (A) Clusters with significant associations between public self-consciousness and gray matter volumes in the occipital cortex (left) and precuneus (right). Scatter plots indicate associations between gray matter volumes (y-axis) and public self-consciousness (x-axis). (B) A cluster with a significant association between self-devaluation and the subgenual anterior cingulate cortex (sACC) response to palatable liquid consumption. The scatter plot indicates the association between brain response (y-axis) and self-devaluation (x-axis). (C) A cluster showing a significant effect of condition on associations between connectivity with the sACC and public self-consciousness. The scatter plot indicates associations between sACC–precuneus/PCC connectivity (y-axis) and public self-consciousness (x-axis). R\u003csup\u003e2\u003c/sup\u003e is the square of the correlation. Public SCS: public self-consciousness of the self-conscious scale.\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6390971/v1/af44e96c5b0bccb8a08b6c7e.png"},{"id":90980341,"identity":"7be792e0-f8f1-44c8-8020-88f15254beee","added_by":"auto","created_at":"2025-09-10 09:17:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1351508,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6390971/v1/4463cab5-5123-49bd-bae6-ecec2b519549.pdf"},{"id":82889479,"identity":"89538736-fc6d-40b6-ad30-c26aacc73ae0","added_by":"auto","created_at":"2025-05-16 12:06:12","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":3383557,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-6390971/v1/9cc238b300586b8747ec1388.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Self-Consciousness Mitigates Weight Gain related to Internalized Weight Bias: Cross-Cultural Survey and Brain Imaging","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe prevalence of obesity has increased worldwide\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, with global adult obesity more than doubling in the last 30 years. The rapid rise in the prevalence of obesity has led to more research on the adverse effects of weight bias and weight bias internalization (WBI) \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Weight bias is defined as holding negative stereotypes about people with higher weights, such as being lazy, lacking willpower, or having poor eating habits, and the resulting negative attitudes toward these individuals \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. When individuals apply negative weight stereotypes to themselves and denigrate themselves because of their body weight, WBI occurs \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. WBI tends to be more pronounced in women \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e and individuals with higher body weights \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. WBI is associated with poor psychosocial (e.g., negative mental health), physical (e.g., health-related quality of life), and behavioral (e.g., disordered eating) health \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe associations between WBI and body mass index (BMI) or weight change have been well studied \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. For instance, higher WBI is associated with greater BMI even in a predominantly healthy weight population (n\u0026thinsp;=\u0026thinsp;1454) \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Additionally, WBI is negatively associated with weight loss \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e and positively associated with weight gain \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. WBI is also associated with various psychological factors, such as poor body image \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, elevated body dissatisfaction \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, and psychological distress \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, all of which are related to self-consciousness \u003csup\u003e\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Self-consciousness is defined as the awareness of oneself, including one's body, actions, and thoughts, and how others perceive them \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. The concept of self-consciousness encompasses both private and public dimensions. Private self-consciousness is defined as the awareness of one's personal inner feelings, while public self-consciousness is the concern about how one is perceived by others \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Thus, WBI, which involves the process of being aware of weight stigma, applying it to oneself, and devaluing one's self-worth, is likely related to self-consciousness. In fact, self-consciousness is believed to be linked to stigma consciousness, which refers to a focus on one's stereotyped status \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Self-consciousness also influences weight management \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e and eating behavior \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, thereby potentially influencing the association between WBI and BMI. Moreover, given that WBI is reported in individuals across the weight spectrum \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, excess weight may not be its sole cause, as self-consciousness could also contribute to WBI. However, the associations among WBI, BMI, and self-consciousness remain unclear. Therefore, the current study aims to examine the effect of self-consciousness on the relationship between WBI and BMI.\u003c/p\u003e \u003cp\u003eThe current study also examined cultural differences in the associations among WBI, BMI, and self-consciousness across four countries (Japan, South Korea, Germany, and the United States). Cultural differences in self-consciousness have long been studied \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e and are related to eating habits. For example, the association between public self-consciousness and the intention to eat a healthy diet was modulated by cultural differences \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Additionally, as the majority of WBI research has been conducted in the United States among women with higher BMI \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, undertaking research in diverse cultures could provide a better understanding of WBI.\u003c/p\u003e \u003cp\u003eFurthermore, the current study examined the associations between WBI or self-consciousness and the brain properties to investigate the neural mechanisms underlining WBI, considering the subgenual anterior cingulate cortex (sACC) as the region of interest (ROI). The sACC is a subregion of the cingulate cortex and has a wide-ranging neural connection with limbic, prefrontal, parietal, and mesiotemporal areas \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. The sACC contributes to the modulation of emotional behavior \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e and food-reward processing \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e; self-awareness, encompassing the reflection of one's recent behavioral history \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e; and social decision-making, specifically the processing of prediction errors in social interactions (i.e., social prediction errors), such as the calculation of differences between actual and predicted intentions of others \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Thus, the sACC could play a significant role in self-consciousness by monitoring one's thoughts and speculating on how others perceive them. Furthermore, given its involvement in observation-driven social learning \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, sACC could be associated with WBI by facilitating learning weight stigma and internalizing it. Therefore, using the sACC as the ROI, magnetic resonance imaging (MRI) measurements of brain structure and responses to food reward were conducted as preliminary research in a Japanese sample.\u003c/p\u003e \u003cp\u003eIt was hypothesized that greater WBI would be linked to heightened self-consciousness, as self-consciousness focuses on one's body and how others see it \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Since self-consciousness is involved in maladaptive eating \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, it could positively mediate the association between WBI and weight status. Due to cultural differences in self-consciousness \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, its mediating effect would differ across countries. Furthermore, the sACC could contribute to increasing WBI by playing a role in self-awareness \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e and predicting the intentions of others \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eExperimental design\u003c/h2\u003e \u003cp\u003eFirst, an online survey was administered to assess WBI, self-consciousness, and BMI in Japan, South Korea, Germany, and the United States. Then, structural and functional MRI (fMRI) measures were performed on Japanese young adults. All studies were approved by the Ethics Committee of the Department of Arts and Sciences, University of Tokyo (Approval No. 812-2). This study adhered to the principles of the Declaration of Helsinki.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eOnline survey\u003c/h2\u003e \u003cp\u003eParticipants aged 18\u0026ndash;45 who had lived in the same country for more than 10 years were included in the online survey. Commercial survey sampling and administration companies were contracted to recruit participants and administer the online survey. After excluding those who failed to enter their responses, a total of 1946 participants from Japan, 500 from South Korea, 598 from Germany, and 580 from the United States were included in the statistical analyses (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) (Supplementary Information). Before beginning the online survey, participants were asked to provide their consent to contribute their data for research purposes; those who consented to participate in this research were included. Participants provided their age, gender, weight, and height, and completed questionnaires about WBI and self-consciousness.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic characteristics of the participants in the Japanese sample.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1946)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;689)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1257)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGender difference\u003c/p\u003e \u003cp\u003eP-value*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.38 \u0026plusmn; 6.90\u003c/p\u003e \u003cp\u003e(18\u0026ndash;45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.43 \u0026plusmn; 6.79\u003c/p\u003e \u003cp\u003e(18\u0026ndash;45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.81 \u0026plusmn; 6.89\u003c/p\u003e \u003cp\u003e(18\u0026ndash;45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index (kg/m2)\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.53 \u0026plusmn; 3.62\u003c/p\u003e \u003cp\u003e(13.79\u0026ndash;42.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.72 \u0026plusmn; 3.65\u003c/p\u003e \u003cp\u003e(14.87\u0026ndash;42.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.88 \u0026plusmn; 3.43\u003c/p\u003e \u003cp\u003e(13.79\u0026ndash;41.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eWeight Self-Stigma Questionnaire\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-devaluation\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.91 \u0026plusmn; 6.35\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.66 \u0026plusmn; 5.97\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.60 \u0026plusmn; 6.44\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFear of enacted stigma\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.23 \u0026plusmn; 4.68\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.71 \u0026plusmn; 4.29\u003c/p\u003e \u003cp\u003e(6\u0026ndash;27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.52 \u0026plusmn; 4.86\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eSelf-Consciousness Scale\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic self-consciousness\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.12 \u0026plusmn; 13.29\u003c/p\u003e \u003cp\u003e(11\u0026ndash;77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.07 \u0026plusmn; 13.51\u003c/p\u003e \u003cp\u003e(11\u0026ndash;77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.34 \u0026plusmn; 12.64\u003c/p\u003e \u003cp\u003e(11\u0026ndash;77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate self-consciousness\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.28 \u0026plusmn; 10.79\u003c/p\u003e \u003cp\u003e(10\u0026ndash;70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.51 \u0026plusmn; 11.12\u003c/p\u003e \u003cp\u003e(10\u0026ndash;70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.25 \u0026plusmn; 10.48\u003c/p\u003e \u003cp\u003e(10\u0026ndash;70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Wilcoxon rank-sum test.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eSD: Standard deviation\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic characteristics of the participants in the samples of three countries.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth Korea\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;500)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;245)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;255)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003cp\u003e( n\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eGender difference (men vs women)\u003c/p\u003e \u003cp\u003eP-value*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.15 \u0026plusmn; 7.48\u003c/p\u003e \u003cp\u003e(15\u0026ndash;45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.01 \u0026plusmn; 7.29\u003c/p\u003e \u003cp\u003e(18\u0026ndash;45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e33.32 \u0026plusmn; 7.58\u003c/p\u003e \u003cp\u003e(18\u0026ndash;45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index (kg/m2)\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.92 \u0026plusmn; 3.74\u003c/p\u003e \u003cp\u003e(14.78\u0026ndash;41.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.33 \u0026plusmn; 3.42\u003c/p\u003e \u003cp\u003e(15.54\u0026ndash;41.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e21.56 \u0026plusmn; 3.53\u003c/p\u003e \u003cp\u003e(14.78\u0026ndash;36.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAsian: 489\u003c/p\u003e \u003cp\u003eWhite/Caucasian: 7\u003c/p\u003e \u003cp\u003eBlack/African American: 1\u003c/p\u003e \u003cp\u003ePrefer not to answer/Don't know: 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAsian: 243\u003c/p\u003e \u003cp\u003eWhite/Caucasian: 1\u003c/p\u003e \u003cp\u003eBlack/African American: 1\u003c/p\u003e \u003cp\u003ePrefer not to answer/Don't know: 0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAsian: 246\u003c/p\u003e \u003cp\u003eWhite/Caucasian: 6\u003c/p\u003e \u003cp\u003eBlack/African American: 0\u003c/p\u003e \u003cp\u003ePrefer not to answer/Don't know: 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eWeight Self-Stigma Questionnaire\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-devaluation\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.89 \u0026plusmn; 5.05\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.56 \u0026plusmn; 4.86\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.21 \u0026plusmn; 5.22\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFear of enacted stigma\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.14 \u0026plusmn; 5.47\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.97 \u0026plusmn; 5.35\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.30 \u0026plusmn; 5.58\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eSelf-Consciousness Scale\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic self-consciousness\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.85 \u0026plusmn; 5.20\u003c/p\u003e \u003cp\u003e(7\u0026ndash;35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.66 \u0026plusmn; 5.35\u003c/p\u003e \u003cp\u003e(7\u0026ndash;35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.04 \u0026plusmn; 5.06\u003c/p\u003e \u003cp\u003e(9\u0026ndash;35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate self-consciousness\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.35 \u0026plusmn; 5.84\u003c/p\u003e \u003cp\u003e(10\u0026ndash;50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.51 \u0026plusmn; 5.77\u003c/p\u003e \u003cp\u003e(10\u0026ndash;50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.20 \u0026plusmn; 5.92\u003c/p\u003e \u003cp\u003e(16\u0026ndash;48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;598)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;284)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;249)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003cp\u003e( n\u0026thinsp;=\u0026thinsp;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eP-value*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.37 \u0026plusmn; 8.08\u003c/p\u003e \u003cp\u003e(18\u0026ndash;45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.74 \u0026plusmn; 7.19\u003c/p\u003e \u003cp\u003e(18\u0026ndash;45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.16\u0026plusmn; 8.05\u003c/p\u003e \u003cp\u003e(18\u0026ndash;45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e26.25 \u0026plusmn; 8.10\u003c/p\u003e \u003cp\u003e(20\u0026ndash;38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index (kg/m2)\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.79 \u0026plusmn; 5.39\u003c/p\u003e \u003cp\u003e(15.00\u0026ndash;53.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.42 \u0026plusmn; 5.33\u003c/p\u003e \u003cp\u003e(16.07\u0026ndash;53.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.20 \u0026plusmn; 5.33\u003c/p\u003e \u003cp\u003e(15.00\u0026ndash;52.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e26.60 \u0026plusmn; 9.81\u003c/p\u003e \u003cp\u003e(18.94\u0026ndash;40.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAsian: 22\u003c/p\u003e \u003cp\u003eWhite/Caucasian: 517\u003c/p\u003e \u003cp\u003eBlack/African American: 17\u003c/p\u003e \u003cp\u003eHispanic/Latino: 11\u003c/p\u003e \u003cp\u003eNative American: 1\u003c/p\u003e \u003cp\u003ePrefer not to answer/Don't know: 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAsian: 5\u003c/p\u003e \u003cp\u003eWhite/Caucasian: 257\u003c/p\u003e \u003cp\u003eBlack/African American: 9\u003c/p\u003e \u003cp\u003eHispanic/Latino: 4\u003c/p\u003e \u003cp\u003eNative American:0\u003c/p\u003e \u003cp\u003ePrefer not to answer/Don't know: 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAsian: 17\u003c/p\u003e \u003cp\u003eWhite/Caucasian: 259\u003c/p\u003e \u003cp\u003eBlack/African American: 8\u003c/p\u003e \u003cp\u003eHispanic/Latino: 6\u003c/p\u003e \u003cp\u003eNative American:1\u003c/p\u003e \u003cp\u003ePrefer not to answer/Don't know: 19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eAsian: 0\u003c/p\u003e \u003cp\u003eWhite/Caucasian: 1\u003c/p\u003e \u003cp\u003eBlack/African American: 0\u003c/p\u003e \u003cp\u003eHispanic/Latino: 1\u003c/p\u003e \u003cp\u003eNative American:0\u003c/p\u003e \u003cp\u003ePrefer not to answer/Don't know: 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eWeight Self-Stigma Questionnaire\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-devaluation\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.43 \u0026plusmn; 6.18\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.99 \u0026plusmn; 5.77\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.98 \u0026plusmn; 6.50\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e11.50 \u0026plusmn; 6.81\u003c/p\u003e \u003cp\u003e(6\u0026ndash;20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.031\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFear of enacted stigma\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.24 \u0026plusmn; 6.18\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.87 \u0026plusmn; 6.07\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.68\u0026plusmn; 6.24\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e13.50 \u0026plusmn; 7.55\u003c/p\u003e \u003cp\u003e(6\u0026ndash;20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eSelf-Consciousness Scale\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic self-consciousness\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.46 \u0026plusmn; 5.72\u003c/p\u003e \u003cp\u003e(7\u0026ndash;35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.99 \u0026plusmn; 5.43\u003c/p\u003e \u003cp\u003e(7\u0026ndash;35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.90\u0026plusmn; 5.90\u003c/p\u003e \u003cp\u003e(7\u0026ndash;35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e22.25 \u0026plusmn; 10.37\u003c/p\u003e \u003cp\u003e(7\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate self-consciousness\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.11 \u0026plusmn; 6.16\u003c/p\u003e \u003cp\u003e(16\u0026ndash;50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.13 \u0026plusmn; 6.03\u003c/p\u003e \u003cp\u003e(16\u0026ndash;47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.50 \u0026plusmn; 5.21\u003c/p\u003e \u003cp\u003e(17\u0026ndash;50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e30.50\u0026plusmn; 9.54\u003c/p\u003e \u003cp\u003e(18\u0026ndash;41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;580)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;282)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;296)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003cp\u003e( n\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eP-value*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.79\u0026plusmn; 7.19\u003c/p\u003e \u003cp\u003e(18\u0026ndash;45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.33 \u0026plusmn; 7.18\u003c/p\u003e \u003cp\u003e(18\u0026ndash;45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.11 \u0026plusmn; 6.16\u003c/p\u003e \u003cp\u003e(16\u0026ndash;50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e23.00 \u0026plusmn; 5.66\u003c/p\u003e \u003cp\u003e(19\u0026ndash;27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index (kg/m2)\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.24\u0026plusmn; 6.98\u003c/p\u003e \u003cp\u003e(12.37\u0026ndash;58.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.38 \u0026plusmn; 6.32\u003c/p\u003e \u003cp\u003e(12.37\u0026ndash;58.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.10 \u0026plusmn; 7.47\u003c/p\u003e \u003cp\u003e(16.12\u0026ndash;58.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e20.01\u0026plusmn; 0.31\u003c/p\u003e \u003cp\u003e(19.79\u0026ndash;20.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAsian: 25\u003c/p\u003e \u003cp\u003eWhite/Caucasian: 314\u003c/p\u003e \u003cp\u003eBlack/African American: 164\u003c/p\u003e \u003cp\u003eHispanic/Latino: 59\u003c/p\u003e \u003cp\u003eNative American:12\u003c/p\u003e \u003cp\u003ePrefer not to answer/Don't know: 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAsian: 17\u003c/p\u003e \u003cp\u003eWhite/Caucasian: 139\u003c/p\u003e \u003cp\u003eBlack/African American: 84\u003c/p\u003e \u003cp\u003eHispanic/Latino: 32\u003c/p\u003e \u003cp\u003eNative American: 7\u003c/p\u003e \u003cp\u003ePrefer not to answer/Don't know: 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAsian: 7\u003c/p\u003e \u003cp\u003eWhite/Caucasian: 175\u003c/p\u003e \u003cp\u003eBlack/African American: 79\u003c/p\u003e \u003cp\u003eHispanic/Latino: 27\u003c/p\u003e \u003cp\u003eNative American:5\u003c/p\u003e \u003cp\u003ePrefer not to answer/Don't know: 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eAsian: 1\u003c/p\u003e \u003cp\u003eWhite/Caucasian: 0\u003c/p\u003e \u003cp\u003eBlack/African American: 1\u003c/p\u003e \u003cp\u003eHispanic/Latino: 0\u003c/p\u003e \u003cp\u003eNative American:0\u003c/p\u003e \u003cp\u003ePrefer not to answer/Don't know: 0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eWeight Self-Stigma Questionnaire\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-devaluation\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.63\u0026plusmn; 6.32\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.99 \u0026plusmn; 6.01\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.23 \u0026plusmn; 6.58\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e15.50 \u0026plusmn; 3.54\u003c/p\u003e \u003cp\u003e(13\u0026ndash;18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFear of enacted stigma\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.63\u0026plusmn; 6.59\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.12 \u0026plusmn; 6.49\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.14 \u0026plusmn; 6.67\u003c/p\u003e \u003cp\u003e(6\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e11.50 \u0026plusmn; 3.54\u003c/p\u003e \u003cp\u003e(9\u0026ndash;14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eSelf-Consciousness Scale\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic self-consciousness\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.80 \u0026plusmn; 6.23\u003c/p\u003e \u003cp\u003e(7\u0026ndash;35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.26 \u0026plusmn; 6.36\u003c/p\u003e \u003cp\u003e(7\u0026ndash;35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.31\u0026plusmn; 6.08\u003c/p\u003e \u003cp\u003e(7\u0026ndash;35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e24.50 \u0026plusmn; 2.12\u003c/p\u003e \u003cp\u003e(23\u0026ndash;26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate self-consciousness\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.53 \u0026plusmn; 6.22\u003c/p\u003e \u003cp\u003e(18\u0026ndash;49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.41 \u0026plusmn; 6.49\u003c/p\u003e \u003cp\u003e(18\u0026ndash;49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.62 \u0026plusmn; 5.97\u003c/p\u003e \u003cp\u003e(18\u0026ndash;49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e37.50 \u0026plusmn; 4.95\u003c/p\u003e \u003cp\u003e(34\u0026ndash;41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e*Wilcoxon rank-sum test.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eSD: Standard deviation\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBrain measurements\u003c/h3\u003e\n\u003cp\u003eA total of 120 Japanese participants were included (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). All participants provided written informed consent. Those with a history of neurological injury; known genetic or medical disorders; previous or current use of psychotropic medications, tobacco, cigarettes, electronic cigarettes; and any MRI exclusion criteria were excluded from the study. Of the participants included in the brain structural measurements, 30 underwent the fMRI experiment (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic characteristics of the participants who completed brain measurements.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStructural MRI measurement\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;120)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGender difference\u003c/p\u003e \u003cp\u003e(men vs women)\u003c/p\u003e \u003cp\u003eP-value*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.88 \u0026plusmn; 5.65\u003c/p\u003e \u003cp\u003e(20\u0026ndash;44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.77 \u0026plusmn; 5.54\u003c/p\u003e \u003cp\u003e(20\u0026ndash;40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.00 \u0026plusmn; 5.81\u003c/p\u003e \u003cp\u003e(20\u0026ndash;44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.661\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index (kg/m2)\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.27\u0026plusmn; 2.81\u003c/p\u003e \u003cp\u003e(16.85\u0026ndash;30.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.09 \u0026plusmn; 2.79\u003c/p\u003e \u003cp\u003e(16.94\u0026ndash;30.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.45 \u0026plusmn; 2.83\u003c/p\u003e \u003cp\u003e(16.85\u0026ndash;28.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.442\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eWeight Self-Stigma Questionnaire\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-devaluation\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.99 \u0026plusmn; 6.10\u003c/p\u003e \u003cp\u003e(6\u0026ndash;27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.03 \u0026plusmn; 5.22\u003c/p\u003e \u003cp\u003e(7\u0026ndash;27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.95 \u0026plusmn; 5.39\u003c/p\u003e \u003cp\u003e(6\u0026ndash;27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFear of enacted stigma\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.15 \u0026plusmn; 3.96\u003c/p\u003e \u003cp\u003e(6\u0026ndash;25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.90 \u0026plusmn; 4.29\u003c/p\u003e \u003cp\u003e(6\u0026ndash;25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.40 \u0026plusmn; 2.64\u003c/p\u003e \u003cp\u003e(6\u0026ndash;16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eSelf-Consciousness Scale\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic self-consciousness\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.46\u0026plusmn; 10.46\u003c/p\u003e \u003cp\u003e(27\u0026ndash;74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.82 \u0026plusmn; 11.28\u003c/p\u003e \u003cp\u003e(28\u0026ndash;74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.10 \u0026plusmn; 9.47\u003c/p\u003e \u003cp\u003e(27\u0026ndash;70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate self-consciousness\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.75\u0026plusmn; 9.27\u003c/p\u003e \u003cp\u003e(21\u0026ndash;70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.40 \u0026plusmn; 9.38\u003c/p\u003e \u003cp\u003e(25\u0026ndash;70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51.10 \u0026plusmn; 9.23\u003c/p\u003e \u003cp\u003e(21\u0026ndash;68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.592\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eFunctional MRI measurement\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGender difference(men vs women)\u003c/p\u003e \u003cp\u003eP-value\u003csup\u003e$\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.77 \u0026plusmn; 5.04\u003c/p\u003e \u003cp\u003e(20\u0026ndash;36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.30 \u0026plusmn; 4.40\u003c/p\u003e \u003cp\u003e(20\u0026ndash;36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.70 \u0026plusmn; 6.29\u003c/p\u003e \u003cp\u003e(20\u0026ndash;35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.982*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index (kg/m2)\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.26 \u0026plusmn; 2.72\u003c/p\u003e \u003cp\u003e(16.85\u0026ndash;28.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.32 \u0026plusmn; 3.09\u003c/p\u003e \u003cp\u003e(16.85\u0026ndash;28.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.13 \u0026plusmn; 1.91\u003c/p\u003e \u003cp\u003e(18.85\u0026ndash;25.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.859\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eWeight Self-Stigma Questionnaire\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-devaluation\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.47 \u0026plusmn; 5.83\u003c/p\u003e \u003cp\u003e(6\u0026ndash;27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.75 \u0026plusmn; 5.32\u003c/p\u003e \u003cp\u003e(6\u0026ndash;27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.90 \u0026plusmn; 5.49\u003c/p\u003e \u003cp\u003e(7\u0026ndash;25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.020\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFear of enacted stigma\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.67 \u0026plusmn; 2.90\u003c/p\u003e \u003cp\u003e(6\u0026ndash;18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.00 \u0026plusmn; 2.53\u003c/p\u003e \u003cp\u003e(6\u0026ndash;16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.00 \u0026plusmn; 3.27\u003c/p\u003e \u003cp\u003e(7\u0026ndash;18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eSelf-Consciousness Scale\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic self-consciousness\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.00 \u0026plusmn; 9.54\u003c/p\u003e \u003cp\u003e(31\u0026ndash;71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56.70 \u0026plusmn; 7.95\u003c/p\u003e \u003cp\u003e(39\u0026ndash;68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.50 \u0026plusmn; 12.50\u003c/p\u003e \u003cp\u003e(31\u0026ndash;71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.561\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate self-consciousness\u003c/p\u003e \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e \u003cp\u003e(Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.03 \u0026plusmn; 7.70\u003c/p\u003e \u003cp\u003e(40\u0026ndash;68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.90 \u0026plusmn; 8.08\u003c/p\u003e \u003cp\u003e(40\u0026ndash;68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.30 \u0026plusmn; 6.93\u003c/p\u003e \u003cp\u003e(41\u0026ndash;62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.393\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Wilcoxon rank-sum test.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e$\u003c/sup\u003e=Tow-sample t-test\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eMRI: magnetic resonance imaging; SD: Standard deviation\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eMeasurements\u003c/h3\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMeasurements for WBI and self-consciousness\u003c/h2\u003e \u003cp\u003eTo assess WBI, the weight self-stigma questionnaire (WSSQ) \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e was used (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The WSSQ comprises two subscales: self-devaluation (negative thoughts about being overweight) and fear of enacted stigma (the perception of being discriminated and identification with a stigmatized group). To assess public- and private self-consciousness, the self-consciousness scale (SCS)\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e was used (Table S2) (Supplementary Information).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBrain imaging\u003c/h3\u003e\n\u003cp\u003eStructural MRI measurement: All structural images were collected using a MAGNETOM Prisma 3.0 Tesla scanner (Siemens Healthineers, Erlangen, Germany). Detailed acquisition protocols can be found in the Supplementary Information.\u003c/p\u003e \u003cp\u003eFunctional MRI measurement: Detailed procedures of the fMRI experiment are provided in the Supplementary Information \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Briefly, participants were instructed to consume a small amount of commercially available palatable juice during the fMRI scan (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, Table S3).\u003c/p\u003e\n\u003ch3\u003eStatistics\u003c/h3\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eOnline survey data\u003c/h2\u003e \u003cp\u003eFirst, in Japanese samples, the gender differences in the WSSQ, SCS, age, and BMI were assessed (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Then, a generalized linear mixed models (GLMM) tested associations between WBI, self-consciousness, and BMI. In the GLMM, BMI was set as a dependent variable, and self-devaluation, fear of enacted stigma, public- and private SCS, and age were set as predictor variables, and gender was set as a random effect (Supplementary Information). The generalized linear model (GLM), without the random effect from the GLMM, was developed in men and women separately. Based on the results of GLMM, a model comparison was performed to investigate the relationships between BMI, self-devaluation, and public SCS (Figure S2) using a cross-validation analysis. A cross-validation analysis was conducted with the cvsem package in R \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e using k\u0026thinsp;=\u0026thinsp;10 folds to evaluate the performance of two mediation models based on the Kullback-Leibler Divergence (KL-D). In Model 1, self-devaluation was set as a predictor of public SCS, public SCS was set as a predictor of BMI, and self-devaluation was set as a predictor of BMI. The mediation effect of public SCS on the path from self-devaluation to BMI was also estimated. In Model 2, BMI was set as a predictor of public SCS, and public SCS as well as BMI were set as predictors of self-devaluation. The mediation effect of public SCS on the path from BMI to self-devaluation was also estimated. In Model 1 and 2, the effect of gender was controlled.\u003c/p\u003e \u003cp\u003eNext, the mediation effect of public SCS on the association between BMI and self-devaluation was examined using the best model suggested by the model comparison. A mediation analysis using the lavaan package in R \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e with 5,000 bootstrapped samples was conducted to assess the mediation effect of self-devaluation on BMI through public SCS, controlling for the effect of gender. For this analysis, all numeric variables were centered.\u003c/p\u003e \u003cp\u003eIn South Korea, Germany, and the United States, the gender differences in the WSSQ, SCS, age, and BMI were assessed (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Then, the same GLMM and GLM used in Japanese samples were fitted for data from each country. Subsequently, multi-group structural equation modeling (SEM) examined whether the mediation effect of public SCS differed in the four countries. Multi-group SEM was conducted using the lavaan package in R \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. For this analysis, numeric variables, except public SCS, were centered across the four countries. The Japanese version of the SCS was rated using a 7-point Likert scale, although the Korean, German, and original SCS were rated using a 5-point Likert scale. Thus, public SCS was centered and divided by the SD to normalize data across the four countries. First, in each country, a simple mediation model controlling for gender was estimated. Then, the constrained model was estimated. This model enforced equality of all regression paths and the residual variances across countries to test for uniformity in mediation effects of public SCS. Bootstrapping with 5,000 samples was used to estimate standard errors. Subsequently, a chi-squared difference test was employed to compare these two (constrained and unconstrained) models. The same multi-group SEM was performed in men and women separately, without controlling for the effect of gender.\u003c/p\u003e \u003cp\u003eAdditionally, the correlation coefficients between BMI and self-devaluation and those between BMI and public SCS were compared between Japan and the other countries. The statistical significance threshold for this comparison was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.016 (0.05/3) using the Bonferroni adjustment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eBrain imaging data\u003c/h2\u003e \u003cp\u003eFor structural images, voxel-based morphometry (VBM) was applied. Conventional preprocessing, including skull-strapping, segmentation, normalization, and smoothing, was performed. Subsequently, a voxel-wise general linear model (GLM) including preprocessed grey matter images as a dependent variable, self-devaluation or public SCS as explanatory variables, and BMI and estimated total intracranial volume as nuisance variables was applied. The predicted effect of these analyses was tested using an ROI approach. For the ROI, a sphere with a radius of 10 mm centered on [x, y, z] = [-1, 27, -2.3] in the sACC was set based on previous studies \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. The unpredicted effects were tested using whole brain analysis (Supplementary Information).\u003c/p\u003e \u003cp\u003eDetailed analysis procedures for functional images were provided in the Supplementary Information. Briefly, conventional preprocessing, including slice-timing correction, field map correction, realigning and unwarping, normalization onto the standard Montreal Neurological Institute space, and smoothing, were performed. At the individual level, the condition-specific effects at each voxel of preprocessed images were estimated using a GLM. Then, a group-level voxel-wise GLM analysis with self-devaluation or public SCS as a covariate-of-interest and gender as a covariate-of-no-interest was performed on individual brain response to palatable liquid consumption estimated at the individual level. The predicted effect of these analyses was tested using the ROI approach. The unpredicted effects were tested using whole brain analysis. Then, the generalized psychophysiological interaction (gPPI) analysis was conducted to test the association between whole brain functional connectivity of the sACC and self-devaluation or public SCS.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eAssociations among WBI, BMI, and self-consciousness\u003c/h2\u003e \u003cp\u003eBMI was positively associated with self-devaluation (β\u0026thinsp;=\u0026thinsp;0.30, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and age (β\u0026thinsp;=\u0026thinsp;0.02, p\u0026thinsp;=\u0026thinsp;0.038), and negatively associated with public SCS (β = -0.04, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table S4). In men, BMI was positively associated with self-devaluation (β\u0026thinsp;=\u0026thinsp;0.35, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and age (β\u0026thinsp;=\u0026thinsp;0.04, p\u0026thinsp;=\u0026thinsp;0.028), and negatively associated with public SCS (β = -0.04, p\u0026thinsp;=\u0026thinsp;0.001) (Table S4). In women, BMI was positively associated with self-devaluation (β\u0026thinsp;=\u0026thinsp;0.28, 95% p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and negatively associated with public SCS (β = -0.04, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table S4).\u003c/p\u003e \u003cp\u003eThe model comparison showed that Model 1 demonstrated a significantly lower average KL-D of 0.07 (Standard Error (SE)\u0026thinsp;=\u0026thinsp;0.03), indicating that it better approximated the true distribution of the data than did Model 2, which had a KL-D of 3.14 (SE\u0026thinsp;=\u0026thinsp;0.25). This suggested that Model 1 was more effective in explaining the data.\u003c/p\u003e \u003cp\u003eA significant indirect effect of self-devaluation on BMI through public SCS, with an estimate of -0.007 (SE\u0026thinsp;=\u0026thinsp;0.002, 95% confidence interval (CI) = [-0.012, -0.004], p\u0026thinsp;=\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) was observed. The overall model fit was adequate, with a comparative fit index (CFI)\u0026thinsp;=\u0026thinsp;1.000, root mean square error of approximation (RMSEA)\u0026thinsp;=\u0026thinsp;0.00, and standardized root mean square residual (SRMR)\u0026thinsp;=\u0026thinsp;0.00, as values above 0.95 for CFI, below 0.08 for SRMR, and below 0.06 for RMSEA are acceptable \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. In men, the indirect effect of self-devaluation was not significant, with an estimate of -0.012 (SE\u0026thinsp;=\u0026thinsp;0.007, 95% CI = [-0.029, -0.003], p\u0026thinsp;=\u0026thinsp;0.062) demonstrating an overall adequate model fit, with a CFI\u0026thinsp;=\u0026thinsp;1.000, RMSEA\u0026thinsp;=\u0026thinsp;0.00, and SRMR\u0026thinsp;=\u0026thinsp;0.00 (Figure S3a). In women, a significant indirect effect of self-devaluation was observed, with an estimate of -0.023 (SE\u0026thinsp;=\u0026thinsp;0.007, 95% CI = [-0.038, -0.012], p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) demonstrating an overall adequate model fit, with a CFI\u0026thinsp;=\u0026thinsp;1.000, RMSEA\u0026thinsp;=\u0026thinsp;0.00, and SRMR\u0026thinsp;=\u0026thinsp;0.00 (Figure S3b).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eCultural differences in associations among WBI, BMI, and self-consciousness\u003c/h2\u003e \u003cp\u003eIn South Korea, BMI was positively associated with self-devaluation (β\u0026thinsp;=\u0026thinsp;0.23, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and age (β\u0026thinsp;=\u0026thinsp;0.05, p\u0026thinsp;=\u0026thinsp;0.023) and negatively associated with public SCS (β = -0.10, p\u0026thinsp;=\u0026thinsp;0.008). In Germany, BMI was positively associated with self-devaluation (β\u0026thinsp;=\u0026thinsp;0.19, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and age (β\u0026thinsp;=\u0026thinsp;0.14, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In the United States, BMI was positively associated with self-devaluation (β\u0026thinsp;=\u0026thinsp;0.24, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), private SCS (β\u0026thinsp;=\u0026thinsp;0.15, p\u0026thinsp;=\u0026thinsp;0.020), and age (β\u0026thinsp;=\u0026thinsp;0.14, p\u0026thinsp;=\u0026thinsp;0.023), and negatively associated with public SCS (β = -0.20, p\u0026thinsp;=\u0026thinsp;0.004) (Table S4). In men and women, GLM revealed varied associations among BMI, WBI, and self-consciousness. Detailed results can be found in Table S4.\u003c/p\u003e \u003cp\u003eThe mediation effects of public SCS significantly differed across countries in total (Δχ\u0026sup2;(12)\u0026thinsp;=\u0026thinsp;980.59, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), in men (Δχ\u0026sup2;(6)\u0026thinsp;=\u0026thinsp;298.92, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Figure S3a) and in women (Δχ\u0026sup2;(6)\u0026thinsp;=\u0026thinsp;568.48, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Figure S3b).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe standardized indirect effects of public self-consciousness on BMI through self-devaluation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% confidence interval\u003c/p\u003e \u003cp\u003e(lower, upper)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ez-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eTotal (men and women)\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJapan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.012, -0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3.396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.034, -0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.050, -0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.042\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.064, -0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.036\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eMen\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJapan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.023, -0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.027, 0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.527\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.598\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.072, 0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.082, 0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.453\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eWomen\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJapan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.028, -0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.991\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.070, -0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.045\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.059, 0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.332\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.078, -0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe correlation coefficient between BMI and self-devaluation, after adjusting for gender, was markedly higher in Japan (r\u0026thinsp;=\u0026thinsp;0.46, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than in South Korea (r\u0026thinsp;=\u0026thinsp;0.28, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), Germany (r\u0026thinsp;=\u0026thinsp;0.20, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and the United States (r\u0026thinsp;=\u0026thinsp;0.21, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The differences in correlation coefficients were statistically significant: z\u0026thinsp;=\u0026thinsp;1.51, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (South Korea vs. Japan); z\u0026thinsp;=\u0026thinsp;8.01, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (Germany vs. Japan); z\u0026thinsp;=\u0026thinsp;7.70, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (the United States vs. Japan). No significant differences in correlations were observed between BMI and public SCS or between Japan and other countries (ps\u0026thinsp;\u0026gt;\u0026thinsp;0.45). In men and women, the correlation coefficients between BMI and self-devaluation were significantly different in Japan than in other countries. In men, the correlation coefficient between BMI and self-devaluation was significantly greater in Japan (r\u0026thinsp;=\u0026thinsp;0.53, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than in South Korea (r\u0026thinsp;=\u0026thinsp;0.36, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), Germany (r\u0026thinsp;=\u0026thinsp;0.12, p\u0026thinsp;=\u0026thinsp;0.049), and the United States (r\u0026thinsp;=\u0026thinsp;0.11, p\u0026thinsp;=\u0026thinsp;0.057). The differences in correlation coefficients were statistically significant: z\u0026thinsp;=\u0026thinsp;2.77, p\u0026thinsp;=\u0026thinsp;0.006 (South Korea vs Japan); z\u0026thinsp;=\u0026thinsp;6.64, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001(Germany vs Japan); z\u0026thinsp;=\u0026thinsp;6.67, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (the United States vs Japan). No significant differences in correlation coefficients were observed between BMI and public SCS between Japan and other countries (ps\u0026thinsp;\u0026gt;\u0026thinsp;0.63). In women, the correlation coefficient between BMI and self-devaluation was significantly greater in Japan (r\u0026thinsp;=\u0026thinsp;0.51, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than in South Korea (r\u0026thinsp;=\u0026thinsp;0.30, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), Germany (r\u0026thinsp;=\u0026thinsp;0.25, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and the United States (r\u0026thinsp;=\u0026thinsp;0.27, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The differences in correlation coefficients were statistically significant: z\u0026thinsp;=\u0026thinsp;3.64, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001(South Korea vs. Japan); z\u0026thinsp;=\u0026thinsp;7.79, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (Germany vs Japan); z\u0026thinsp;=\u0026thinsp;4.46, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001(the United States vs Japan). No significant differences in correlation coefficients were observed between BMI and public SCS between Japan and other countries (ps\u0026thinsp;\u0026gt;\u0026thinsp;0.33).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eAssociations among brain structural properties, WBI, and self-consciousness\u003c/h2\u003e \u003cp\u003eNo significant associations between self-devaluation or public SCS and gray matter volumes were observed in the predicted ROI.\u003c/p\u003e \u003cp\u003eWhole brain analysis showed public SCS was positively associated with gray matter volumes in the lateral occipital cortex ([x, y, z] = [-26, -78, 42], z\u0026thinsp;=\u0026thinsp;4.02, cluster size\u0026thinsp;=\u0026thinsp;155 voxels, p\u003csub\u003efamily\u0026minus;wise error rate (FWE)\u0026minus;corrected\u003c/sub\u003e = 0.036) and precuneus ([x, y, z] = [20, -54, 26], z\u0026thinsp;=\u0026thinsp;4.30, cluster size\u0026thinsp;=\u0026thinsp;16 voxels, p\u003csub\u003eFWE\u0026minus;corrected\u003c/sub\u003e = 0.043) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). No association was found between gray matter volumes and self-devaluation. After adjusting for multiple comparisons due to the testing of gray matter volumes in relation to two variables, significance of associations between gray matter volumes in the lateral occipital cortex or precuneus and public SCS were at a trend level (p\u003csub\u003eFWE\u0026minus;corrected\u003c/sub\u003e = 0.072 and 0.086, respectively).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eAssociations among brain response to palatable liquid consumption, WBI, and self-consciousness\u003c/h2\u003e \u003cp\u003eGreater self-devaluation was positively associated with sACC response ([x, y, z] = [8, 32, -6], z\u0026thinsp;=\u0026thinsp;3.72, p\u003csub\u003eFWE\u0026minus;corrected\u003c/sub\u003e = 0.011, cluster size\u0026thinsp;=\u0026thinsp;15 voxels) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb), although public SCS did not reveal any significant association with sACC. After adjusting for multiple comparisons due to the testing of brain response in relation to two variables, the observed associations between sACC response and self-devaluation remained statistically significant (p\u003csub\u003eFWE\u0026minus;corrected\u003c/sub\u003e = 0.022). Whole brain analysis showed no association between brain response and self-devaluation or public SCS.\u003c/p\u003e \u003cp\u003eThe gPPI analysis showed that, in contrast to the tasteless condition, a significantly greater association was observed between the public SCS and the connectivity between the sACC and the cluster in the post cingulate cortex (PCC)/precuneus region ([x, y, z] = [-4, -38, 32], t\u0026thinsp;=\u0026thinsp;3.69, p\u003csub\u003efalse discovery rata(FDR)\u0026minus;\u003c/sub\u003ecorrected\u0026thinsp;\u0026lt;\u0026thinsp;0.001, cluster size\u0026thinsp;=\u0026thinsp;84 voxels) in the gustatory condition (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). No association was found between connectivity with the sACC and self-devaluation.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe current study examined the associations among WBI, self-consciousness, and BMI in Japan, South Korea, Germany, and the United States. Additionally, the study explored the associations between WBI or self-consciousness, and the brain\u0026rsquo;s structural and functional properties.\u003c/p\u003e \u003cp\u003eAs indicated in a previous study \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, self-devaluation demonstrated a positive association with BMI in Japan and the other countries, among both men and women, except for men in Germany. WBI was significantly associated with dysregulated eating behaviors, such as overeating \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, that were used to cope with WBI\u0026rsquo;s negative psychological effects \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, which could potentially cause weight gain \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e or weight regain \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Contrary to the hypothesis, public self-consciousness was negatively associated with BMI in Japan, South Korea, and the United States. A significant preference for thinness exists in Asian and Western countries \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, and there is a common belief that weight can be controlled through diet and exercise \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e, and that individuals who lack the willpower to control these habits are significantly susceptible to weight gain \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Thus, given that public self-consciousness is the awareness of the self as a social and public object \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, individuals with greater public self-consciousness may be more sensitive to the pressure to remain thin for both aesthetic and social reasons. Furthermore, since public self-consciousness denotes attentiveness to the self as viewed by others \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, it would help individuals recognize themselves objectively. Thus, in the same way that keeping a daily food diary helps to objectively recognize one's own eating habits, change eating behavior, and lead to significant weight loss \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e, public self-consciousness would help to objectively monitor individuals\u0026rsquo; eating habits and maintain healthy diet. Additionally, as the results of GLMM or GLM and model comparison analysis revealed, self-devaluation could cause weight gain, whereas public self-consciousness demonstrated a mediation effect, mitigating the weight gain driven by self-devaluation in the Japanese. Overall, self-devaluation could be a causative agent rather than a consequence of weight gain, whereas public self-consciousness may attenuate the positive impact of self-devaluation on weight gain.\u003c/p\u003e \u003cp\u003eSince the majority of previous studies on WBI have been conducted in the United States with women with excess weight \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, conducting WBI studies in other regions with populations that have a wider range of BMI seemed crucial. Thus, the present study was conducted in four countries among individuals with wide-ranging BMI. The multi-group SEM analysis revealed that the mediation effect of public self-consciousness on the relationship between self-devaluation and BMI significantly varied across Japan, South Korea, Germany, and the United States. Previous studies reveal cultural differences in public self-consciousness \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. For example, power distance\u0026mdash;the distance a person feels or maintains between themselves and a person in a position of power \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e, which is pronounced in Asian countries \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e\u0026mdash;positively affected public self-consciousness, which in turn positively influenced consumers\u0026rsquo; intention to eat healthfully \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Moreover, because our data revealed significant mediating effects of public self-consciousness among women from Asian countries (South Korea and Japan), a gender effect on cultural differences in the mediating effect of public self-consciousness is plausible. Public self-consciousness had a more substantial influence on the internalization of ideal appearance among South Korean females than among German females \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Thus, Asian women may be more affected by public self-consciousness, which can lead to an internalization of a preference for thinness. Consequently, the positive effect of self-devaluation on BMI may be mitigated. In fact, from 1990 to 2022, although the prevalence of underweight people declined in the majority of the 200 countries for both men and women, South Korea and Japan were the sole regions to exhibit an epidemiologically significant increase in prevalence of being underweight among women, notwithstanding their classification as high-income nations \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Additionally, in comparison to the other three studied countries, self-devaluation exhibited a stronger positive correlation with BMI in Japan, despite Japan having the lowest BMI among them. Thus, public self-consciousness likely exerts a more pronounced negative mediating effect on the relationship between self-devaluation and BMI in Japanese women. Consequently, the negative moderating effect of public self-consciousness on BMI may vary across countries and is particularly pronounced among women in Japan although there are cultural and regional variations in factors influencing weight maintenance, such as genetic, biological, and environmental elements.\u003c/p\u003e \u003cp\u003eStructural brain imaging data showed that public self-consciousness was positively associated with gray matter volume in the lateral occipital cortex and precuneus, and these results are consistent with a previous MRI study \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. The precuneus and its surrounding regions, including the PCC, could play significant roles in self-awareness, mental representations related to oneself \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, and speculating or understanding how others perceive one's physical and personality traits (e.g., \"I think my friend thinks I am selfish\") \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Consequently, the precuneus and the lateral occipital cortex may play a role in self-recognition by considering how others judge an individual.\u003c/p\u003e \u003cp\u003eSubsequently, the sACC response was positively related with self-devaluation, and greater sACC\u0026ndash;PCC/precuneus connectivity was positively related to public self-consciousness. The sACC has a wide range of neural connections with various regions including the precuneus \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, and is involved with food-reward processing \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, social prediction errors \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, and observation-driven social learning \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Social approval prediction errors, which were calculated as the difference between the feedback received from others (e.g., how likable the person was) and the participants' expected social feedback, were significantly associated with the sACC \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Such prediction errors in the sACC could be used for observation-driven social learning through direct experience or by observing the action and outcome of another person \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Thus, the sACC could play a role in internalizing negative stereotypes about people with higher weights. The sACC is also involved in food reward processing \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Therefore, during palatable liquid consumption, the sACC might evaluate food reward under the influence of the degree of WBI. Furthermore, greater sACC\u0026ndash;precuneus/PCC connectivity was positively associated with public self-consciousness. Alterations in sACC and precuneus/PCC connection have been linked to eating disorders \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e and depression \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e, which is characterized by a lack of motivation and anhedonia. Thus, this neural connection could play a role in processing food-reward value. Overall, public self-consciousness exhibited a negative mediating effect on the positive impact of self-devaluation on BMI, and greater public self-consciousness was associated with increased gray matter volumes in the precuneus and greater sACC\u0026ndash;precuneus/PCC functional connectivity, suggesting that public self-consciousness may exert a negative mediating effect on the positive effect of self-devaluation on BMI by modulating the sACC\u0026ndash;precuneus/PCC connectivity.\u003c/p\u003e \u003cp\u003eThis study has some limitations. First, although the online survey suggests that self-devaluation is a cause rather than a consequence of weight gain, the causal relationship between weight gain and self-devaluation should be confirmed by longitudinal studies. Second, this study focused on WBI, BMI, and self-consciousness, ignoring factors like socioeconomic status \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, which significantly influence WBI. Future studies should consider other factors to better understand WBI. Third, public self-consciousness was linked to gray matter volume in the precuneus, but this region doesn't overlap with the precuneus/PCC cluster seen in the connectivity analysis. Since the precuneus may exhibit enhanced connectivity with nearby areas as well as intra-hemispheric connectivity \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e, the current findings would indicate that public self-consciousness is controlled across the precuneus and adjacent regions. However, it is important to note that differences in participant or brain imaging techniques between structural and functional brain imaging could potentially account for the observed discrepancies in brain imaging findings. Finally, brain measures were performed on Japanese samples only. Cultural differences found among WBI, BMI, and public self-consciousness make a cross-cultural brain imaging comparison essential for future studies.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe current study has found that public self-consciousness would negatively mediate the positive effect of self-devaluation on BMI, and its mediating effect varied across different cultures. Furthermore, brain measurements have indicated that public self-consciousness attenuates the positive association between BMI and self-devaluation by modulating the sACC\u0026ndash;precuneus/PCC connectivity. Although excessive public self-consciousness would be associated with maladaptive eating \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, proper adjustment of public self-consciousness would be a potential therapeutic target to mitigate the negative health consequences of WBI.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank all those involved for participating in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY.N.: Conceptualization, Data collection, Data analysis, Writing original draft. K.H and N.M: Review \u0026amp; editing. All authors reviewed and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by the Grant-in-Aid for Transformative Research Areas (A) of Japan Society for the Promotion of Science (JP21H05172).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData and codes for analysis are available indefinitely at https://doi.org/10.17605/OSF.IO/UTKVE\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePhelps, N. H. et al. Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults. \u003cem\u003eLancet\u003c/em\u003e \u003cb\u003e403\u003c/b\u003e, 1027\u0026ndash;1050. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0140-6736(23)02750-2\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(23)02750-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNutter, S., Saunders, J. F. \u0026amp; Waugh, R. Current trends and future directions in internalized weight stigma research: a scoping review and synthesis of the literature. \u003cem\u003eJ. Eat. Disord\u003c/em\u003e. \u003cb\u003e12\u003c/b\u003e, 98. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s40337-024-01058-0\u003c/span\u003e\u003cspan address=\"10.1186/s40337-024-01058-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlberga, A. S., Russell-Mayhew, S., von Ranson, K. M. \u0026amp; McLaren, L. Weight bias: a call to action. \u003cem\u003eJ. Eat. Disord\u003c/em\u003e. \u003cb\u003e4\u003c/b\u003e, 34. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s40337-016-0112-4\u003c/span\u003e\u003cspan address=\"10.1186/s40337-016-0112-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePearl, R. L. \u0026amp; Puhl, R. M. Weight bias internalization and health: a systematic review. \u003cem\u003eObes. Rev.\u003c/em\u003e \u003cb\u003e19\u003c/b\u003e, 1141\u0026ndash;1163. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/obr.12701\u003c/span\u003e\u003cspan address=\"10.1111/obr.12701\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHughes, A. M. et al. Demographic, socioeconomic and life-course risk factors for internalized weight stigma in adulthood: evidence from an English birth cohort study. \u003cem\u003eLancet Reg. Health Eur.\u003c/em\u003e \u003cb\u003e40\u003c/b\u003e, 100895. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.lanepe.2024.100895\u003c/span\u003e\u003cspan address=\"10.1016/j.lanepe.2024.100895\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eForouhar, V., Edache, I. Y., Salas, X. R. \u0026amp; Alberga, A. S. Weight bias internalization and beliefs about the causes of obesity among the Canadian public. \u003cem\u003eBMC Public. Health\u003c/em\u003e. \u003cb\u003e23\u003c/b\u003e, 1621. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12889-023-16454-5\u003c/span\u003e\u003cspan address=\"10.1186/s12889-023-16454-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRomano, K. A. et al. Weight Bias Internalization and Psychosocial, Physical, and Behavioral Health: A Meta-Analysis of Cross-Sectional and Prospective Associations. \u003cem\u003eBehav. Ther.\u003c/em\u003e \u003cb\u003e54\u003c/b\u003e, 539\u0026ndash;556. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.beth.2022.12.003\u003c/span\u003e\u003cspan address=\"10.1016/j.beth.2022.12.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNakamura, Y. \u0026amp; Asano, M. Developing and validating a Japanese version of the Weight Self-Stigma Questionnaire. \u003cem\u003eEat. Weight Disord\u003c/em\u003e. \u003cb\u003e28\u003c/b\u003e, 44. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s40519-023-01573-0\u003c/span\u003e\u003cspan address=\"10.1007/s40519-023-01573-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeig, E. H. et al. Weight bias internalization and its association with health behaviour adherence after bariatric surgery. \u003cem\u003eClin. Obes.\u003c/em\u003e \u003cb\u003e10\u003c/b\u003e, e12361. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/cob.12361\u003c/span\u003e\u003cspan address=\"10.1111/cob.12361\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePearl, R. L., Puhl, R. M., Lessard, L. M., Himmelstein, M. S. \u0026amp; Foster, G. D. Prevalence and correlates of weight bias internalization in weight management: A multinational study. \u003cem\u003eSSM Popul. Health\u003c/em\u003e. \u003cb\u003e13\u003c/b\u003e, 100755. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ssmph.2021.100755\u003c/span\u003e\u003cspan address=\"10.1016/j.ssmph.2021.100755\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRomano, K. A., Heron, K. E. \u0026amp; Henson, J. M. Examining associations among weight stigma, weight bias internalization, body dissatisfaction, and eating disorder symptoms: Does weight status matter? \u003cem\u003eBody Image\u003c/em\u003e. \u003cb\u003e37\u003c/b\u003e, 38\u0026ndash;49. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.bodyim.2021.01.006\u003c/span\u003e\u003cspan address=\"10.1016/j.bodyim.2021.01.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMacho, S., Andr\u0026eacute;s, A. \u0026amp; Salda\u0026ntilde;a, C. Weight discrimination, BMI, or weight bias internalization? Testing the best predictor of psychological distress and body dissatisfaction. \u003cem\u003eObes. (Silver Spring)\u003c/em\u003e. \u003cb\u003e31\u003c/b\u003e, 2178\u0026ndash;2188. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/oby.23802\u003c/span\u003e\u003cspan address=\"10.1002/oby.23802\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTheron, W. H., Nel, E. M. \u0026amp; Lubbe, A. J. Relationship between body-image and self-consciousness. \u003cem\u003ePercept. Mot Skills\u003c/em\u003e. \u003cb\u003e73\u003c/b\u003e, 979\u0026ndash;983. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2466/pms.1991.73.3.979\u003c/span\u003e\u003cspan address=\"10.2466/pms.1991.73.3.979\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1991).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePanayiotou, G. \u0026amp; Kokkinos, C. M. Self-consciousness and psychological distress: A study using the Greek SCS. \u003cem\u003ePers. Indiv. Differ.\u003c/em\u003e \u003cb\u003e41\u003c/b\u003e, 83\u0026ndash;93. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.paid.2005.10.025\u003c/span\u003e\u003cspan address=\"10.1016/j.paid.2005.10.025\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2006).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanamoto, M. \u0026amp; Kanamoto, M. Relationship between body-consciousness and self-consciousness in male and female adolescents. \u003cem\u003eHum. Perform. Meas.\u003c/em\u003e \u003cb\u003e2\u003c/b\u003e, 57\u0026ndash;64. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.14859/jjtehpe.2.57\u003c/span\u003e\u003cspan address=\"10.14859/jjtehpe.2.57\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2002).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDaSilveira, A., DeSouza, M. L. \u0026amp; Gomes, W. B. Self-consciousness concept and assessment in self-report measures. \u003cem\u003eFront. Psychol.\u003c/em\u003e \u003cb\u003e6\u003c/b\u003e, 930. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpsyg.2015.00930\u003c/span\u003e\u003cspan address=\"10.3389/fpsyg.2015.00930\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFenigstein, A., Scheier, M. F. \u0026amp; Buss, A. H. Public and private self-consciousness: Assessment and theory. \u003cem\u003eJ. Consult. Clin. Psychol.\u003c/em\u003e \u003cb\u003e43\u003c/b\u003e, 522\u0026ndash;527. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/h0076760\u003c/span\u003e\u003cspan address=\"10.1037/h0076760\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1975).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePinel, E. C. You're Just Saying That Because I'm a Woman: Stigma Consciousness and Attributions to Discrimination. \u003cem\u003eSelf Identity\u003c/em\u003e. \u003cb\u003e3\u003c/b\u003e, 39\u0026ndash;51. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/13576500342000031\u003c/span\u003e\u003cspan address=\"10.1080/13576500342000031\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2004).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun, Q., Wang, N., Li, S. \u0026amp; Zhou, H. Local spatial obesity analysis and estimation using online social network sensors. \u003cem\u003eJ. Biomed. Inf.\u003c/em\u003e \u003cb\u003e83\u003c/b\u003e, 54\u0026ndash;62. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jbi.2018.03.010\u003c/span\u003e\u003cspan address=\"10.1016/j.jbi.2018.03.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJostes, A., Pook, M. \u0026amp; Florin, I. Public and private self-consciousness as specific psychopathological features. \u003cem\u003ePers. Indiv. Differ.\u003c/em\u003e \u003cb\u003e27\u003c/b\u003e, 1285\u0026ndash;1295. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0191-8869(99)00077-X\u003c/span\u003e\u003cspan address=\"10.1016/S0191-8869(99)00077-X\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1999).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePearl, R. L. Internalization of weight bias and stigma: Scientific challenges and opportunities. \u003cem\u003eAm. Psychol.\u003c/em\u003e \u003cb\u003e79\u003c/b\u003e, 1308\u0026ndash;1319. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/amp0001455\u003c/span\u003e\u003cspan address=\"10.1037/amp0001455\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDelvecchio, E., Mabilia, D., Miconi, D., Chirico, I. \u0026amp; Li, J. B. Self-consciousness in Chinese and Italian adolescents: An exploratory cross-cultural study using the ASC. \u003cem\u003eCurr. Psychology: J. Diverse Perspect. Diverse Psychol. Issues\u003c/em\u003e. \u003cb\u003e34\u003c/b\u003e, 140\u0026ndash;153. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s12144-014-9247-0\u003c/span\u003e\u003cspan address=\"10.1007/s12144-014-9247-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHong, K. H. A cross-cultural study on the influence of public self-consciousness and sociocultural pressure over ideal appearance attitude and body shame. \u003cem\u003eJ. Korean Soc. Cloth. Text.\u003c/em\u003e \u003cb\u003e34\u003c/b\u003e, 1731\u0026ndash;1741. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5850/jksct.2010.34.10.1731\u003c/span\u003e\u003cspan address=\"10.5850/jksct.2010.34.10.1731\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun, T., Horn, M. \u0026amp; Merritt, D. Impacts of cultural dimensions on healthy diet through public self-consciousness. \u003cem\u003eJ. Consumer Mark.\u003c/em\u003e \u003cb\u003e26\u003c/b\u003e, 241\u0026ndash;250. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1108/07363760910965846\u003c/span\u003e\u003cspan address=\"10.1108/07363760910965846\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVergani, F. et al. Anatomic Connections of the Subgenual Cingulate Region. \u003cem\u003eNeurosurgery\u003c/em\u003e \u003cb\u003e79\u003c/b\u003e, 465\u0026ndash;472. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1227/neu.0000000000001315\u003c/span\u003e\u003cspan address=\"10.1227/neu.0000000000001315\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDrevets, W. C., Savitz, J. \u0026amp; Trimble, M. The subgenual anterior cingulate cortex in mood disorders. \u003cem\u003eCNS Spectr.\u003c/em\u003e \u003cb\u003e13\u003c/b\u003e, 663\u0026ndash;681. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/s1092852900013754\u003c/span\u003e\u003cspan address=\"10.1017/s1092852900013754\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBore, M. C. et al. Distinct neurofunctional alterations during motivational and hedonic processing of natural and monetary rewards in depression \u0026ndash; a neuroimaging meta-analysis. \u003cem\u003ePsychol. Med.\u003c/em\u003e \u003cb\u003e54\u003c/b\u003e, 639\u0026ndash;651. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/S0033291723003410\u003c/span\u003e\u003cspan address=\"10.1017/S0033291723003410\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWittmann, M. K. et al. Self-Other Mergence in the Frontal Cortex during Cooperation and Competition. \u003cem\u003eNeuron\u003c/em\u003e \u003cb\u003e91\u003c/b\u003e, 482\u0026ndash;493. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neuron.2016.06.022\u003c/span\u003e\u003cspan address=\"10.1016/j.neuron.2016.06.022\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLockwood, P. L. \u0026amp; Wittmann, M. K. Ventral anterior cingulate cortex and social decision-making. \u003cem\u003eNeurosci. Biobehav Rev.\u003c/em\u003e \u003cb\u003e92\u003c/b\u003e, 187\u0026ndash;191. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neubiorev.2018.05.030\u003c/span\u003e\u003cspan address=\"10.1016/j.neubiorev.2018.05.030\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWill, G. J., Rutledge, R. B., Moutoussis, M. \u0026amp; Dolan, R. J. Neural and computational processes underlying dynamic changes in self-esteem. \u003cem\u003eElife\u003c/em\u003e \u003cb\u003e6\u003c/b\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.7554/eLife.28098\u003c/span\u003e\u003cspan address=\"10.7554/eLife.28098\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoiner, J., Piva, M., Turrin, C. \u0026amp; Chang, S. W. C. Social learning through prediction error in the brain. \u003cem\u003eNPJ Sci. Learn.\u003c/em\u003e \u003cb\u003e2\u003c/b\u003e, 8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41539-017-0009-2\u003c/span\u003e\u003cspan address=\"10.1038/s41539-017-0009-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLillis, J., Luoma, J. B., Levin, M. E. \u0026amp; Hayes, S. C. Measuring weight self-stigma: the weight self-stigma questionnaire. \u003cem\u003eObes. (Silver Spring)\u003c/em\u003e. \u003cb\u003e18\u003c/b\u003e, 971\u0026ndash;976. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/oby.2009.353\u003c/span\u003e\u003cspan address=\"10.1038/oby.2009.353\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNakamura, Y. \u0026amp; Ishida, T. The effect of multiband sequences on statistical outcome measures in functional magnetic resonance imaging using a gustatory stimulus. \u003cem\u003eNeuroImage\u003c/em\u003e \u003cb\u003e300\u003c/b\u003e, 120867. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.neuroimage.2024.120867\u003c/span\u003e\u003cspan address=\"10.1016/j.neuroimage.2024.120867\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrowne, M. W. \u0026amp; Cudeck, R. Alternative Ways of Assessing Model Fit. \u003cem\u003eSociol. Methods Res.\u003c/em\u003e \u003cb\u003e21\u003c/b\u003e, 230\u0026ndash;258. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/0049124192021002005\u003c/span\u003e\u003cspan address=\"10.1177/0049124192021002005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1992).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCudeck, R. A. \u0026amp; Browne, M. W. Cross-Validation Of Covariance Structures. \u003cem\u003eMultivar. Behav. Res.\u003c/em\u003e \u003cb\u003e18 2\u003c/b\u003e, 147\u0026ndash;167 (1983).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRosseel, Y. \u0026amp; Lavaan An R package for structural equation modeling and more. Version 0.5\u0026ndash;12 (BETA). \u003cem\u003eJ. Stat. Softw.\u003c/em\u003e \u003cb\u003e48\u003c/b\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://doi.org/10.18637/jss.v048.i02\u003c/span\u003e\u003cspan address=\"10.18637/jss.v048.i02\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu, L. \u0026amp; Bentler, P. M. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. \u003cem\u003eStruct. Equation Modeling: Multidisciplinary J.\u003c/em\u003e \u003cb\u003e6\u003c/b\u003e, 1\u0026ndash;55. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/10705519909540118\u003c/span\u003e\u003cspan address=\"10.1080/10705519909540118\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1999).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSwami, V. Cultural influences on body size ideals: Unpacking the impact of Westernization and modernization. \u003cem\u003eEur. Psychol.\u003c/em\u003e \u003cb\u003e20\u003c/b\u003e, 44\u0026ndash;51. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1027/1016-9040/a000150\u003c/span\u003e\u003cspan address=\"10.1027/1016-9040/a000150\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHollis, J. F. et al. Weight loss during the intensive intervention phase of the weight-loss maintenance trial. \u003cem\u003eAm. J. Prev. Med.\u003c/em\u003e \u003cb\u003e35\u003c/b\u003e, 118\u0026ndash;126. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.amepre.2008.04.013\u003c/span\u003e\u003cspan address=\"10.1016/j.amepre.2008.04.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHofstede, G. \u003cem\u003eCulture's Consequences: International Differences in Work-Related Values\u003c/em\u003e (SAGE, 1984).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWitt, M. A. \u0026amp; Redding, G. Asian business systems: institutional comparison, clusters and implications for varieties of capitalism and business systems theory. \u003cem\u003eSocio-Economic Rev.\u003c/em\u003e \u003cb\u003e11\u003c/b\u003e, 265\u0026ndash;300. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ser/mwt002\u003c/span\u003e\u003cspan address=\"10.1093/ser/mwt002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorita, T., Asada, M. \u0026amp; Naito, E. Gray-Matter Expansion of Social Brain Networks in Individuals High in Public Self-Consciousness. \u003cem\u003eBrain Sci.\u003c/em\u003e \u003cb\u003e11\u003c/b\u003e, 374 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCavanna, A. E. \u0026amp; Trimble, M. R. The precuneus: a review of its functional anatomy and behavioural correlates. \u003cem\u003eBrain\u003c/em\u003e \u003cb\u003e129\u003c/b\u003e, 564\u0026ndash;583. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/brain/awl004\u003c/span\u003e\u003cspan address=\"10.1093/brain/awl004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2006).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcAdams, C. J. \u0026amp; Krawczyk, D. C. Who am I? How do I look? Neural differences in self-identity in anorexia nervosa. \u003cem\u003eSoc. Cogn. Affect. Neurosci.\u003c/em\u003e \u003cb\u003e9\u003c/b\u003e, 12\u0026ndash;21. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/scan/nss093\u003c/span\u003e\u003cspan address=\"10.1093/scan/nss093\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDatta, N., Hughes, A., Modafferi, M. \u0026amp; Klabunde, M. An FMRI meta-analysis of interoception in eating disorders. \u003cem\u003eNeuroImage\u003c/em\u003e \u003cb\u003e305\u003c/b\u003e, 120933. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.neuroimage.2024.120933\u003c/span\u003e\u003cspan address=\"10.1016/j.neuroimage.2024.120933\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu, Z. et al. Hyperconnectivity between the posterior cingulate and middle frontal and temporal gyrus in depression: Based on functional connectivity meta-analyses. \u003cem\u003eBrain Imaging Behav.\u003c/em\u003e \u003cb\u003e16\u003c/b\u003e, 1538\u0026ndash;1551. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11682-022-00628-7\u003c/span\u003e\u003cspan address=\"10.1007/s11682-022-00628-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJitsuishi, T. \u0026amp; Yamaguchi, A. Characteristic cortico-cortical connection profile of human precuneus revealed by probabilistic tractography. \u003cem\u003eScientific Reports\u003c/em\u003e 13, (1936). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-023-29251-2\u003c/span\u003e\u003cspan address=\"10.1038/s41598-023-29251-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"weight bias internalization, self-consciousness, body mass index, subgenual anterior cingulate cortex, precuneus","lastPublishedDoi":"10.21203/rs.3.rs-6390971/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6390971/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWeight bias internalization (WBI), where individuals adopt negative stereotypes about excess weight, is linked to adverse health outcomes. Although prior research indicates associations between WBI, weight status, and psychological factors linked to self-consciousness, these relationships remain unclear. Thus, this study examined these associations and the relationship between brain characteristics and WBI or self-consciousness. An online survey was conducted in Japan (n\u0026thinsp;=\u0026thinsp;1946), South Korea (n\u0026thinsp;=\u0026thinsp;500), Germany (n\u0026thinsp;=\u0026thinsp;598), and the United States (n\u0026thinsp;=\u0026thinsp;580) to assess WBI, self-consciousness, and body mass index (BMI). In Japanese samples, associations between brain structural (n\u0026thinsp;=\u0026thinsp;120) or functional (n\u0026thinsp;=\u0026thinsp;30) characteristics and WBI or self-consciousness were explored. Self-consciousness negatively mediated the influence of WBI on BMI, varying across countries. Gray matter volume in the precuneus correlated positively with self-consciousness, while the subgenual anterior cingulate cortex (sACC) response to food reward correlated positively with WBI. Functional connectivity between the precuneus and sACC was positively associated with self-consciousness. Therefore, self-consciousness may reduce the impact of WBI on BMI by modulating connectivity between the sACC and precuneus, providing further insight into the interactions between WBI and self-consciousness.\u003c/p\u003e","manuscriptTitle":"Self-Consciousness Mitigates Weight Gain related to Internalized Weight Bias: Cross-Cultural Survey and Brain Imaging","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-16 12:06:07","doi":"10.21203/rs.3.rs-6390971/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d0f6e159-1c64-41e0-8b69-6bc082bf0e5b","owner":[],"postedDate":"May 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":48509308,"name":"Biological sciences/Psychology"},{"id":48509309,"name":"Biological sciences/Psychology/Human behaviour"},{"id":48509310,"name":"Biological sciences/Neuroscience"},{"id":48509311,"name":"Biological sciences/Neuroscience/Feeding behaviour"}],"tags":[],"updatedAt":"2025-09-10T09:09:18+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-16 12:06:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6390971","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6390971","identity":"rs-6390971","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}