Next Article in Journal
Determinants of E-Cigarette and Cigarette Use among Youth and Young Adults in Poland—PolNicoYouth Study
Previous Article in Journal
Youth Positive Mental Health Concepts and Definitions: A Systematic Review and Qualitative Synthesis
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Factorial Model of Obese Adolescents: The Role of Body Image Concerns and Selective Depersonalization—A Pilot Study

1
Department of Experimental Medicine, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy
2
Department of Psychology, University of Campania “Luigi Vanvitelli”, 81100 Caserta, Italy
3
Department of Clinical and Experimental Medicine, University of Foggia, 71100 Foggia, Italy
4
Department of Movement Sciences and Wellbeing, University of Naples “Parthenope”, 80133 Naples, Italy
5
Neurological Unit, CTO Hospital, AORN “Ospedali dei Colli”, 80131 Naples, Italy
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Int. J. Environ. Res. Public Health 2022, 19(18), 11501; https://doi.org/10.3390/ijerph191811501
Submission received: 2 July 2022 / Revised: 2 September 2022 / Accepted: 9 September 2022 / Published: 13 September 2022

Abstract

:
Background: The relationship binding body weight to psychological well-being is unclear. The present study aims at identifying the contribution, and specificity, of some dimensions (i.e., eating-related symptoms, body image disorders, eating habits, personality traits, and emotional difficulties) characterizing the psychological profile of obese adolescents (749 participants, 325 females; 58.3% normal-weight, 29.9% overweight, and 11.7% obese; mean age = 16.05, SD = 0.82). Methods: By introducing the scores obtained by standardized self-report tools into a generalized linear model, a factorial reduction design was used to detect the best fitting discriminant functions and the principal components explaining the higher proportion of the variance. Results: We found two discriminant functions correctly classifying 87.1% of normal-weight, 57.2% of overweight, and 68.2% of obese adolescents. Furthermore, two independent factors, explaining 69.68% of the total variance, emerged. Conclusions: The first factor, “Body Image Concerns”, included the drive for thinness, body dissatisfaction, and interpersonal distrust. The second factor, “Selective Depersonalization”, included a trend toward depersonalization and dissatisfaction with the torso. The neurophysiological implications of our findings will be discussed.

1. Introduction

Obesity has approximately tripled in recent decades in both developed and developing countries, and the World Health Organization has formally recognized it as a global epidemic [1]. Weight gain is the most common nutritional disease in young individuals [2,3,4] and obesity at a young age is considered the main predictor of adult obesity [5,6].
It is well known that weight gain and obesity represent multifactorial conditions involving several interactions between genetic, physiologic, psychological, and social alterations [7,8,9,10,11]. However, although a negative association between obesity and physical health is widely acknowledged [12,13], the relationship binding body weight to psychological well-being is unclear. It has been hypothesized that behavioral and psychological factors could play a key role in modulating this relationship [14].
Early generations of studies focused on the link binding adolescent obesity to psychiatric disorders (e.g., affective, anxiety, somatoform disorders); however, the available data on this relationship are unclear [15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31]. Indeed, previous studies exploring whether obesity precedes mental disorders or whether psychological impairments boost weight gain provided inconclusive results [19]. Therefore, the link between weight gain and mental disorders does not appear to be unidirectional, and obesity was not included in the taxonomy of the latest revision of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) [32].
Later generations of studies have instead focused on the role exerted by more targeted psychological domains. In particular, self-esteem, body image perception, emotion regulation, and personality traits have been the most explored domains.
As for self-esteem, it seems to play a modulatory role in the relationship between body weight and depression [33,34]. However, only a low percentage of obese children exhibit low self-esteem coupled with depressive symptoms [35,36]. Furthermore, it has been shown that self-esteem scores in overweight and obese children generally fall within the normal range, even in clinical samples [33,37], and self-perceived body weight appears to be more closely related to reduced self-esteem rather than actual body weight [38].
Cross-sectional data have shown that body dissatisfaction in children and adolescents is a significant predictor of weight and eating disorders [39,40,41,42,43,44]. Body image is a multidimensional construct underlying how individuals perceive, think, and feel about their bodies [45]. It is usually assessed along a continuum ranging from unhealthy body perceptions (inaccurate perceptions and major negative qualities) to healthy body perceptions (accurate perceptions and predominantly positive attributes) [45,46,47]. Several studies reported that adolescent obesity is associated with increased body dissatisfaction [48], in combination with unhealthy body image and weight-related concerns [49,50,51]; it has also been found to strongly predict body dissatisfaction in adulthood [52,53,54,55,56,57,58,59].
Another line of research focused on the emotional triggers anticipating dysfunctional eating behaviors. Three main psychological-driven eating styles are related to the subjective ability to regulate emotions: emotional eating, external eating, and restrained eating [60,61,62]. Emotional eating explains overeating behaviors as a reaction to negative emotions (e.g., anxiety, depression, disappointment, loneliness) [63]. It is a maladaptive coping mechanism providing an instant reward to mitigate emotional dysregulation [64,65]. This construct is supported by physiological evidence indicating a relationship between obesity and the hypothalamic–pituitary axis (HPA) stress response [66,67,68], which would increase the ingestion of “comfort food” [69,70]. However, studies investigating the association between emotional eating and adolescent obesity have provided mixed results, highlighting positive association [71,72,73,74,75], negative association [76,77], and also no association [78,79,80]. The external eating construct [81] suggests that obese people are more sensitive to external food stimuli such as sight, smell, and taste [82,83]. However, it has been shown that external eating may also occur independently of food characteristics [80]. Finally, restrained eating implies greater efforts to limit food intake for controlling body weight [84,85]. However, it has been reported that a failure to plan and regulate food intake may induce, rather than prevent, overeating [86,87,88]. Indeed, restrictive habits may increase overeating risk as a result of excessive caloric deprivation, with cognitive control that may break down in fatigue or stress conditions [89]. Moreover, restrictive diets could be linked to both obesity and eating disorders [89,90], with episodes of binge eating often preceding prolonged periods of fasting [90].
Last but not least, some personality traits have been associated with maladaptive eating behaviors and obesity in both childhood and adolescence [91]. By definition, personality refers to a constellation of relatively stable traits underlying the individual’s tendency to think, act, and feel in a certain way [92]. Personality is related to unhealthy behaviors [93,94] such as high-calorie intake and a sedentary lifestyle [95,96,97] and it may also affect weight gain through psychological mechanisms interacting with the ability to cope with stress [98]. According to Cloninger’s psychobiological model, obese children showed lower persistence, higher novelty seeking [99], and more impulsivity compared with normal-weight subjects [71,100]. However, many of these findings arise from cross-sectional studies involving targeted clinical populations. Conversely, longitudinal studies on personality and weight gain at a young age are not extensive and provide conflicting results. Obese individuals might exhibit overeating behaviors even independently of a personological/emotional configuration [101].
In short, previous research has failed to detect a clear pattern of psychological functioning characterizing adolescent obesity [102]. This could stem from a difficulty in appreciating the extent and variability of psychological distress in the obese population. Accordingly, to date, the main challenge is to identify, among the obese subjects, which of these manifest certain psychological characteristics, and how they exhibit discomfort.
Given the progressive growth of overweight/obesity prevalence in the last decades, the relationship between obesity and behavioral/psychological dimensions—and how this affects weight rise—needs to be further explored. In particular, it may be useful to address the obesity issue in factorial terms instead of exploring selective domains. This might flatten individual variabilities likely associated with the heterogeneity of results available in the literature. Therefore, providing a multifactorial model of the psychological functioning of obese adolescents could, on the one hand, increase the reliability of psychodiagnostic assessment tools and, on the other hand, help to configure tailored weight loss treatments.
In the present pilot study, we propose a multivariate analysis, based on the generalized linear model, aimed at identifying the most affected areas of the psychological and behavioral spectrum as assessed by self-report measures (i.e., eating-related symptoms, body image, eating habits, emotional regulation processes, and personality traits) in a sample of obese adolescents residing in southern Italy. In particular, our purpose was to explore the contribution, and sensitivity, of certain domains in characterizing the psychological functioning of obese adolescents. We hypothesize the existence of a linear combination of psychological factors characterizing adolescent obesity.

2. Materials and Methods

2.1. Participants

The study was carried out on 749 participants (325 girls and 424 boys), aged between 14 and 17 years old (mean age = 16.05, SD = 0.82), recruited—via convenience sampling method—from different public high schools in the Campania region. The initiative was promoted by the Department of Experimental Medicine of the University of Campania “Luigi Vanvitelli” (Italy) and conducted by the Outpatient Clinic of Dietetics, Sports Medicine, and Psychophysical Well-Being during screening days intended for adolescent students. Inclusion criteria were the following: aged between 14 and 18 years old (to satisfy the administration criteria envisaged by the tools used); absence of intellectual or linguistic deficits; absence of neuropsychiatric disorders (e.g., schizophrenia [103], TIA, stroke, head trauma, epilepsy, major depressive disorder, bipolar disorder); absence of executive deficits (Frontal Assessment Battery–15) [104]; absence of cardiocerebrovascular diseases, cancer, type I or II diabetes, non-progressive (e.g., post-traumatic) or reversible (e.g., metabolic type, by substance intoxication, by nutritional deficiencies) cognitive impairment, connective tissue diseases (e.g., systemic lupus erythematosus, Still disease), respiratory or food allergies; no history of alcohol or drugs abuse/addiction. Furthermore, according to DSM-5 [32], no participants enrolled in the study met the diagnostic criteria for feeding and eating disorders (anorexia nervosa, bulimia nervosa, binge eating disorder, avoidant/restrictive food intake disorder, pica, rumination disorder, other specified feeding or eating disorder, unspecified feeding and eating disorders).
The anthropometric measurements (i.e., weight and height) of each participant were detected and three BMI categories were constructed in line with normative data based on the Italian cross-sectional growth charts [105], where a BMI score lower than the 85th percentile was classified as normal weight, a BMI score included in the percentile range 85th–95th was classified as overweight, and a BMI score ≥ 95th percentile was classified as obese.

2.2. Measures

Data were collected by using the following psychometric questionnaires. These are included in the standard assessment protocol employed by the U.O.C. of Dietetics, Sports Medicine, and Psychophysical Well-Being (University of Campania “Luigi Vanvitelli”) in the outpatient clinical practice.
Eating Disorders Inventory 2 (EDI-2) [106,107]. This is a widely used self-report measure of psychological symptoms commonly associated with eating and weight disorders. It consists of 91 items organized into 11 subscales: Drive for Thinness (DT), Bulimia (BU), Body Dissatisfaction (BD), Ineffectiveness (IN), Perfectionism (P), Interpersonal Distrust (ID), Interoceptive Awareness (IA), Maturity Fears (MF), Asceticism (ASC), Impulse Regulation (IR), and Social Insecurity (SI) (Cronbach’s α = 0.78–0.84).
Body Uneasiness Test (BUT-Form A) [108]. It is a multidimensional tool (34 items) for the clinical assessment of body uneasiness: Global Severity Index (GSI), Weight Phobia (WP), Body Image Concerns (BIC), Avoidance (A), Compulsive Self-Monitoring (CSM), and Depersonalization (D) (Cronbach’s α = 0.79–0.90).
Body Satisfaction Scale (BSS) [109,110]. It is a 16-item self-report questionnaire that measures body dissatisfaction, with each item assessing satisfaction with a specific body part. Each body part is rated on a 7-point Likert scale ranging from “very satisfied” to “very dissatisfied”. The BSS total score (BSS-Total) is obtained by summing the Head (BSS-Head), Torso (BSS-Torso), and Limbs (BSS-Limbs) sub-scores (Cronbach’s α = 0.64–0.85).
Dieter’s Inventory of Eating Temptations (DIET) [111,112]. It is an 18-item inventory designed to assess behavioral competence in six types of situations related to weight control: Overeating (OE), Negative Emotions (NE), Exercise (EX), Resisting Temptation (RT), Positive Social (PS), and Food Choice (FC). The scoring provides for a Total Score (TS-DIET) and six sub-scores for each subdomain (Cronbach’s α = 0.56–0.86).
Roman Alexithymia Scale (RAS) [113]. This questionnaire consists of 27 items allowing us to measure some relevant alexithymia components: Somatic Expression of Emotions (SEE), Difficulties to Identify the Emotions (DIE), Difficulties to Communicate the Emotion (DCE), Externally Oriented Thinking (EOT), and Difficulties to be Empathetic (DE); the sum of the five dimensions produces a total score of alexithymia (Total-RAS) (Cronbach’s α = 0.78–0.81).
Adolescent Dissociative Experiences Scale (A-DES) [114,115]. It is a screening measure for dissociative experience (i.e., dissociative amnesia, absorption and imaginative involvement, depersonalization and derealization, and passive influence). For each item, respondents indicate the frequency of the pertinent experience on an 11-point scale ranging from 0 (“never”) to 10 (“always”). The total A-DES score can be obtained by averaging across item scores (Cronbach’s α = 0.91).
Temperament and Character Inventory (TCI) [116,117]. It is a 240-item self-report questionnaire constructed to assess personality traits according to Cloninger’s psychobiological model. This model takes into account personality in seven dimensions: four temperament scales, i.e., Novelty Seeking (NS), Harm Avoidance (HA), Reward Dependence (RD), and Persistence (P), and three character scales, i.e., Self-Directedness (SD), Cooperativeness (C), and Self-Transcendence (ST) (Cronbach’s α = 0.82–0.88).
The psychometric properties of all the above-mentioned tools have been extensively explored in the Italian adolescent population. These tools are considered highly reliable for the clinical evaluation of eating behavior and weight-related disorders in Italy.

2.3. Statistical Analysis

To determine which psychological/behavioral variables discriminated the three BMI groups (normal-weight, overweight, obese), a stepwise discriminant function analysis was performed. According to the classification matrix, the number of correctly classified cases was reported. Then, only for the obese subgroup, the variables loading the emerged discriminant function(s) were entered into a principal component analysis (PCA) with Varimax rotation to detect any independent latent factors. The number of factors to be extracted was determined following the Mineigen criterion (i.e., eigenvalues > 1) or inspecting the scree plot. Data were analyzed using IBM SPSS Statistics for Windows, version 26 (IBM Corp., Armonk, NY, USA)and JASP packages.

3. Results

According to z-scores, no univariate outliers were detected (i.e., |3|). Square root transformation (√Xi) was performed to normalize variables in line with skewness and kurtosis parameters (i.e., if >|1|). According to the assumption criteria of the generalized linear model, each participant belonged to a single group based on her/his BMI [105] (BMI for sex and age growth charts: normal weight, overweight, and obese). Based on Mahalanobis’ distance ( D i 2 ), no multivariate outliers were detected ( D i 2 = 73.402, p > 0.001). Multivariate normality was assumed by Mardia’s coefficient (   i = 1 N ( D i 2 ) 2   N   = 1956.91 < 2024). Multicollinearity was assessed by either tolerance (T) or variance inflation factor (VIF). Total scores of each psychodiagnostic tool were removed since they were excessively correlated with each other. Analysis of missing data showed random missingness (MCAR) that was handled through the recommended multiple imputation method.

3.1. Descriptive Statistics

The whole sample included 437 normal-weight (58.3%, 185 girls), 224 overweight (29.9%, 112 girls), and 88 obese (11.7%, 28 girls) participants. According to two-way chi-squared test (χ2), a significant association was found between sex and BMI categories [χ2(2) = 8.980, p < 0.01, φ = 0.11]. The analysis of the adjusted standardized residuals (zr) was used as post hoc analysis [118]. Results showed that the number of female participants included in the overweight subgroup was significantly larger than expected (zr = 2.4). Furthermore, the number of females was significantly smaller than expected (zr = −2.3) in the obese subgroup. Descriptive statistics of the BMI-ranked group were integrated by one-way analysis of variance (ANOVA, see Table 1). Two-tailed p-values < 0.05 were considered statistically significant. We used Benjamini and Hochberg’s method [119] to control the false discovery rate.

3.2. Stepwise Discriminant Analysis

All the assumption criteria of discriminant analysis were satisfied; in particular, multivariate normality, adequate size of the smallest group (i.e., n > 20), and the ratio of variables/number of subjects (37 independent variables). Additionally, G*Power 3.1.9.4 was used to perform a power analysis for determining the number of participants required. At a nominal alpha level of 0.05, power (1–β) set to 0.80, effect size (f2v) of 0.33, 3 groups and 37 variables, the required total sample size was 81.
The analysis was performed by entering the gender variable as a covariate [F(1, 36) = 179.36, p = 0.002, η2 = 0.37]. The analysis identified two discriminant functions: the first function [χ²(32) = 535.24, p < 0.001 (Ʌ di Wilks 0.482)] showed the following eigenvalues: 0.763, variance explained: 81.2%, canonical correlation: 0.658. The second function [χ²(15) = 119.42, p < 0.001 (Ʌ di Wilks 0.850)] showed the following eigenvalues: 0.177, variance explained: 18.8%, canonical correlation: 0.388. The discriminant structure matrix (Table 2) shows correlations of each variable with the respective discriminant function. The Varimax rotation procedure was performed. The rotated pooled correlations indicated that EDI-2-DT (0.476), EDI-2-BD (0.433), BSS-Torso (0.317), EDI-2-ID (0.245), and BUT-D (0.211) loaded on the first function. The second function was loaded by positive scores on the DIET-RT (0.446) and RAS-DCE (0.205) as well as negative scores on the EDI-2-IN (−0.294) and BUT-CSM (−0.237).

3.3. Classification Results

Table 3 shows the percentage of the subjects correctly vs. incorrectly classified. The extracted discriminant functions correctly classified 87.1% of normal-weight, 57.2% of overweight, and 68.2% of obese subjects. Overall, the functions correctly classified 75.9% of participants. Centroids of each group are displayed in Table 4. Normal-weight subjects were characterized by positive scores at the second function and negative scores at the first function. Overweight subjects were instead characterized by negative scores at the second function. Finally, obese subjects were characterized by positive scores in the first function and negative scores in the second function (see Figure 1).

3.4. Principal Components Analysis

In order to detect independent latent factors, the discriminant functions characterizing obese subjects (EDI-2-DT, EDI-2-BD, EDI-2-ID, BUT-D, and BSS-Torso) were entered into a PCA (n = 88). The rotated component matrix is reported in Table 5. The PCA revealed two factors (Bartlett’s test = 127.78, p < 0.001) explaining 69.68% of the total variance. The first factor, i.e., “Body Image Concerns” (eigenvalue: 2.12, variance explained: 42.48), was loaded by the EDI-2-DT, EDI-2-BD, and EDI-2-ID scores. The second factor, i.e., “Selective Depersonalization” (eigenvalue: 1.36, variance explained: 27.19), was loaded by the BUT-D and BSS-Torso scores.

4. Discussion

The present pilot study aimed to detect a linear combination of psychological/behavioral variables characterizing adolescent obesity. Participants completed a self-report assessment battery exploring psychological dimensions commonly related to eating and weight disorders, namely, eating-related symptoms, body image, eating habits, emotional regulation processes, and personality traits.
To determine which domain characterized each subgroup (normal-weight, overweight, and obese), a discriminant analysis was performed. The extracted functions correctly classified 75.9% of participants. In particular, 68.2% of obese subjects and 87.1% of normal-weight subjects were correctly classified. Based on the discriminant solution, two independent latent factors emerged for the obese subgroup.
The first factor (“Body Image Concerns”) included the drive for thinness, body dissatisfaction, and interpersonal distrust. Conversely, the second factor (“Selective Depersonalization”) included depersonalization and dissatisfaction with the torso.
The “Body Image Concerns” factor was mainly explained by the drive for thinness and body dissatisfaction. By definition, the drive for thinness underlies an extreme wish to lose weight combined with an intense desire to be thinner, as well as the fear of weight gain [106]. Body dissatisfaction, instead, refers to a general discontentment with body shape, with a higher focus on the body parts most susceptible to fat deposits [106]. Finally, this factor was also explained by the interpersonal distrust reflecting a sense of alienation and reluctance to form close relationships or uncomfortableness in expressing emotions towards others [106].
Body image refers to a complex neuropsychological construct involving the individual’s perceptions, sensations, and attitudes about attractiveness and physical appearance [120,121,122,123]. In sociocultural terms, excessive thinness is constantly encouraged by media as an exclusive beauty standard [124,125], which appears to be internalized—together with body image dissatisfaction—long before puberty [126]. The internalization of a thin ideal may affect general self-determination, self-esteem, and filtering of media messages, thus increasing unhealthy eating and weight-control behaviors [127,128,129,130,131].
Furthermore, subjects with eating and weight disorders selectively focus their attention on physical appearance-related stimuli [123,132,133]. Indeed, some studies assessing attentional processing via eye movements in body exposure tasks showed that these subjects paid more attention to their self-perceived unsatisfactory body parts than to the satisfactory ones; conversely, when they looked at other people’s bodies, the opposite pattern was detected [134,135,136]. Still, in pupillometric studies using mydriasis as a physiological index of cognitive load and frontal activity [137,138], dilated pupil size, in combination with decreased blink rate (an additional index of increased attention and concentration) [139], was observed when participants allocated their attention towards their own unattractive body parts. Selective attention to certain physical features interacts with underlying knowledge structures (i.e., the body schema) filtering information, and orienting behavior [140].
Lastly, interpersonal distrust is likely the result of the idealization of the thin culture exacerbating prejudice and discrimination toward obese individuals [19]. Negative attitudes towards obese individuals might be pervasive and prejudice and discrimination may represent chronic stressors affecting the psychological well-being of obese individuals [141,142,143].
One might hypothesize that obese adolescents manifest a rumination polarized on the desire to be thin. Rumination is characterized by prolonged, repetitive, and recurrent thinking about one’s concerns and experiences [144]. According to the Goal Progress Theory [145], rumination is triggered by the perception of a discrepancy between the current state and the ideal target. In line with this claim, body dissatisfaction may trigger ruminative thoughts as a result of a dysfunctional comparison between the actual and the ideal body image.
As reported above, the second factor (“Selective depersonalization”) was explained by depersonalization and body dissatisfaction with the torso. Depersonalization is characterized by feelings of detachment and estrangement from the body. Our results seem to suggest that this phenomenon selectively involved the torso, i.e., the most dissatisfying body part.
Depersonalization is, by definition, a symptom of dissociative disorders characterized by impaired self-awareness. According to the DSM-5 criteria, it represents a persistent feeling of being detached from one’s mental processes and/or body [32], i.e., as if one is watching her/himself from the outside or as if she/he was in a dream. Depersonalization implies that mental activity, body, and the surrounding environment change in their quality, raising a feeling of unreality [146]. More specifically, disembodiment (i.e., a subdomain of depersonalization) refers to the lack of body ownership and loss of agency, namely, the feeling that actions occur automatically, irrespective of the agent’s willingness. This phenomenon ranges from an unspecific sensation of not being in the body to out-of-body experiences [147]. However, in the general population, only a few cases (1–2%) acquire clinical relevance [148]; conversely, fleeting depersonalization experiences are commonly observed, with a lifetime prevalence ranging from 26 to 74% [148,149].
It has been suggested that depersonalization provides psychological protection against acute emotional stress [150] and it is related to anxiety, stressful life events, or life-threatening situations [151]. Depersonalization may represent an inhibitory response ensuring the preservation of adaptive behaviors [147]. According to the “corticolimbic disconnection hypothesis” [147,148], fronto-limbic suppressive mechanisms would mediate an inhibitory response generating a state of emotional numbness. During depersonalization experiences, activation of the prefrontal cortex (PFC) interacts with the anterior cingulate cortex (ACC) and amygdala, generating low emotionality, attentive difficulties, autonomic mitigation, and indifference to pain [152,153,154,155]. In addition, hypoactivity of posterior parietal regions has been associated with deficits in processing and integrating somatosensory information [156,157,158,159,160,161] and low self-awareness. The somatosensory pathways are notoriously involved in both conscious perception/recognition of one’s own body (i.e., body image) [162] and in the body schema construction [163], i.e., a dynamic representation of one’s own body used to drive actions [164,165,166,167,168,169,170]. In addition, either the posterior insula or the angular gyrus also plays a significant role in integrating different input signals related to self-awareness in terms of enteroception, feelings of agency, and visceral sensations [171,172,173,174,175,176,177,178,179,180,181,182,183].
Overweight and obese adolescents are more likely to misperceive their body features, i.e., they tend to underestimate [184,185] or overestimate [178,186,187] their body weight and body parts [48,188,189,190,191], particularly when these are perceived as unattractive [135,192,193]. In the current study, selective dissatisfaction about with torso, in combination with depersonalization, was detected in obese adolescents. This result is in line with previous investigations using body size estimation-based paradigms [188,189,191].
Overall, the results of the present pilot study suggest the coexistence of two apparently opposing trends, which may instead represent two faces of the same medal. On the one hand, obese adolescents reported generalized body image dissatisfaction, accompanied by the desire to lose weight. On the other hand, they also showed a pattern of depersonalization/poor self-awareness strictly related to the most unsatisfactory body part, i.e., the torso. Further studies are needed to explore the relationship between these two clusters. In particular, future research could assess whether “Body Image Concerns” affects “Selective Depersonalization”, or vice versa. Clearly, these two factors may have a different impact on modulating behavior and interindividual differences. This may justify why some obese adolescents are motivated to undertake, and successfully conclude, weight loss programs, while other ones instead alienate from the weight problem. In this vein, integrated treatments including cognitive-behavioral and body exposure techniques [135] appear to be promising in clinical practice.
Our study presents some limitations. First, it does not allow to draw conclusions about gender differences due to the imbalanced ratio of male/female in the overweight and obese subgroups. Future studies are needed to additionally explore gender differences on the matter. However, our findings might be psychometrically transversal since we removed the effect of the sex variable. Second, our discriminant solution correctly classified 75.9% of participants by using only questionnaire data. The remaining percentage may be explained by including more objective measures of body representation (for instance, quantitative estimations of own body size, and heartbeat detection accuracy as a measure of interoceptive awareness (see [48] for additional details)). Third, psychological traits were evaluated by self-reported questionnaires which notoriously tend to overestimate the prevalence of psychopathology [194]. Fourth, results are restricted to students enrolled in screening initiatives and do not provide any information on the larger number of obese individuals not seeking treatment or seeking help in non-clinical settings. Finally, we did not take into account the role exerted by maturation processes or family history of obesity.

5. Conclusions

Our preliminary results showed that obesity negatively affects body perception and subjective body experience in obese adolescents. In particular, obese subjects are characterized by two relatively independent psychological factors exerting a critical influence on body representation. On the one hand, we detected a cognitive body image dissatisfaction mainly associated with an excessive desire for thinness. On the other hand, obese adolescents showed a feeling of estrangement and detachment from the body region perceived as the most unpleasant, such as the torso. In sum, the discomfort observed in both the “explicit” and “implicit” dimensions demonstrates that the representation of one’s own body plays a critical role in adolescent obesity, much more so than other variables explored.

Author Contributions

Conceptualization, M.L.M., A.M. and I.V.; methodology, M.L.M., C.R.I. and I.V.; software and formal analysis, C.R.I. and M.L.M.; investigation, M.L.M., R.P. and G.D.M.; literature review, M.S., A.V., G.C., V.M. and M.L.M.; writing—original draft preparation, M.L.M., C.R.I., G.M., G.C. and I.V.; writing—review and editing, M.L.M., G.M., R.P., A.M. and I.V.; supervision, M.L.M., G.M., A.I., S.C., A.M. and I.V. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

All participants gave prior written informed consent to the study which was approved by the ethics committee of the University of Campania “Luigi Vanvitelli” (Local Ethic Committee Dept. Med.; Approval Code: 20.15.12/Fatt.Cons.Dip.; Approval Date: 15 December 2020) and carried out according to the 1964 Declaration of Helsinki.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. FAO; IFAD; UNICEF; WFP; WHO. The State of Food Security and Nutrition in the World 2018: Building Climate Resilience for Food Security and Nutrition; Food and Agriculture of the United Nations: Rome, Italy, 2018. [Google Scholar]
  2. Ng, M.; Fleming, T.; Robinson, M.; Thomson, B.; Graetz, N.; Margono, C.; Mullany, E.C.; Biryukov, S.; Abbafati, C.; Abera, S.F.; et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: A systematic analysis for the Global Burden of Disease Study 2013. Lancet 2014, 384, 766–781. [Google Scholar] [CrossRef]
  3. Ogden, C.L.; Fryar, C.D.; Carroll, M.D.; Flegal, K.M. Mean body weight, height, and body mass index, United States 1960–2002. Adv. Data 2004, 347, 1–17. [Google Scholar]
  4. Ogden, C.L.; Carroll, M.D.; Curtin, L.R.; McDowell, M.A.; Tabak, C.J.; Flegal, K. Prevalence of Overweight and Obesity in the United States, 1999–2004. JAMA 2006, 295, 1549–1555. [Google Scholar] [CrossRef] [PubMed]
  5. Whitaker, R.C.; Wright, J.A.; Pepe, M.S.; Seidel, K.D.; Dietz, W.H. Predicting obesity in young adulthood from childhood and parental obesity. New Engl. J. Med. 1997, 337, 869–873. [Google Scholar] [CrossRef] [PubMed]
  6. Singh, A.S.; Mulder, C.; Twisk, J.W.R.; Van Mechelen, W.; Chinapaw, M.J.M. Tracking of childhood overweight into adulthood: A systematic review of the literature. Obes. Rev. 2008, 9, 474–488. [Google Scholar] [CrossRef] [PubMed]
  7. Crispino, M.; Trinchese, G.; Penna, E.; Cimmino, F.; Catapano, A.; Villano, I.; Perrone-Capano, C.; Mollica, M.P. Interplay between peripheral and central inflammation in obesity-promoted disorders: The impact on synaptic mitochondrial functions. Int. J. Mol. Sci. 2020, 21, 5964. [Google Scholar] [CrossRef]
  8. La Marra, M.; Caviglia, G.; Perrella, R. Using Smartphones When Eating Increases Caloric Intake in Young People: An Overview of the Literature. Front. Psychol. 2020, 11, 587886. [Google Scholar] [CrossRef]
  9. Monda, V.; la Marra, M.; Perrella, R.; Caviglia, G.; Iavarone, A.; Chieffi, S.; Messina, G.; Carotenuto, M.; Monda, M.; Messina, A. Obesity and brain illness: From cognitive and psychological evidences to obesity paradox. Diabetes Metab. Syndr. Obes. Targets Ther. 2017, 10, 473–479. [Google Scholar] [CrossRef]
  10. Sinha, A.; Kling, S. A Review of Adolescent Obesity: Prevalence, Etiology, and Treatment. Obes. Surg. 2008, 19, 113–120. [Google Scholar] [CrossRef]
  11. Signoriello, E.; Lus, G.; Polito, R.; Casertano, S.; Scudiero, O.; Coletta, M.; Monaco, M.L.; Rossi, F.; Nigro, E.; Daniele, A. Adiponectin profile at baseline is correlated to progression and severity of multiple sclerosis. Eur. J. Neurol. 2018, 26, 348–355. [Google Scholar] [CrossRef]
  12. Monda, M.; Messina, G.; Mangoni, C.; De Luca, B. Resting energy expenditure and fat-free mass do not decline during aging in severely obese women. Clin. Nutr. 2008, 27, 657–659. [Google Scholar] [CrossRef] [PubMed]
  13. De Fusco, C.; Messina, A.; Monda, V.; Viggiano, E.; Moscatelli, F.; Valenzano, A.; Esposito, T.; Sergio, C.; Cibelli, G.; Monda, M.; et al. Osteopontin: Relation between Adipose Tissue and Bone Homeostasis. Stem Cells Int. 2017, 2017, 4045238. [Google Scholar] [CrossRef] [PubMed]
  14. Wadden, T.A.; Brownell, K.D.; Foster, G.D. Obesity: Responding to the global epidemic. J. Consult. Clin. Psychol. 2002, 70, 510–525. [Google Scholar] [CrossRef] [PubMed]
  15. Anderson, S.E.; Cohen, P.; Naumova, E.N.; Jacques, P.F.; Must, A. Adolescent obesity and risk for subsequent major depressive disorder and anxiety disorder: Prospective evidence. Psychosom. Med. 2007, 69, 740–747. [Google Scholar] [CrossRef]
  16. Britz, B.; Siegfried, W.; Ziegler, A.; Lamertz, C.; Herpertz-Dahlmann, B.; Remschmidt, H.; Wittchen, H.-U.; Hebebrand, J. Rates of psychiatric disorders in a clinical study group of adolescents with extreme obesity and in obese adolescents ascertained via a population based study. Int. J. Obes. 2000, 24, 1707–1714. [Google Scholar] [CrossRef]
  17. Daniels, S.R.; Arnett, D.K.; Eckel, R.H.; Gidding, S.S.; Hayman, L.L.; Kumanyika, S.; Williams, C.L. Overweight in children and adolescents: Pathophysiology, consequences, prevention, and treatment. Circulation 2005, 111, 1999–2012. [Google Scholar] [CrossRef]
  18. Eisenberg, M.E.; Neumark-Sztainer, D.; Story, M. Associations of weight-based teasing and emotional well-being among adolescents. Arch. Pediatr. Adolesc. Med. 2003, 157, 733–738. [Google Scholar] [CrossRef]
  19. Fabricatore, A.N.; Wadden, T.A. Psychological aspects of obesity. Clin. Dermatol. 2004, 22, 332–337. [Google Scholar] [CrossRef]
  20. Franko, D.L.; Striegel-Moore, R.H.; Thompson, D.; Schreiber, G.B.; Daniels, S.R. Does adolescent depression predict obesity in black and white young adult women? Psychol. Med. 2005, 35, 1505–1513. [Google Scholar] [CrossRef]
  21. Goodman, E.; Whitaker, R.C. A Prospective study of the role of depression in the development and persistence of adolescent obesity. Pediatrics 2002, 110, 497–504. [Google Scholar] [CrossRef]
  22. Hasler, G.; Pine, D.S.; Kleinbaum, D.G.; Gamma, A.; Luckenbaugh, D.; Ajdacic, V.; Eich, D.; Rössler, W.; Angst, J. Depressive symptoms during childhood and adult obesity: The Zurich Cohort Study. Mol. Psychiatry 2005, 10, 842–850. [Google Scholar] [CrossRef] [PubMed]
  23. Herva, A.; Laitinen, J.; Miettunen, J.; Veijola, J.; Karvonen, J.T.; Läksy, K.; Joukamaa, M. Obesity and depression: Results from the longitudinal Northern Finland 1966 Birth Cohort Study. Int. J. Obes. 2005, 30, 520–527. [Google Scholar] [CrossRef] [PubMed]
  24. Kasen, S.; Cohen, P.; Chen, H.; Must, A. Obesity and psychopathology in women: A three decade prospective study. Int. J. Obes. 2007, 32, 558–566. [Google Scholar] [CrossRef]
  25. Lobstein, T.; Baur, L.; Uauy, R. Obesity in children and young people: A crisis in public health. Obes. Rev. 2004, 5, 4–85. [Google Scholar] [CrossRef] [PubMed]
  26. Marcus, M.D.; Wildes, J.E. Obesity: Is it a mental disorder? Int. J. Eat. Disord. 2009, 42, 739–753. [Google Scholar] [CrossRef]
  27. Merten, M.J.; Wickrama, K.A.S.; Williams, A.L. Adolescent obesity and young adult psychosocial outcomes: Gender and racial differences. J. Youth Adolesc. 2008, 37, 1111–1122. [Google Scholar] [CrossRef]
  28. Richardson, L.P.; Davis, R.; Poulton, R.; McCauley, E.; Moffitt, T.E.; Caspi, A.; Connell, F. A longitudinal evaluation of adolescent depression and adult obesity. Arch. Pediatr. Adolesc. Med. 2003, 157, 739–745. [Google Scholar] [CrossRef]
  29. Roberts, R.E.; Deleger, S.; Strawbridge, W.J.; Kaplan, G.A. Prospective association between obesity and depression: Evidence from the Alameda County Study. Int. J. Obes. 2003, 27, 514–521. [Google Scholar] [CrossRef]
  30. Wang, Y.; Lobstein, T. Worldwide trends in childhood overweight and obesity. Pediatr. Obes. 2006, 1, 11–25. [Google Scholar] [CrossRef]
  31. Wardle, J.; Williamson, S.; Johnson, F.; Edwards, C. Depression in adolescent obesity: Cultural moderators of the association between obesity and depressive symptoms. Int. J. Obes. 2005, 30, 634–643. [Google Scholar] [CrossRef]
  32. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders: DSM-5; American Psychiatric Association: Washington, DC, USA, 2013. [Google Scholar]
  33. French, S.A.; Story, M.; Perry, C.L. Self-esteem and obesity in children and adolescents: A literature review. Obes. Res. 1995, 3, 479–490. [Google Scholar] [CrossRef] [PubMed]
  34. Schwimmer, J.B.; Burwinkle, T.M.; Varni, J.W. Health-related quality of life of severely obese children and adolescents. JAMA 2003, 289, 1813–1819. [Google Scholar] [CrossRef] [PubMed]
  35. Braet, C.; Mervielde, I.; Vandereycken, W. Psychological aspects of childhood obesity: A controlled study in a clinical and nonclinical sample. J. Pediatr. Psychol. 1997, 22, 59–71. [Google Scholar] [CrossRef] [PubMed]
  36. Erermis, S.; Cetin, N.; Tamar, M.; Bukusoglu, N.; Akdeniz, F.; Goksen, D. Is obesity a risk factor for psychopathology among adolescents? Pediatr. Int. 2004, 46, 296–301. [Google Scholar] [CrossRef]
  37. Wardle, J.; Cooke, L. The impact of obesity on psychological well-being. Best Pract. Res. Clin. Endocrinol. Metab. 2005, 19, 421–440. [Google Scholar] [CrossRef]
  38. Hill, A.J. Psychological aspects of obesity. Psychiatry 2005, 4, 26–30. [Google Scholar] [CrossRef]
  39. Ackard, D.M.; Croll, J.K.; Kearney-Cooke, A. Dieting frequency among college females: Association with disordered eating, body image, and related psychological problems. J. Psychosom. Res. 2002, 52, 129–136. [Google Scholar] [CrossRef]
  40. Cooley, E.; Toray, T. Body image and personality predictors of eating disorder symptoms during the college years. Int. J. Eat. Disord. 2001, 30, 28–36. [Google Scholar] [CrossRef]
  41. Neumark-Sztainer, D.; Paxton, S.J.; Hannan, P.J.; Haines, J.; Story, M. Does body satisfaction matter? J. Adolesc. Health 2006, 39, 244–251. [Google Scholar] [CrossRef]
  42. Neumark-Sztainer, D.; Wall, M.M.; Guo, J.; Story, M.; Haines, J.; Eisenberg, M.E. Obesity, disordered eating, and eating disorders in a longitudinal study of adolescents: How do dieters fare 5 years later? J. Am. Diet. Assoc. 2006, 106, 559–568. [Google Scholar] [CrossRef]
  43. Rohde, P.; Stice, E.; Marti, C.N. Development and predictive effects of eating disorder risk factors during adolescence: Implications for prevention efforts. Int. J. Eat. Disord. 2014, 48, 187–198. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. van den Berg, P.; Neumark-Sztainer, D. Fat ‘n happy 5 years later: Is it bad for overweight girls to like their bodies? J. Adolesc. Health 2007, 41, 415–417. [Google Scholar] [CrossRef] [PubMed]
  45. Cash, T.F.; Phillips, K.A.; Santos, M.T.; Hrabosky, J.I. Measuring “negative body image”: Validation of the body image disturbance questionnaire in a nonclinical population. Body Image 2004, 1, 363–372. [Google Scholar] [CrossRef]
  46. Grogan, S. Promoting Positive Body Image in Males and Females: Contemporary Issues and Future Directions. Sex Roles 2010, 63, 757–765. [Google Scholar] [CrossRef]
  47. Chieffi, S.; Iavarone, A.; La Marra, M.; Messina, G.; Villano, I.; Ranucci, S.; Monda, M. Memory for proprioceptive targets in bulimia nervosa. J. Psychiatry. 2015, 18, 297. [Google Scholar]
  48. Mölbert, S.C.; Sauer, H.; Dammann, D.; Zipfel, S.; Teufel, M.; Junne, F.; Enck, P.; Giel, K.E.; Mack, I. Multimodal Body Representation of Obese Children and Adolescents before and after Weight-Loss Treatment in Comparison to Normal-Weight Children. PLoS ONE 2016, 11, e0166826. [Google Scholar] [CrossRef]
  49. Bearman, S.K.; Presnell, K.; Martinez, E.; Stice, E. The Skinny on body dissatisfaction: A longitudinal study of adolescent girls and boys. J. Youth Adolesc. 2006, 35, 217–229. [Google Scholar] [CrossRef]
  50. Caccavale, L.J.; Farhat, T.; Iannotti, R.J. Social engagement in adolescence moderates the association between weight status and body image. Body Image 2012, 9, 221–226. [Google Scholar] [CrossRef]
  51. Calzo, J.P.; Sonneville, K.R.; Haines, J.; Blood, E.A.; Field, A.E.; Austin, S.B. The development of associations among body mass index, body dissatisfaction, and weight and shape concern in adolescent boys and girls. J. Adolesc. Health 2012, 51, 517–523. [Google Scholar] [CrossRef]
  52. Barker, E.T.; Galambos, N.L. Body dissatisfaction of adolescent girls and boys: Risk and resource factors. J. Early Adolesc. 2003, 23, 141–165. [Google Scholar] [CrossRef]
  53. Bucchianeri, M.M.; Arikian, A.J.; Hannan, P.J.; Eisenberg, M.E.; Neumark-Sztainer, D. Body dissatisfaction from adolescence to young adulthood: Findings from a 10-year longitudinal study. Body Image 2012, 10, 1–7. [Google Scholar] [CrossRef] [PubMed]
  54. Field, A.E.; Camargo, C.A.; Taylor, C.B.; Berkey, C.S.; Roberts, S.B.; Colditz, G.A. Peer, parent, and media influences on the development of weight concerns and frequent dieting among preadolescent and adolescent girls and boys. Pediatrics 2001, 107, 54–60. [Google Scholar] [CrossRef]
  55. Jones, D.C. Body Image Among Adolescent Girls and Boys: A Longitudinal Study. Dev. Psychol. 2004, 40, 823–835. [Google Scholar] [CrossRef] [PubMed]
  56. Lawler, M.; Nixon, E. Body dissatisfaction among adolescent boys and girls: The effects of body mass, peer appearance culture and internalization of appearance ideals. J. Youth Adolesc. 2010, 40, 59–71. [Google Scholar] [CrossRef] [PubMed]
  57. Presnell, K.; Bearman, S.K.; Stice, E. Risk factors for body dissatisfaction in adolescent boys and girls: A prospective study. Int. J. Eat. Disord. 2004, 36, 389–401. [Google Scholar] [CrossRef]
  58. Quick, V.; Eisenberg, M.E.; Bucchianeri, M.M.; Neumark-Sztainer, D. Prospective predictors of body dissatisfaction in young adults: 10-year longitudinal findings. Emerg. Adulthood 2013, 4, 271–282. [Google Scholar] [CrossRef]
  59. Tiggemann, M. Body dissatisfaction and adolescent self-esteem: Prospective findings. Body Image 2005, 2, 129–135. [Google Scholar] [CrossRef]
  60. Elfhag, K. Personality correlates of obese eating behaviour: Swedish universities Scales of Personality and the Three Factor Eating Questionnaire. Eat. Weight Disord. Stud. Anorex. Bulim. Obes. 2005, 10, 210–215. [Google Scholar] [CrossRef]
  61. Elfhag, K.; Linné, Y. Gender differences in associations of eating pathology between mothers and their adolescent offspring. Obes. Res. 2005, 13, 1070–1076. [Google Scholar] [CrossRef]
  62. Van Strien, T. Ice-cream consumption, tendency toward overeating, and personality. Int. J. Eat. Disord. 2000, 28, 460–464. [Google Scholar] [CrossRef]
  63. Kaplan, H.I.; Kaplan, H.S. The psychosomatic concept of obesity. J. Nerv. Ment. Dis. 1957, 125, 181–201. [Google Scholar] [CrossRef] [PubMed]
  64. Heatherton, T.F.; Herman, C.P.; Polivy, J. Effects of physical threat and ego threat on eating behaviour. J. Pers. Soc. Psychol. 1991, 60, 138–143. [Google Scholar] [CrossRef]
  65. van Strien, T.; Ouwens, M.A. Effects of distress, alexithymia and impulsivity on eating. Eat. Behav. 2007, 8, 251–257. [Google Scholar] [CrossRef] [PubMed]
  66. Adam, T.C.; Epel, E.S. Stress, eating and the reward system. Physiol. Behav. 2007, 91, 449–458. [Google Scholar] [CrossRef] [PubMed]
  67. Messina, A.; Monda, V. Role of the orexin system on arousal, attention, feeding behaviour and sleep disorders. Acta Med. Mediterr. 2017, 4, 645–649. [Google Scholar] [CrossRef]
  68. Cavaliere, G.; Viggiano, E.; Trinchese, G.; De Filippo, C.; Messina, A.; Monda, V.; Valenzano, A.; Cincione, R.I.; Zammit, C.; Cimmino, F.; et al. Long Feeding High-Fat Diet Induces Hypothalamic Oxidative Stress and Inflammation, and Prolonged Hypothalamic AMPK Activation in Rat Animal Model. Front. Physiol. 2018, 9, 818. [Google Scholar] [CrossRef]
  69. Gibson, E.L. The psychobiology of comfort eating: Implications for neuropharmacological interventions. Behav. Pharmacol. 2012, 23, 442–460. [Google Scholar] [CrossRef]
  70. Messina, A.; Monda, M.; Valenzano, A.; Messina, G.; Villano, I.; Moscatelli, F.; Cibelli, G.; Marsala, G.; Polito, R.; Ruberto, M.; et al. Functional Changes Induced by Orexin A and Adiponectin on the Sympathetic/Parasympathetic Balance. Front. Physiol. 2018, 9, 259. [Google Scholar] [CrossRef]
  71. Braet, C.; Claus, L.; Verbeken, S.; Van Vlierberghe, L. Impulsivity in overweight children. Eur. Child Adolesc. Psychiatry 2007, 16, 473–483. [Google Scholar] [CrossRef]
  72. dos Passos, D.R.; Gigante, D.P.; Maciel, F.V.; Matijasevich, A. Children’s eating behaviour: Comparison between normal and overweight children from a school in Pelotas, Rio Grande do Sul, Brazil. Rev. Paul. Pediatr. 2015, 33, 42–49. [Google Scholar]
  73. Steinsbekk, S.; Barker, E.D.; Llewellyn, C.; Fildes, A.; Wichstrøm, L. Emotional Feeding and Emotional Eating: Reciprocal Processes and the Influence of Negative Affectivity. Child Dev. 2018, 89, 1234–1246. [Google Scholar] [CrossRef] [PubMed]
  74. Viana, V.; Sinde, S.; Saxton, J.C. Children’s Eating Behaviour Questionnaire: Associations with BMI in Portuguese children. Br. J. Nutr. 2008, 100, 445–450. [Google Scholar] [CrossRef] [PubMed]
  75. Webber, L.; Hill, C.; Saxton, J.; Van Jaarsveld, C.H.; Wardle, J. Eating behaviour and weight in children. Int. J. Obes. 2008, 33, 21–28. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  76. Braet, C.; Claus, L.; Goossens, L.; Moens, E.; Van Vlierberghe, L.; Soetens, B. Differences in Eating Style between Overweight and Normal-Weight Youngsters. J. Health Psychol. 2008, 13, 733–743. [Google Scholar] [CrossRef]
  77. Snoek, H.M.; Van Strien, T.; Janssens, J.M.A.M.; Engels, R. Emotional, external, restrained eating and overweight in Dutch adolescents. Scand. J. Psychol. 2007, 48, 23–32. [Google Scholar] [CrossRef] [PubMed]
  78. Caccialanza, R.; Nicholls, D.; Cena, H.; Maccarini, L.; Rezzani, C.; Antonioli, L.; Dieli, S.; Roggi, C. Validation of the Dutch Eating Behaviour Questionnaire parent version (DEBQ-P) in the Italian population: A screening tool to detect differences in eating behaviour among obese, overweight and normal-weight preadolescents. Eur. J. Clin. Nutr. 2004, 58, 1217–1222. [Google Scholar] [CrossRef]
  79. Ebbeling, C.B.; Pawlak, D.B.; Ludwig, D.S. Childhood obesity: Public-health crisis, common sense cure. Lancet 2002, 360, 473–482. [Google Scholar] [CrossRef]
  80. van Strien, T.; Oosterveld, P. The children’s DEBQ for assessment of restrained, emotional, and external eating in 7- to 12-year-old children. Int. J. Eat. Disord. 2008, 41, 72–81. [Google Scholar] [CrossRef]
  81. Obese Humans and Ruts; Schachter, S.; Rodin, J. (Eds.) ErlbaumiWiley: Washington, DC, USA, 1974. [Google Scholar]
  82. Elfhag, K.; Morey, L.C. Personality traits and eating behavior in the obese: Poor self-control in emotional and external eating but personality assets in restrained eating. Eat. Behav. 2008, 9, 285–293. [Google Scholar] [CrossRef]
  83. Messina, A.; Monda, V. An allied health: The pasta. Acta Med. Mediterr. 2017, 4, 641–644. [Google Scholar] [CrossRef]
  84. Stice, E.; Spoor, S.; Bohon, C.; Veldhuizen, M.G.; Small, D.M. Relation of reward from food intake and anticipated food intake to obesity: A functional magnetic resonance imaging study. J. Abnorm. Psychol. 2008, 117, 924–935. [Google Scholar] [CrossRef] [PubMed]
  85. Monda, V.; Polito, R.; Lovino, A.; Finaldi, A.; Valenzano, A.; Nigro, E.; Corso, G.; Sessa, F.; Asmundo, A.; Di Nunno, N.; et al. Short-Term Physiological Effects of a Very Low-Calorie Ketogenic Diet: Effects on Adiponectin Levels and Inflammatory States. Int. J. Mol. Sci. 2020, 21, 3228. [Google Scholar] [CrossRef] [PubMed]
  86. Field, A.E.; Austin, S.B.; Taylor, C.B.; Malspeis, S.; Rosner, B.; Rockett, H.R.; Gillman, M.W.; Colditz, G.A. Relation between dieting and weight change among preadolescents and adolescents. Pediatrics 2003, 112, 900–906. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  87. Johnson, F.; Wardle, J. Dietary restraint, body dissatisfaction, and psychological distress: A prospective analysis. J. Abnorm. Psychol. 2005, 114, 119–125. [Google Scholar] [CrossRef]
  88. Stice, E.; Shaw, H.A. Role of body dissatisfaction in the onset and maintenance of eating pathology: A synthesis of research findings. J. Psychosom. Res. 2002, 53, 985–993. [Google Scholar] [CrossRef]
  89. Claus, L.; Braet, C.; Decaluwé, V. Dieting history in obese youngsters with and without disordered eating. Int. J. Eat. Disord. 2006, 39, 721–728. [Google Scholar] [CrossRef]
  90. Tanofsky-Kraff, M.; Yanovski, S.Z.; Schvey, N.A.; Olsen, C.H.; Gustafson, J.; Yanovski, J.A. A prospective study of loss of control eating for body weight gain in children at high risk for adult obesity. Int. J. Eat. Disord. 2009, 42, 26–30. [Google Scholar] [CrossRef]
  91. Pulkki-Råback, L.; Elovainio, M.; Kivimäki, M.; Raitakari, O.T.; Keltikangas-Järvinen, L. Temperament in childhood predicts body mass in adulthood: The cardiovascular risk in young finns study. Health Psychol. 2005, 24, 307–315. [Google Scholar] [CrossRef]
  92. Hintsanen, M.; Jokela, M.; Cloninger, C.R.; Pulkki-Råback, L.; Hintsa, T.; Elovainio, M.; Josefsson, K.; Rosenström, T.; Mullola, S.; Raitakari, O.T.; et al. Temperament and character predict body-mass index: A population-based prospective cohort study. J. Psychosom. Res. 2012, 73, 391–397. [Google Scholar] [CrossRef]
  93. Yang, X.; Telama, R.; Hirvensalo, M.; Hintsa, T.; Pulkki-Råback, L.; Hintsanen, M.; Keltikangas-Järvinen, L.; Viikari, J.S.A.; Raitakari, O.T. Leadership component of type A behavior predicts physical activity in early midlife. Int. J. Behav. Med. 2010, 19, 48–55. [Google Scholar] [CrossRef]
  94. Bree, M.B.V.D.; Przybeck, T.R.; Cloninger, C.R. Diet and personality: Associations in a population-based sample. Appetite 2006, 46, 177–188. [Google Scholar] [CrossRef] [PubMed]
  95. Swinburn, B.A.; Caterson, I.; Seidell, J.C.; James, W.P.T. Diet, nutrition and the prevention of excess weight gain and obesity. Public Health Nutr. 2004, 7, 123–146. [Google Scholar] [PubMed]
  96. Moscatelli, F.; Messina, G.; Valenzano, A.; Petito, A.; Triggiani, A.I.; Ciliberti, M.A.P.; Monda, V.; Messina, A.; Tafuri, D.; Capranica, L.; et al. Relationship between RPE and Blood Lactate after Fatiguing Handgrip Exercise in Taekwondo and Sed-entary Subjects. Biol. Med. 2015, 1, S3008. [Google Scholar] [CrossRef]
  97. Villano, I.; La Marra, M.; Messina, A.; Di Maio, G.; Moscatelli, F.; Chieffi, S.; Monda, M.; Messina, G.; Monda, V. Effects of vegetarian and vegan nutrition on body composition in competitive futsal athletes. Prog. Nutr. 2021, 23, e2021126. [Google Scholar] [CrossRef]
  98. Krebs, H.; Weyers, P.; Janke, W. Validation of the German version of Cloninger’s TPQ: Replication and correlations with stress coping, mood measures and drug use. Pers. Individ. Differ. 1998, 24, 805–814. [Google Scholar] [CrossRef]
  99. Hwang, J.W.; Lyoo, I.K.; Kim, B.N.; Shin, M.S.; Kim, S.J.; Cho, S.C. The relationship Between temperament and character and psychopathology in community children with overweight. J. Dev. Behav. Pediatr. 2006, 27, 18–24. [Google Scholar] [CrossRef]
  100. Nederkoorn, C.; Braet, C.; Van Eijs, Y.; Tanghe, A.; Jansen, A. Why obese children cannot resist food: The role of impulsivity. Eat. Behav. 2006, 7, 315–322. [Google Scholar] [CrossRef]
  101. Villano, I.; Ilardi, C.R.; Arena, S.; Scuotto, C.; Gleijeses, M.G.; Messina, G.; Messina, A.; Monda, V.; Monda, M.; Iavarone, A.; et al. Obese Subjects without Eating Disorders Experience Binge Episodes Also Independently of Emotional Eating and Personality Traits among University Students of Southern Italy. Brain Sci. 2021, 11, 1145. [Google Scholar] [CrossRef]
  102. Friedman, M.A.; Brownell, K.D. Psychological correlates of obesity: Moving to the next research generation. Psychol. Bull. 1995, 117, 3–20. [Google Scholar] [CrossRef]
  103. Hassan, A.; De Luca, V.; Dai, N.; Asmundo, A.; Di Nunno, N.; Monda, M.; Villano, I. Effectiveness of Antipsychotics in Reducing Suicidal Ideation: Possible Physiologic Mechanisms. Healthcare 2021, 9, 389. [Google Scholar] [CrossRef]
  104. Ilardi, C.R.; Chieffi, S.; Scuotto, C.; Gamboz, N.; Galeone, F.; Sannino, M.; Garofalo, E.; La Marra, M.; Ronga, B.; Iavarone, A. The Frontal Assessment Battery 20 years later: Normative data for a shortened version (FAB15). Neurol. Sci. 2021, 43, 1709–1719. [Google Scholar] [CrossRef]
  105. Cacciari, E.; Milani, S.; Balsamo, A.; Spada, E.; Bona, G.; Cavallo, L.; Cerutti, F.; Gargantini, L.; Greggio, N.; Tonini, G.; et al. Italian cross-sectional growth charts for height, weight and BMI (2 to 20 yr). J. Endocrinol. Investig. 2006, 29, 581–593. [Google Scholar] [CrossRef]
  106. Garner, D.M. Eating Disorder Inventory-2 Professional Manual; Psychological Assessment Resources: Odessa, Ukraine, 1991. [Google Scholar]
  107. Rizzardi, M.; Trombini, E.; Trombini, G. EDI-2: Manuale; Organizzazioni Speciali: Firenze, Italy, 1995. [Google Scholar]
  108. Cuzzolaro, M.; Vetrone, G.; Marano, G.; Garfinkel, P. The Body Uneasiness Test (BUT): Development and validation of a new body image assessment scale. Eat. Weight Disord. Stud. Anorex. Bulim. Obes. 2006, 11, 1–13. [Google Scholar] [CrossRef] [PubMed]
  109. Riva, G.; Molinari, E. Factor Structure of the Italian Version of the Body Satisfaction Scale: A Multisample Analysis. Percept. Mot. Ski. 1998, 86, 1083–1088. [Google Scholar] [CrossRef] [PubMed]
  110. Slade, P.D.; Dewey, M.E.; Newton, T.; Brodie, D.; Kiemle, G. Development and preliminary validation of the body satisfaction scale (BSS). Psychol. Health 1990, 4, 213–220. [Google Scholar] [CrossRef]
  111. Molinari, E.; Compare, A. Psicologia clinica dell’obesità in età pediatrica. In Salute & Equilibrio Nutrizionale; Giovannini, M., Ed.; Springer: Milano, Italy, 2006; pp. 59–90. [Google Scholar]
  112. Schlundt, D.G.; Zimering, R.T. The Dieter’s Inventory of Eating Temptations: A Measure of Weight Control Competence. Addict. Behav. 1988, 13, 151–164. [Google Scholar] [CrossRef]
  113. Baiocco, R.; Giannini, A.M.; Laghi, F.; SAR. Scala Alessitimica Romana. Valutazione delle Capacità di Riconoscere, Esprimere e Verbalizzare le Emozioni. Manuale e Protocolli [RAS. Roman Alexithymic Scale. Evaluation of the Ability to Recognize, Express and Verbalize Emotions. Manual and Protocols]; Erickson: Trento, Italy, 2005. [Google Scholar]
  114. Armstrong, J.G.; Putnam, F.W.; Carlson, E.; Libero, D.Z.; Smith, S.R. Development and Validation of a Measure of Adolescent Dissociation: The Adolescent Dissociative Experiences Scale. J. Nerv. Ment. Dis. 1997, 185, 491–497. [Google Scholar] [CrossRef]
  115. Schimmenti, A. Psychometric Properties of the Adolescent Dissociative Experiences Scale (A-DES) in a Sample of Italian Adolescents. J. Trauma Dissociation 2015, 17, 244–257. [Google Scholar] [CrossRef]
  116. Abbate-Daga, G.; Gramaglia, C.; Malfi, G.; Pierò, A.; Fassino, S. Eating problems and personality traits. An Italian pilot study among 992 high school students. Eur. Eat. Disord. Rev. 2006, 15, 471–478. [Google Scholar] [CrossRef]
  117. Cloninger, C.R.; Przybeck, T.R.; Svrakic, D.M.; Wetzel, R.D. The Temperament and Character Inventory (TCI): A Guide to Its Development and Use; Washington University: St-Louis, MO, USA, 1994. [Google Scholar]
  118. Ilardi, C.R.; Garofalo, E.; Chieffi, S.; Gamboz, N.; La Marra, M.; Iavarone, A. Daily exposure to digital displays may affect the clock-drawing test: From psychometrics to serendipity. Neurol. Sci. 2020, 41, 3683–3690. [Google Scholar] [CrossRef]
  119. Benjamini, Y.; Hochberg, Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. J. R. Stat. Soc. Ser. B 1995, 57, 289–300. [Google Scholar] [CrossRef]
  120. Cooper, P.J.; Whelan, E.; Woolgar, M.; Morrell, J.; Murray, L. Association between childhood feeding problems and maternal eating disorder: Role of the family environment. Br. J. Psychiatry 2004, 184, 210–215. [Google Scholar] [CrossRef] [PubMed]
  121. Cooper, M.J.; Rose, K.S.; Turner, H. The specific content of core beliefs and schema in adolescent girls high and low in eating disorder symptoms. Eat. Behav. 2006, 7, 27–35. [Google Scholar] [CrossRef] [PubMed]
  122. Rushford, N.; Ostermeyer, A. Body image disturbances and their change with videofeedback in anorexia nervosa. Behav. Res. Ther. 1997, 35, 389–398. [Google Scholar] [CrossRef]
  123. Viken, R.J.; Treat, T.A.; Nosofsky, R.M.; McFall, R.M.; Palmeri, T.J. Modeling individual differences in perceptual and attentional processes related to bulimic symptoms. J. Abnorm. Psychol. 2002, 111, 598–609. [Google Scholar] [CrossRef]
  124. Groesz, L.M.; Levine, M.P.; Murnen, S.K. The effect of experimental presentation of thin media images on body satisfaction: A meta-analytic review. Int. J. Eat. Disord. 2001, 31, 10005. [Google Scholar] [CrossRef]
  125. Posavac, S.S.; Posavac, H.D. Predictors of Women’s Concern with Body Weight: The Roles of Perceived Self-Media Ideal Discrepancies and Self-Esteem. Eat. Disord. 2002, 10, 153–160. [Google Scholar] [CrossRef]
  126. Sands, E.R.; Wardle, J. Internalization of ideal body shapes in 9-12-year-old girls. Int. J. Eat. Disord. 2003, 33, 193–204. [Google Scholar] [CrossRef]
  127. Ahern, A.L.; Bennett, K.M.; Kelly, M.; Hetherington, M.M. A qualitative exploration of young women’s attitudes towards the thin ideal. J. Health Psychol. 2010, 16, 70–79. [Google Scholar] [CrossRef]
  128. Bojorquez-Chapela, I.; Unikel, C.; Mendoza, M.-E.; De Lachica, F. Another body project: The thin ideal, motherhood, and body dissatisfaction among Mexican women. J. Health Psychol. 2013, 19, 1120–1131. [Google Scholar] [CrossRef]
  129. Mask, L.; Blanchard, C.M. The protective role of general self-determination against “thin ideal” media exposure on women’s body image and eating–related concerns. J. Health Psychol. 2011, 16, 489–499. [Google Scholar] [CrossRef]
  130. Shroff, H.; Thompson, J.K. Peer influences, body-image dissatisfaction, eating dysfunction and self-esteem in adolescent girls. J. Health Psychol. 2006, 11, 533–551. [Google Scholar] [CrossRef] [PubMed]
  131. Th⊘Gersen-Ntoumani, C.; Ntoumanis, N.; Nikitaras, N. Unhealthy weight control behaviours in adolescent girls: A process model based on self-determination theory. Psychol. Health 2010, 25, 535–550. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  132. Hargreaves, D.; Tiggemann, M. The role of appearance schematicity in the development of adolescent body dissatisfaction. Cogn. Ther. Res. 2002, 26, 691–700. [Google Scholar] [CrossRef]
  133. Williamson, N.A. Body image disturbance in eating disorders: A form of cognitive bias? Eat. Disord. 1996, 4, 47–58. [Google Scholar] [CrossRef]
  134. Freeman, R.; Touyz, S.; Sara, G.; Rennie, C.; Gordon, E.; Beumont, P. In the eye of the beholder: Processing body shape information in anorexic and bulimic patients. Int. J. Eat. Disord. 1991, 10, 709–714. [Google Scholar] [CrossRef]
  135. Jansen, A.; Nederkoorn, C.; Mulkens, A. Selective visual attention for ugly and beautiful body parts in eating disorders. Behav. Res. Ther. 2005, 43, 183–196. [Google Scholar] [CrossRef]
  136. Jansen, A.; Voorwinde, V.; Hoebink, Y.; Rekkers, M.; Martijn, C.; Mulkens, S. Mirror exposure to increase body satisfaction: Should we guide the focus of attention towards positively or negatively evaluated body parts? J. Behav. Ther. Exp. Psychiatry 2016, 50, 90–96. [Google Scholar] [CrossRef]
  137. McGuigan, F.J.; Andreassi, J.L. Psychophysiology—Human Behavior and Physiological Response. Am. J. Psychol. 1981, 94, 359. [Google Scholar] [CrossRef]
  138. Siegle, G.J.; Granholm, E.; E Ingram, R.; Matt, G. Pupillary and reaction time measures of sustained processing of negative information in depression. Biol. Psychiatry 2001, 49, 624–636. [Google Scholar] [CrossRef]
  139. Gregory, R.L. Eye and brain: The Psychology of Seeing; Princeton University Press: Princeton, NJ, USA, 2015; Volume 80. [Google Scholar]
  140. Cruz-Sáez, S.; Pascual, A.; Salaberria, K.; Etxebarria, I.; Echeburúa, E. Risky eating behaviors and beliefs among adolescent girls. J. Health Psychol. 2015, 20, 154–163. [Google Scholar] [CrossRef]
  141. Cramer, P.; Steinwert, T. Thin is good, fat is bad: How early does it begin? J. Appl. Dev. Psychol. 1998, 19, 429–451. [Google Scholar] [CrossRef]
  142. Staffieri, J.R. A study of social stereotype of body image in children. J. Pers. Soc. Psychol. 1967, 7, 101–104. [Google Scholar] [CrossRef] [PubMed]
  143. Vener, A.M.; Krupka, L.R.; Gerard, R.J. Overweight/obese patients: An overview. Practitioner 1982, 226, 1102–1109. [Google Scholar] [PubMed]
  144. Sapuppo, W.; Ruggiero, G.M.; Caselli, G.; Sassaroli, S. The Body of Cognitive and Metacognitive Variables in Eating Disorders: Need of Control, Negative Beliefs about Worry Uncontrollability and Danger, Perfectionism, Self-esteem and Worry. Isr. J. Psychiatry Relat. Sci. 2018, 55, 55–63. [Google Scholar]
  145. Martin, L.L.; Tesser, A. Some ruminative thoughts. Adv. Soc. Cogn. 1996, 9, 1–47. [Google Scholar]
  146. Sierra, M.; David, A.S. Depersonalization: A selective impairment of self-awareness. Conscious. Cogn. 2011, 20, 99–108. [Google Scholar] [CrossRef]
  147. Sierra, M.; Berrios, G. Depersonalization: Neurobiological perspectives. Biol. Psychiatry. 1998, 44, 898–908. [Google Scholar] [CrossRef]
  148. Reutens, S.; Nielsen, O.; Sachdev, P. Depersonalization disorder. Curr. Opin. Psychol. 2010, 23, 278–283. [Google Scholar] [CrossRef]
  149. Sierra, M.; David, A.S.; Hunter, E.C.M. The epidemiology of depersonalisation and derealisation. Soc. Psychiatry 2004, 39, 9–18. [Google Scholar] [CrossRef]
  150. Medford, N.; Sierra, M.; Baker, D.; David, A.S. Understanding and treating depersonalization disorder. Adv. Psychiatr. Treat. 2005, 11, 92–100. [Google Scholar] [CrossRef]
  151. Baker, D.; Hunter, E.; Lawrence, E.; Medford, N.; Patel, M.; Senior, C.; Sierra, M.; Lambert, M.V.; Phillips, M.L.; David, A.S. Depersonalisation disorder: Clinical features of 204 cases. Br. J. Psychiatry. 2003, 182, 428–433. [Google Scholar] [CrossRef] [PubMed]
  152. Lemche, E.; Surguladze, S.; Giampietro, V.; Anilkumar, A.; Brammer, M.; Sierra, M.; Chitnis, X.; Williams, S.; Gasston, D.; Joraschky, P.; et al. Limbic and prefrontal response to facial emotion expressions in depersonalisation. Neuroreport 2007, 18, 473–477. [Google Scholar] [CrossRef] [PubMed]
  153. Medford, N.; Brierley, B.; Brammer, M.; Bullmore, E.T.; David, A.S.; Phillips, M.L. Emotional memory in depersonalization disorder: A functional MRI study. Psychiatry Res. Neuroimaging 2006, 148, 93–102. [Google Scholar] [CrossRef] [PubMed]
  154. La Marra, M.; Ilardi, C.R.; Villano, I.; Carosella, M.; Staiano, M.; Iavarone, A.; Chieffi, S.; Messina, G.; Polito, R.; Scarinci, A.; et al. Functional Relationship between Inhibitory Control, Cognitive Flexibility, Psychomotor Speed and Obesity. Brain Sci. 2022, 12, 1080. [Google Scholar] [CrossRef] [PubMed]
  155. La Marra, M.; Villano, I.; Ilardi, C.R.; Carosella, M.; Staiano, M.; Iavarone, A.; Chieffi, S.; Messina, G.; Polito, R.; Porro, C.; et al. Executive Functions in Overweight and Obese Treatment-Seeking Patients: Cross-Sectional Data and Longitudinal Perspectives. Brain Sci. 2022, 12, 777. [Google Scholar] [CrossRef]
  156. Chieffi, S.; Ilardi, C.R.; Iavarone, A. Parietal lobe dysfunction in schizophrenia: A review. Curr. Psychiatry Rev. 2018, 14, 71–83. [Google Scholar] [CrossRef]
  157. Chieffi, S.; Castaldi, C.; Di Maio, G.; La Marra, M.; Messina, A.; Monda, V.; Villano, I. Attentional bias in the radial and vertical dimensions of space. Comptes Rendus. Biol. 2019, 342, 97–100. [Google Scholar] [CrossRef]
  158. Mantovani, A.; Simeon, D.; Urban, N.; Bulow, P.; Allart, A.; Lisanby, S.H. Temporo-parietal junction stimulation in the treatment of depersonalization disorder. Psychiatry Res. 2011, 186, 138–140. [Google Scholar] [CrossRef]
  159. Simeon, D.; Guralnik, O.; Hazlett, E.A.; Spiegel-Cohen, J.; Hollander, E.; Buchsbaum, M.S. Feeling unreal: A PET study of depersonalization disorder. Am. J. Psychiatry 2000, 157, 1782–1788. [Google Scholar] [CrossRef]
  160. Ilardi, C.R.; Iavarone, A.; La Marra, M.; Iachini, T.; Chieffi, S. Hand movements in mild cognitive impairment: Clinical implications and insights for future research. J. Integr. Neurosci. 2022, 21, 67. [Google Scholar] [CrossRef]
  161. Ilardi, C.R.; Chieffi, S.; Iachini, T.; Iavarone, A. Neuropsychology of posteromedial parietal cortex and conversion factors from Mild Cognitive Impairment to Alzheimer’s disease: Systematic search and state-of-the-art review. Aging 2021, 34, 289–307. [Google Scholar] [CrossRef] [PubMed]
  162. De Vignemont, F. Body schema and body image—Pros and cons. Neuropsychologia 2010, 48, 669–680. [Google Scholar] [CrossRef] [PubMed]
  163. Dijkerman, H.C.; de Haan, E.H. Somatosensory processes subserving perception and action. Behav. Brain Sci. 2007, 30, 189–201. [Google Scholar] [CrossRef]
  164. Černelič-Bizjak, M.; Jenko-Pražnikar, Z. Impact of negative cognitions about body image on inflammatory status in relation to health. Psychol. Health 2013, 29, 264–278. [Google Scholar] [CrossRef] [PubMed]
  165. Chieffi, S.; Messina, A.; Villano, I.; Valenzano, A.A.; Nigro, E.; la Marra, M.; Cibelli, G.; Monda, V.; Salerno, M.; Tafuri, D.; et al. The Use of Velocity Information in Movement Reproduction. Front. Psychol. 2017, 8, 983. [Google Scholar] [CrossRef] [PubMed]
  166. Chieffi, S.; Messina, G.; Messina, A.; Villano, I.; Monda, V.; Ambra, F.I.; Garofalo, E.; Romano, F.; Mollica, M.P.; Monda, M.; et al. Memory for Spatial Locations in a Patient with Near Space Neglect and Optic Ataxia: Involvement of the Occipitotemporal Stream. Front. Neurol. 2017, 8, 231. [Google Scholar] [CrossRef] [PubMed]
  167. Chieffi, S.; Messina, G.; Villano, I.; Messina, A.; Ilardi, C.R.; Monda, M.; Salerno, M.; Sessa, F.; Mollica, M.P.; Cavaliere, G.; et al. Hemispheric Asymmetries in Radial Line Bisection: Role of Retinotopic and Spatiotopic Factors. Front. Psychol. 2018, 9, 2200. [Google Scholar] [CrossRef]
  168. Gallagher, S.; Cole, J. Body image and body schema in a deafferented subject. JMB 1995, 16, 369–389. [Google Scholar]
  169. Sedda, A.; Scarpina, F. Dorsal and ventral streams across sensory modalities. Neurosci. Bull. 2012, 28, 291–300. [Google Scholar] [CrossRef]
  170. Monda, V.; Valenzano, A.; Moscatelli, F.; Salerno, M.; Sessa, F.; Triggiani, A.I.; Viggiano, A.; Capranica, L.; Marsala, G.; De Luca, V.; et al. Primary Motor Cortex Excitability in Karate Athletes: A Transcranial Magnetic Stimulation Study. Front. Physiol. 2017, 8, 695. [Google Scholar] [CrossRef]
  171. Aldosky, H.Y. Impact of obesity and gender differences on electrodermal activities. Gen. Physiol. Biophys. 2019, 38, 513–518. [Google Scholar] [CrossRef] [PubMed]
  172. Chieffi, S.; Villano, I.; Messina, A.; Monda, V.; La Marra, M.; Messina, G.; Monda, M. Involvement of orexin in sleep disorders and neurodegenerative diseases. Curr. Top. Pept. 2015, 16, 49–54. [Google Scholar]
  173. Craig, A.D. Significance of the insula for the evolution of human awareness of feelings from the body. Ann. N. Y. Acad. Sci. 2011, 1225, 72–82. [Google Scholar] [CrossRef]
  174. Critchley, H.D.; Wiens, S.; Rotshtein, P.; Öhman, A.; Dolan, R. Neural systems supporting interoceptive awareness. Nat. Neurosci. 2004, 7, 189–195. [Google Scholar] [CrossRef] [PubMed]
  175. Villano, I.; La Marra, M.; Di Maio, G.; Monda, V.; Chieffi, S.; Guatteo, E.; Messina, G.; Moscatelli, F.; Monda, M.; Messina, A. Physiological Role of Orexinergic System for Health. Int. J. Environ. Res. Public Health 2022, 19, 8353. [Google Scholar] [CrossRef] [PubMed]
  176. Farrer, C.; Franck, N.; Georgieff, N.; Frith, C.; Decety, J.; Jeannerod, M. Modulating the experience of agency: A positron emission tomography study. NeuroImage 2003, 18, 324–333. [Google Scholar] [CrossRef]
  177. Giesbrecht, T.; Merckelbach, H.; Ter Burg, L.; Cima, M.; Simeon, D. Acute dissociation predicts rapid habituation of skin conductance responses to aversive auditory probes. J. Trauma. Stress 2008, 21, 247–250. [Google Scholar] [CrossRef]
  178. Scarpina, F.; Castelnuovo, G.; Molinari, E. Tactile mental body parts representation in obesity. Psychiatry Res. 2014, 220, 960–969. [Google Scholar] [CrossRef]
  179. Sierra, M.; Senior, C.; Phillips, M.L.; David, A.S. Autonomic response in the perception of disgust and happiness in depersonalization disorder. Psychiatry Res. 2006, 145, 225–231. [Google Scholar] [CrossRef]
  180. Simeon, D.; Knutelska, M.; Nelson, D.; Guralnik, O. Feeling unreal: A depersonalization disorder update of 117 cases. J. Clin. Psychiatry 2003, 64, 990–997. [Google Scholar] [CrossRef]
  181. Taylor-Clarke, M.; Jacobsen, P.; Haggard, P. Keeping the world a constant size: Object constancy in human touch. Nat. Neurosci. 2004, 7, 219–220. [Google Scholar] [CrossRef] [PubMed]
  182. Chieffi, S.; Messina, G.; La Marra, M.; Iavarone, A.; Viggiano, A.; De Luca, V.; Monda, M. Distractor interference in visual motor tasks. In Horizon in Neuroscience Research; Nova Science Publishers, Inc.: Hauppauge, NY, USA, 2014. [Google Scholar]
  183. Precenzano, F.; Ruberto, M. Sleep habits in children affected by autism spectrum disorders: A preliminary case-control study. Int. J. Obes. 2017, 3, 405–409. [Google Scholar] [CrossRef]
  184. Maximova, K.; McGrath, J.; Barnett, T.; O’Loughlin, J.; Paradis, G.; Lambert, M. Do you see what I see? Weight status misperception and exposure to obesity among children and adolescents. Int. J. Obes. 2008, 32, 1008–1015. [Google Scholar] [CrossRef]
  185. O’Connor, J.N.; Golley, R.K.; Perry, R.A.; Magarey, A.M.; Truby, H. A longitudinal investigation of overweight children’s body perception and satisfaction during a weight management program. Appetite 2015, 85, 48–51. [Google Scholar] [CrossRef] [PubMed]
  186. Docteur, A.; Urdapilleta, I.; Defrance, C.; Raison, J. Body Perception and Satisfaction in Obese, Severely Obese, and Normal Weight Female Patients. Obesity 2010, 18, 1464–1465. [Google Scholar] [CrossRef]
  187. Gardner, R.M.; Gallegos, V.; Martinez, R.; Espinoza, T. Mirror feedback and judgments of body size. J. Psychosom. Res. 1989, 33, 603–607. [Google Scholar] [CrossRef]
  188. Braet, C.; Tanghe, A.; Decaluwé, V.; Moens, E.; Rosseel, Y. Inpatient Treatment for Children With Obesity: Weight Loss, Psychological Well-being, and Eating Behavior. J. Pediatr. Psychol. 2004, 29, 519–529. [Google Scholar] [CrossRef]
  189. Ratcliff, M.B.; Eshleman, K.E.; Reiter-Purtill, J.; Zeller, M.H. Prospective changes in body image dissatisfaction among adolescent bariatric patients: The importance of body size estimation. Surg. Obes. Relat. Dis. 2011, 8, 470–475. [Google Scholar] [CrossRef]
  190. Shaban, L.H.; Vaccaro, J.A.; Sukhram, S.D.; Huffman, F.G. Perceived body image, eating behavior, and sedentary activities and body mass index categories in Kuwaiti female adolescents. Int. J. Pediatr. 2016, 2016, 1092819. [Google Scholar] [CrossRef]
  191. Watson, P.M.; Dugdill, L.; Pickering, K.; Owen, S.; Hargreaves, J.; Staniford, L.J.; Murphy, R.C.; Knowles, Z.; Cable, N. Service evaluation of the GOALS family-based childhood obesity treatment intervention during the first 3 years of implementation. BMJ Open 2015, 5, e006519. [Google Scholar] [CrossRef]
  192. Griffen, T.C.; Naumann, E.; Hildebrandt, T. Mirror exposure therapy for body image disturbances and eating disorders: A review. Clin. Psychol. Rev. 2018, 65, 163–174. [Google Scholar] [CrossRef] [PubMed]
  193. Kollei, I.; Horndasch, S.; Erim, Y.; Martin, A. Visual selective attention in body dysmorphic disorder, bulimia nervosa and healthy controls. J. Psychosom. Res. 2016, 92, 26–33. [Google Scholar] [CrossRef] [PubMed]
  194. Fairburn, C.G.; Beglin, S.J. Assessment of eating disorders: Interview or self-report questionnaire? Int. J. Eat. Disord. 1994, 16, 363–370. [Google Scholar] [CrossRef]
Figure 1. Graphical representation of each BMI-ranked group based on discriminant dimensions.
Figure 1. Graphical representation of each BMI-ranked group based on discriminant dimensions.
Ijerph 19 11501 g001
Table 1. Mean raw scores (SDs) for each scale.
Table 1. Mean raw scores (SDs) for each scale.
Normal-Weight
(n = 437)
Overweight
(n = 224)
Obese
(n = 88)
p-Value
Eating Disorder Inventory 2 (EDI-2)
Drive for Thinness—DT3.8 (5)8.1 (5.8)11.6 (5.5)<0.001 *
Bulimia—BU2.4 (2.8)2.7 (3.7)3.1 (3)0.156
Body Dissatisfaction—BD6.4 (5.8)12.8 (7.6)16 (6.1)<0.001 *
Ineffectiveness—IN3.1 (3.4)4.7 (4.5)4.2 (3.9)<0.001 *
Perfectionism—P4.7 (3.2)5 (3.7)5.4 (3)0.175
Interpersonal Distrust—ID3.4 (2.8)3.5 (2.8)5 (3.6)0.006 *
Interoceptive Awareness—IA5.1 (5)6 (4.9)6.2 (6.6)0.113
Maturity Fears—MF6.3 (3.7)6.9 (4.8)7 (3.7)0.425
Asceticism—ASC3.3 (2.8)4.1 (3.1)4.6 (3.3)0.001 *
Impulse Regulation—IR4.3 (4.3)5.8 (4.8)5.9 (5.7)<0.001 *
Social Insecurity—SI3.4 (2.4)4 (3.4)4.2 (3.9)0.048
Body Uneasiness Test (BUT-Form A)
Global Severity Index—GSI0.8 (0.7)1.4 (1)1.5 (0.8)<0.001 *
Weight Phobia—WP1.2 (0.8)2 (1.2)2 (0.9)<0.001 *
Body Image Concerns—BIC0.9 (0.8)1.9 (1.3)2.2 (1.1)<0.001 *
Compulsive Self-Monitoring—CSM0.9 (0.8)1.2 (0.9)1.2 (0.8)<0.001 *
Avoidance—A0.4 (0.7)0.7 (0.8)0.8 (0.9)<0.001 *
Depersonalization—D0.5 (0.7)0.8 (0.9)1 (0.9)<0.001 *
Body Satisfaction Scale (BSS)
BSS-Total35.1 (12)38.8 (9.8)40.9 (11.6)<0.001 *
BSS-Head13.8 (5.1)12.9 (4.6)13.6 (6)0.377
BSS-Torso10.9 (4.3)12.7 (3.8)14.7 (4.2)<0.001 *
BSS-Limbs10.4 (4.8)13.2 (4.8)12.6 (4.9)<0.001 *
Dieter’s Inventory of Eating Temptations (DIET)
DIET Total Score4.3 (1)4.1 (0.9)4.1 (0.9)0.042
Overeating—OE3.7 (1.5)3.8 (1.5)3.6 (1.4)0.811
Negative Emotions—NE4.8 (1.4)4.7 (1.3)4.4 (1.5)0.233
Positive Social—PS4.6 (1.6)4.2 (1.3)4.1 (1.2)0.009 *
Food Choice—FC3.1 (1.5)3.0 (1.2)2.9 (1.4)0.810
Resisting Temptation—RT5.1 (1.6)4.3 (1.5)4.6 (1.5)<0.001 *
Exercise—EX3.9 (1.3)3.9 (1.2)4.2 (1.5)0.067
Roman Alexithymia Scale (RAS)
Somatic Expression of Emotions—SEE8.9 (2.5)9.3 (3.0)9.2 (3.4)0.753
Difficulties to identify the emotions—DIE13.2 (3.4)14.4 (3.4)12.8 (3.3)<0.001 *
Difficulties to communicate the emotion—DCE10.6 (2.9)9.3 (2.3)9.7 (2.3)<0.001 *
Externally oriented thinking—EOT10.2 (1.9)10.3 (2.3)10.3 (2.6)0.841
Difficulties to be empathetic—DE11.4 (2.3)11.1 (2.1)12.2 (2.7)<0.001 *
Total score RAS53.4 (7.1)54.3 (8.3)55.1 (10)0.363
Adolescent Dissociative Experiences Scale (A-DES)1.9 (1.4)1.9 (1.3)2.3 (1.8)0.862
Temperament and Character Inventory (TCI)
Novelty Seeking—NS20.9 (4.7)20.8 (5.7)20.2 (4.5)0.410
Harm avoidance—HA46.5 (36.2)52.5 (40.8)45.4 (40.4)0.142
Reward Dependence—RD15.6 (3.3)15.9 (2.9)15.4 (3)0.662
Persistence—P4.5 (1.6)4.4 (1.5)4.7 (1.7)0.281
Self-Directedness—SD26.2 (6)25.5 (7.7)28.3 (7.3)0.001 *
Cooperativeness—C30.2 (5.6)30.3 (5.2)30.1 (5.8)0.846
Self-Transcendence—ST17.3 (5.3)16 (5.6)14.8 (5.6)<0.001 *
Note: ANOVAs were significant (*) according to Benjamini and Hochberg’s adjusting method.
Table 2. Correlations between the discriminating variables and the canonical functions.
Table 2. Correlations between the discriminating variables and the canonical functions.
Functions
12
EDI-2—Drive for Thinness—DT0.476
EDI-2—Body Dissatisfaction—BD0.433
BSS-Torso0.317
EDI-2—Interpersonal Distrust—ID0.245
BUT—Depersonalization—D0.211
DIET—Resisting Temptation—RT 0.446
EDI-2—Ineffectiveness—IN −0.294
BUT—Compulsive Self-Monitoring—CSM −0.237
RAS—Difficulties to communicate the emotion—DCE 0.205
Table 3. Classification results based on discriminant analysis.
Table 3. Classification results based on discriminant analysis.
BMIPredicted Group Membership (%)Total
Normal-WeightOverweightObese
Normal-weight87.110.12.8100.0
Overweight37.457.25.4100.0
Obese18.213.668.2100.0
Table 4. Functions at group centroids.
Table 4. Functions at group centroids.
Functions
12
Normal-weight−0.5050.452
Overweight0.199−0.775
Obese0.992−0.274
Table 5. Principal component matrix.
Table 5. Principal component matrix.
Component
12
EDI-2—Drive for Thinness—DT0.899
EDI-2—Body Dissatisfaction—BD0.824
EDI-2—Interpersonal Distrust—ID0.474
BUT—Depersonalization—D 0.904
BSS-Torso 0.889
Rotation method: Varimax with Kaiser normalization.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

La Marra, M.; Messina, A.; Ilardi, C.R.; Staiano, M.; Di Maio, G.; Messina, G.; Polito, R.; Valenzano, A.; Cibelli, G.; Monda, V.; et al. Factorial Model of Obese Adolescents: The Role of Body Image Concerns and Selective Depersonalization—A Pilot Study. Int. J. Environ. Res. Public Health 2022, 19, 11501. https://doi.org/10.3390/ijerph191811501

AMA Style

La Marra M, Messina A, Ilardi CR, Staiano M, Di Maio G, Messina G, Polito R, Valenzano A, Cibelli G, Monda V, et al. Factorial Model of Obese Adolescents: The Role of Body Image Concerns and Selective Depersonalization—A Pilot Study. International Journal of Environmental Research and Public Health. 2022; 19(18):11501. https://doi.org/10.3390/ijerph191811501

Chicago/Turabian Style

La Marra, Marco, Antonietta Messina, Ciro Rosario Ilardi, Maria Staiano, Girolamo Di Maio, Giovanni Messina, Rita Polito, Anna Valenzano, Giuseppe Cibelli, Vincenzo Monda, and et al. 2022. "Factorial Model of Obese Adolescents: The Role of Body Image Concerns and Selective Depersonalization—A Pilot Study" International Journal of Environmental Research and Public Health 19, no. 18: 11501. https://doi.org/10.3390/ijerph191811501

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop