Validation of the Children Eating Behaviour Questionnaire (CEBQ) in Italian children ​

Validation of the Children Eating Behaviour Questionnaire (CEBQ) in Italian children ​ | 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 Research Article Validation of the Children Eating Behaviour Questionnaire (CEBQ) in Italian children ​ GIUSEPPINA ROSARIA UMANO, Giulia Rondinelli, Margherita Siciliano, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9150177/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Background Childhood eating patterns play a crucial role in shaping long-term health and well-being, underscoring the importance of reliable assessment tools. The Child Eating Behavior Questionnaire (CEBQ) is a widely used parent-report measure that has been validated across numerous languages and populations. This study examines the validity of an Italian version of the CEBQ for use in Italian-speaking populations. Methods Using a cross-sectional design, 184 children (51.6% males) aged 4–12 years were recruited from both clinical and community settings. Parents completed the CEBQ to report their child’s eating behaviors across the “food liking” and four “food avoiding” subscales. In a subgroup of parents, the questionnaire was administered twice (after one month) for test-retest reliability assessment. Factorial analysis was performed to test questionnaire structure consistency with the original CEBQ. Children’s height and weight were recorded to calculate BMI and BMI z-scores. Results The test-retest analysis confirmed the reliability of the questionnaires. The r spearman correlation between the two administrations ranged from 0.54 to 0.77. The ICCs ranged from 0.62 to 0.796. The Principal Component Analysis (PCA) identified eight principal components (matching the original questionnaire structure) with a total explained variance of 66.8%. The Kaiser-Meyer-Olkin value (0.832) indicated adequate sampling, and Bartlett’s test was significant, confirming sufficient correlations for factor analysis. The Exploratory Factor Analysis further supported the extraction of eight factors, consistent with the PCA findings. Conclusions This Italian version of the CEBQ is a valid and reliable instrument for the evaluation of eating behaviours in Italian children and adolescents. CEBQ children and adolescents eating behaviours Figures Figure 1 Plain English Summary This study looked at how well an Italian version of the Child Eating Behavior Questionnaire (CEBQ) works for understanding kids’ eating habits. CEBQ is a tool parents fill out to describe how their children behave around food (such as how much they enjoy eating or how emotions affects desire to eat). Researchers collected data from 184 Italian children aged 4 to 12, coming from both everyday families and clinical settings. Some parents filled out the questionnaire twice a month apart, to check whether the answers stayed consistent over time. The results showed good reliability, meaning parents’ responses were stable. Statistical analyses also confirmed that the Italian questionnaire kept the same structure as the original version. Overall, the findings show that this Italian CEBQ is a solid and trustworthy way to assess eating behaviors in Italian children and teens, making it useful for both research and practical evaluations. Background The increasing prevalence of childhood obesity represents a significant challenge to public health globally [ 1 ]. In this context, assessing children's eating behaviors and lifestyles is fundamental to identifying the risk factors associated with obesity and developing targeted interventions [ 2 ]. Children’s eating behaviour is shaped by a complex interplay of biological, psychological, and environmental factors that often emerge early in life and can significantly contribute to the development of overweight and obesity [ 2 ]. Various theoretical frameworks highlight the central role of temperament, emotional regulation, and sensitivity to internal cues of hunger and satiety as core determinants of eating behaviour in childhood [ 3 ]. In this context, understanding eating patterns is a key objective for both clinical research and early intervention. Numerous studies have shown that specific eating behaviour traits -such as heightened food responsiveness, difficulty recognizing satiety, and a tendency to eat in response to negative emotions- are associated with an increased risk of overweight in children [ 4 , 5 ]. The systematic assessment of these traits requires validated, standardized, and culturally adapted tools capable of capturing behavioural nuances across different sociocultural contexts. Over the years, the Children’s Eating Behaviour Questionnaire (CEBQ) has emerged as one of the most reliable and widely used instruments internationally for evaluating eating behaviours in children [ 6 ]. The questionnaire was designed to provide a reliable and validated instrument for measuring key dimensions of children’s eating behaviour. Based on parent-report, the CEBQ encompasses eight subscales grouped into two overarching dimensions: 'food approach' (propensity toward food) and 'food avoidance' (tendency to avoid food). Its multidimensional structure enables the assessment of various behavioural aspects, including emotional responsiveness to food, enjoyment of eating, self-regulation, and sensitivity to satiety cues. This facilitates a comprehensive analysis of the behavioural phenotype associated with obesity risk and might help in tailoring behavioural therapy [ 2 – 4 ]. Moreover, several studies conducted across diverse cultural contexts -including the Netherlands, Spain, Turkey, China, and Brazil -have confirmed the robustness of its factorial structure and the good reliability of its subscales [ 7 – 10 ]. These studies have also reported significant correlations between CEBQ subscales and anthropometric indicators such as Body Mass Index (BMI) or BMI-z scores, further supporting the construct validity of the instrument [ 7 – 10 ]. However, the validation of a psychometric instrument requires a specific process of linguistic and cultural adaptation, which cannot be assumed even in countries with seemingly similar sociocultural contexts. Factors such as the cultural meaning attributed to food, parental feeding practices, meal structure, and social norms can vary substantially, potentially affecting how questionnaire items are understood and interpreted [ 11 ]. Therefore, despite its widespread use, a validated Italian version of the CEBQ is not currently available, limiting its clinical and research application within the Italian context. This gap in the literature represents a significant limitation for the implementation of prevention and intervention programs based on valid and culturally sensitive tools. In light of these considerations, the present study aims to: 1) translate and culturally adapt the CEBQ for the Italian population, ensuring conceptual equivalence with the original version; 2) explore its factorial structure through both exploratory and confirmatory factor analyses, to determine whether the original eight-factor model is replicable in the Italian sample; 3) assess its internal reliability using Cronbach’s alpha for each subscale; 4) examine construct invariance according to socio-demographic and anthropometric variables, to evaluate the generalizability of the tool across different subgroups of the pediatric population. Therefore, this study aims to provide an Italian version of the CEBQ that is psychometrically robust, theoretically sound, and clinically useful for professionals and researchers working to promote children’s nutritional health and well-being. Methods Participants This study was based on a cross-sectional analysis of data collected from a total of 184 children (mean age 9.24 ± 2.96 years, 51.6% males) in the South of Italy. A school-based cohort (n = 88), consisting of children aged 9 to 10 years attending primary school in the Apulia region; and a clinical cohort (n = 96), consisting of children and adolescents attending the Pediatric Clinic of the University Hospital 'Luigi Vanvitelli' in Naples because of overweight and obesity. Inclusion criteria were age between 4 to 12 years, parents able to speak, read, and understand Italian language and consent to participate. All participating children underwent an anthropometric evaluation. Weight was measured using a beam scale, with the child wearing lightweight clothing. Height was assessed using a Harpenden stadiometer. BMI Body Mass Index (BMI) was calculated using the standard formula: weight (kg) / height² (m²) and subsequently converted into age- and sex-standardized z-scores (z-score BMI), based on the WHO growth reference standards [ 12 , 13 ]. A subgroup of parents in the school cohort (real word group) was used to assess the reliability of the test. In this subgroup, the questionnaire was administered twice, with a one-month interval between administrations. Participants were classified into five z-score BMI categories to reflect a continuum from severe underweight to severe obesity. The study was approved by the Ethic Committee (protocol n. 266/2018) and was conducted according to the Declaration of Helsinki. The Children’s Eating Behaviour Questionnaire The CEBQ is a parent-report instrument consisting of 35 items divided into eight subscales, with parents reporting on their child’s typical eating habits. For this study, the original version by Carnell & Wardle [ 4 ] was translated into Italian by two independent research groups. The translations were then compared and harmonized to adapt the 35 items into a common and easily understandable language for all participants (Supplemental Table 1). All translators approved the final version. The questionnaire comprises eight eating behaviour subscales, each consisting of 3 to 6 items: Food responsiveness (FR, 5 items), Enjoyment of food (EF, 4 items), Emotional overeating (EOE, 4 items), Desire to drink (DD, 3 items), Satiety responsiveness (SR, 5 items), Slowness in eating (SE, 4 items), Emotional undereating (EUE, 4 items), Food fussiness (FF, 6 items). Parents were asked to respond to 35 questions regarding their children's eating behaviour using a 5-point Likert scale, ranging from "never" (1) to "always" (5), as in the original version [ 6 ]. Higher scores on the sum (or average) of each subscale indicate a greater expression of the eating behaviour represented by that subscale (e.g., food responsiveness, desire to drink, etc.). The CEBQ subscales are categorized into “food liking” (EF, FR, EOE, DD) and “food avoiding” (SR, SE, EUE, FF) dimensions, with food liking behaviours showing a positive association, and food avoiding behaviours a negative association, with children’s relative weight. The EF subscale represents a general interest in food, while the FR subscale aims to measure eating in response to external food cues. It has been observed that these behaviours become more pronounced as children grow older [ 14 ]. The DD subscale measures preference for sugary beverages, indicating that this desire is driven by sweet taste rather than thirst. This increased intake of liquid calories may affect long-term weight [ 15 ]. The SR subscale reflects the ability to regulate food intake based on internal satiety signals. The SE subscale measures the speed of eating during a meal and reflects a gradually reduced interest in the meal. The FF subscale reflects a lack of interest in food and reluctance to try new foods (food neophobia), leading to an inadequate variety of foods [ 16 ]. Finally, the EOE and EUE scales are characterized by an increase or decrease in eating in response to emotions [ 17 ]. The original English questionnaire was translated into Italian by two independent bilingual translators. Their translations were reviewed and combined to produce a single Italian version. This version was then back-translated into English by two native English speakers proficient in Italian, and the back-translations were compared with the original questionnaire. A team of translators and researchers subsequently finalized the Italian form of the scale. Statistical analysis Test–retest reliability of the questionnaire was evaluated using three complementary indicators: the intraclass correlation coefficient (ICC), Spearman correlations between pre- and post-scores, and paired-samples t-tests comparing the means. For the classification of reliability, commonly used thresholds in the literature were adopted. For the ICC a two-way random-effects model with absolute agreement was performed. Intraclass correlation coefficient values 0.90 excellent. For Spearman correlations, values between 0.10–0.29 are considered low, 0.30–0.49 moderate, 0.50–0.69 good, and ≥ 0.70 very good. To explore the factorial structure of the CEBQ questionnaire, a Principal Component Analysis (PCA) was initially conducted as a preliminary exploratory procedure. Moreover, since PCA considers total variance (common, specific, and error variance), an Exploratory Factor Analysis (EFA) was subsequently performed to identify the underlying latent factorial structure. The adequacy of the sample for factor analysis was assessed using the Kaiser-Meyer-Olkin (KMO) index and the Bartlett’s test of sphericity. EFA was conducted using the Minimum Residual extraction method with Varimax rotation. To evaluate the goodness of fit of the factorial structure emerging from the Exploratory Factor Analysis (EFA), a Confirmatory Factor Analysis (CFA) was performed. Several fit indices were used to evaluate how well the hypothesized model fits the observed data, including the RMSEA (Root Mean Square Error of Approximation), the SRMR (Standardized Root Mean Square Residual), the CFI (Comparative Fit Index), and the TLI (Tucker-Lewis Index) evaluate the approximation error; values below 0.08 are generally considered acceptable. The CFI (Comparative Fit Index) and TLI (Tucker-Lewis Index) assess model fit by comparing the tested model to a null model, with values ≥ 0.90 indicating acceptable fit and ≥ 0.95 indicating good fit [ 18 ]. The internal reliability of the extracted dimensions was assessed using Cronbach’s α coefficient. Cronbach’s alpha is a measure of internal consistency, indicating how closely related a set of items are as a group. Values below 0.40 suggest low reliability; values between 0.40 and 0.60 indicate questionable reliability; values between 0.60 and 0.80 are considered acceptable; and values between 0.80 and 0.90 indicate good reliability. Spearman’s rank-order correlation was conducted to examine the inter-correlation between subscales and the correlation between the eight subscale scores and continuous variables, namely age, BMI, and z-score BMI. A correlation coefficient > 0.50 is considered a large effect, between 0.3 and 0.5 a medium effect [ 19 ]. The Mann-Whitney U test was conducted to test differences between the two groups (primary school and University Hospital) and sex in CEBQ subscales. The Kruskal-Wallis test was performed to test differences according to weight status (underweight, normal-weight, overweight, and obesity), the Dunn test was applied for post-hoc analysis and multiple comparison. The statistical procedures for exploratory factor analysis (EFA) and CFA were performed with Jamovi (version 2.6.44), while the statistical procedures for the correlation analyses were performed with SPSS (version 20). Results A total of 184 questionnaires were completed by parents. The mean age of the children in the sample was 9.24 ± 2.96 years, 51.6% were males, mean BMI was 20.94 ± 5.3, and mean z-score BMI was 1.40 ± 1.43. Table 1 describes the anthropometric and CEBQ subscales scores of the sample. Table 1 Characteristics of the cohort Characteristic Participants N = 184 Group (primary school/University Hospital, n) 88/96 Age (years) 9.24 ± 2.96 Sex (M/F, %) 51.6/48.4 BMI 20.94 ± 5.31 Z-score BMI 1.40 ± 1.43 Food Responsiveness (FR) 11.55 ± 5.11 Food Fussiness (FF) 18.33 ± 5.63 Slowness in Eating (SE) 10.74 ± 4.29 Emotional Under-Eating (EUE) 9.59 ± 3.73 Desire to Drink (DD) 8.02 ± 3.08 Satiety Responsiveness (SR) 13.72 ± 4.30 Enjoyment of Food (EF) 14.09 ± 3.61 Emotional Over-Eating (EOE) 8.04 ± 3.23 Data are expressed as mean ± standard deviations and as percentages for continuous variables Test–retest reliability The subscales demonstrated stability between test and re-test ranging from moderate to good. Specifically, the FR subscale showed ICC(2,1) = 0.624 (95% C.I.: 0.462–0.746, p < 0.001), EOE ICC(2,1) = 0.632 (95% C.I.: 0.472–0.751, p < 0.001), EF ICC(2,1) = 0.697 (95% C.I.: 0.559–0.797, p < 0.001), DD ICC(2,1) = 0.721 (95% C.I.: 0.591–0.815, p < 0.001), SR ICC(2,1) = 0.741 (95% C.I.: 0.618–0.828, p < 0.001), SE ICC(2,1) = 0.796, (95% C.I.: 0.692–0.867, p < 0.001) EUE ICC(2,1) = 0.620 (95% C.I.: 0.459–0.743, p < 0.001), and FF ICC(2,1) = 0.711 (95% C.I.: 0.576–0.808, p < 0.001). Overall, these values indicate satisfactory temporal stability for all subscales. Spearman correlations between the two administrations confirmed the pattern observed with the ICCs, with values ranging from 0.54 to 0.77 (all p < 0.001). Specifically: FR r = 0.541; EOE r = 0.618; EF r = 0.727; DD r = 0.679; SR r = 0.690; SE r = 0.771; EUE r = 0.625; FF r = 0.728. These results indicate high consistency between pre- and post-scores, ranging from good to very good. Paired-samples t-tests revealed no significant differences between T1 and T2 for any subscale (all p > 0.05), indicating that scores did not change systematically between the two administrations. Exploratory and Confirmatory Factor Analysis The PCA analysis suggested the presence of eight main components (as expected from the original structure of the questionnaire from which it was translated), based on the Kaiser criterion (eigenvalue > 1) and the inspection of the scree plot, with a total explained variance of 66.8%. The Kaiser-Meyer-Olkin index showed a value of 0.832, indicating a sufficient correlation among variables. Additionally, Bartlett’s test of sphericity was significant (χ² =2947, p < 0.001), confirming the presence of relationships between variables and supporting the suitability of factor analysis. EFA confirmed the extraction of eight factors, consistent with the PCA results. The extracted factors explained 57.5% of the total variance, a lower value compared to PCA, as EFA extracts only common variance while excluding specific and error variance. The analysis of the factor loading matrix showed that the items clustered coherently with the theoretical dimensions of the questionnaire, with factor loadings above 0.40 for each item on its respective factor. The CFA analysis revealed an adequate model fit, with RMSEA = 0.0668 and SRMR = 0.0754. However, the CFI (0.851) and TLI (0.833) values are below the optimal threshold of 0.90, indicating some discrepancy between the theoretical model and the observed data (Table 2 ). Table 2 Model fit indices from Confirmatory Factorial Analysis Index Value χ² (degree of freedom) 969 (532) χ² p value <.0001 CFI 0.851 TLI 0.833 SRMR 0.0754 RMSEA 0.0668 Legend: CFI: Comparative Fit Index; RMSEA: Root Mean Square Error of Approximation; SRMR: Standardized Root Mean Square Residual; TLI: Tucker-Lewis Index Reliability Table 3 displays the results of the reliability test. Cronbach’s α coefficient ranged between 0.70–0.85 for all subscales. These values indicate good internal consistency of the scales, with coefficients exceeding the acceptability threshold of 0.70, except for the EOE factor (0.70), which still approaches an acceptable level of reliability. Table 3 Internal reliability of the sample CEBQ Factor Mean (DS) Cronbach’s α coefficient Food Responsiveness 11.55 (5.11) 0.849 Food Fussiness 18.33 (5.63) 0.833 Slowness in Eating 10.74 (4.23) 0.831 Emotional Under-Eating 9.59 (3.73) 0.725 Desire to Drink 8.02 (3.08) 0.772 Satiety Responsiveness 13.72 (4.30) 0.767 Enjoyment of Food 14.09 (3.61) 0.823 Emotional Over-Eating 8.04 (3.23) 0.697 Spearman correlation analyses showed that the “food avoiding” subscales (FF, SE, SR, and EUE) and the “food approach” subscales were positively inter-correlated (Table 4). Moreover, we observed an inverse correlation between the “food liking” and the “food avoiding” subscales, except for EOE and EUE that were positively correlated (r = 0.42, p < 0.0001). The EOE-FR, EF-SR, EF-FR, and SR-SE showed a large inter-correlation, whereas the EOE-EUE, SE-EF, FF-EF, FF-FR, and FR-SE a moderate correlation. The DD subscale showed no significant correlation with any of the other subscales. Age, gender, and weight differences We observed a direct correlation between children’s age and EOE subscale (r = 0.19, p = 0.008), no other significant were observed between age and the other subscales (all p > 0.05). Moreover, no differences were observed between males and females. Conversely, z-score BMI was positively correlated with FR (r = 0.41, p < 0.0001), EOE (r = 0.28, p = 0.0002), and EF (r = 0.44, p < 0.0001). An inverse correlation between z-score BMI an SR (r= -0.40, p < 0.0001) and SE (r= -0.36, p < 0.0001) was observed. Figure 1 shows the differences in median scores for the “food liking” (Fig. 1 , panel A) and “food avoiding” (Fig. 1 , panel B) subscales according to weight status. The Kruskal-Wallis test showed a significant difference in 5 out of the 8 subscales [FR: χ2(4) = 33.769, p = < 0.0001; EOE: χ2(4) = 17.229, p = 0.0008; EF: χ2(4) = 33.611, p = < 0.0001; SR χ2(4) = 28.085, p = < 0.0001; SE χ2(4) = 25.213, p = < 0.0001]. The post-hoc analysis revealed that Children with obesity showed significantly higher scores compared to normal-weight and overweight group in FR (p < 0.0001 and p = 0.0008, respectively), EOE (p = 0.003 and p = 0.01, respectively), and EF (p < 0.0001 and p = 0.005, respectively). Accordingly, children with obesity showed lower scores in SR compared to normal-weight (p < 0.0001) and overweight group (p = 0.04) and SE compared to normal-weight group (p 0.05). Discussion The aim of the present study was to validate the Italian version of the Children’s Eating Behaviour Questionnair in a sample of Italian children aged 4 to 12 years, in order to provide a reliable tool for assessing eating behaviours in the paediatric population. The findings largely support the original theoretical structure proposed by Wardle et al. [ 6 ], confirming the applicability of the CEBQ within the Italian context. The test–retest analysis indicated that the questionnaire exhibits generally satisfactory temporal stability. Subscales showed ICC coefficients from moderate to good, while pre–post correlations confirmed high consistency across administrations. Furthermore, the absence of significant differences in t-tests suggests no systematic changes in scores over time. These findings suggest that the instrument reliably measures the targeted constructs over time, making it suitable for both clinical assessment and research. Notably, the SE subscale, with particularly high ICC and correlation values, demonstrates greater stability than other subscales, suggesting that some construct dimensions may be more robust over time. Overall, these results support the use of the questionnaire as a reliable tool for detecting stable individual differences across administrations, providing confidence in the validity of longitudinal data collected. Exploratory factor analysis confirmed the presence of eight core factors, corresponding to the theoretical subscales of the questionnaire. The factor loadings were consistent with international literature, indicating a sound latent structure of the construct. Additionally, the KMO index of 0.832 and a significant Bartlett’s test of sphericity supported the adequacy of the sample for factor analysis. Subsequent CFA yielded acceptable fit indices for the RMSEA and SRMR, while the CFI and TLI, though below optimal thresholds, fall within a range reported in similar studies conducted on non-English-speaking populations [ 20 , 21 ]. It is plausible that the relatively small sample size may have negatively influenced these latter indices. Nonetheless, the fidelity to the original theoretical model and the observed cross-cultural replicability suggest that the factor structure is sufficiently robust in the Italian context. Regarding internal consistency, all subscales demonstrated Cronbach’s alpha values ≥ 0.70 that indicate a generally good internal reliability of the Italian version of the questionnaire. No significant gender differences were found across the CEBQ subscales, in line with the findings of Wardle et al. [ 6 ]. This suggests that the eating behaviours assessed by the CEBQ are not strongly influenced by sex in this age range. With regard to BMI-z categories, the analysis revealed patterns consistent with existing literature: children with severe obesity reported significantly higher scores on food liking subscales such as Food Responsiveness, Enjoyment of Food, and Emotional Overeating, and lower scores on inhibitory subscales such as Satiety Responsiveness and Slowness in Eating. These findings support the hypothesis that childhood obesity is associated with increased food orientation and reduced internal appetite regulation, in line with previous research [ 4 , 8 ]. The findings of this study confirm that the Italian version of the CEBQ is a valid and reliable tool for assessing eating behaviours in paediatric populations. Its ease of administration, combined with the ability to differentiate between obesogenic and protective eating behaviours, makes it suitable for both clinical and preventive settings. Routine use of the CEBQ by paediatricians, nutritionists, and psychologists may facilitate the early identification of children at risk for eating-related disorders or overweight, enabling the development of tailored interventions targeting specific behavioural patterns. This study presents several limitations. First, the sample size, although sufficient for preliminary analyses, limits the generalizability of the findings and may have contributed to the suboptimal model fit in the confirmatory factor analysis (CFA). Second, the sample is not representative of the entire Italian population, as participants were recruited from only two geographic areas and included a high proportion of children with elevated BMI. Additionally, the cross-sectional design of the study precludes assessment of the sensitivity to behavioural changes over time. Despite these limitations, the results support the use of the CEBQ Italian version as a valid instrument for measuring eating behaviours in children. The questionnaire might be helpful in highlight changes in eating habits, both physiological or pathological, in the long term and then, in early diagnose eating behaviour disorders in free living subjects. Moreover, it would be useful for assessing the effects io behavioural therapy on eating habits in the multidisciplinary treatment of childhood/adolescence obesity. Abbreviations CEBQ Child Eating Behavior Questionnaire CFI Comparative Fit Index DD Desire to drink EF Enjoyment of food EFA Exploratory Factor Analysis EOE Emotional overeating EUE Emotional undereating FF Food fussiness FR Food responsiveness ICC Intraclass correlation coefficient KMO Kaiser-Meyer-Olkin PCA Principal Component Analysis RMSEA Root Mean Square Error of Approximation SE Slowness in eating SR Satiety responsiveness SRMR Standardized Root Mean Square Residual TLI Tucker-Lewis Index Declarations Acknowledgments We acknowledge all the families and participants that contributed to the study Author contribution GRU: supervision, conception, first draft writing; GR and GC: data curation; MS: investigation; ADS and PM statistical analyses; EMDG: writing editing final draft; MC: conception, writing editing final draft. All the authors read and approved the final manuscript. Funding No funding was received for this study. Availability of data and materials The dataset(s) supporting the conclusions of this article is(are) available upon reasonable request to the corresponding author. Ethical approval and consent to participate All procedures performed in the present study were in accordance with the Declaration of Helsinki. Ethical approval was obtained from the Institutional Ethic Committee (protocol n. 266/2018). Written informed consent was collected from each participant. Consent for publication Not applicable. Competing interests All authors declare that they have no competing interests References Pulungan AB, Puteri HA, Ratnasari AF, Hoey H, Utari A, Darendeliler F, et al. Childhood Obesity as a Global Problem: a Cross-sectional Survey on Global Awareness and National Program Implementation. J Clin Res Pediatr Endocrinol. 2023;16(1):31-40. Scaglioni S, De Cosmi V, Ciappolino V, Parazzini F, Brambilla P, Agostoni C. Factors Influencing Children's Eating Behaviours. Nutrients.2018;10(6):706. Blissett J, Fogel A. Emotional eating and obesity in children: The role of parenting. International Journal of Obesity. 2023;37(7), 765–771. Carnell S, Wardle J. Appetitive traits in children. New evidence for associations with weight and a common, behavioral phenotype in early childhood. International Journal of Obesity. 2008;32(3), 343–351. Webber L, Hill C, Cooke L, Carnell S, Wardle J. Associations between child weight and maternal feeding styles are mediated by maternal perceptions and concerns. European Journal of Clinical Nutrition. 2009; 64(3), 259–265. Wardle J, Guthrie CA, Sanderson S, Rapoport L. Development of the Children’s Eating Behaviour Questionnaire. The Journal of Child Psychology and Psychiatry. 2001;42(7), 963–970. Sánchez U, Weisstaub G, Santos JL, Corvalán C, Uauy R. GOCS cohort: Children’s Eating Behaviour Questionnaire (CEBQ) and BMI in Chilean preschool children. Appetite. 2016;100, 32–36. Viana V, Sinde S, Saxton, JC. Children's Eating Behaviour Questionnaire: Associations with BMI in Portuguese children. Br J Nutr. 2008;00(2), 445–450. Gao M, Xue K, Guo H. Reliability and Validity Study of the Children's Eating Behavior Questionnaire in Chinese School-Age Children. J Nutr Sci Vitaminol (Tokyo). 2020;66(Supplement):S82-S86. Sleddens EFC, Kremers SPJ, Thijs C. The Children’s Eating Behaviour Questionnaire: Factorial validity and association with Body Mass Index in Dutch children aged 6–7. nt J Behav Nutr Phys Act. 2008;20;5:49. Birch LL, Ventura AK. Preventing childhood obesity: What works? International Journal of Obesity. 2009;33(S1), S74–S81. de Onis M, Onyango AW, Borghi E, Siyam A, Nishida C, Siekmann J. Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ. 2007;85(9):660-7. Cole TJ. The LMS method for constructing normalized growth standards. Eur J Clin Nutr. 1990;44(1):45-60. Pietrobelli A, Pecoraro L, Ferruzzi A. Effects of COVID‐19 Lockdown on Life-style Behaviors in Children with Obesity Living in Verona, Italy: A Longitudinal Study. Obesity. 2020;28:1382-1385. Sweetman C, Wardle J, Cooke L. Soft drinks and 'desire to drink' in preschoolers. International Journal of Behavioral Nutrition and Physical Activity. 2008;2;5:60. Dovey TM, Staples PA, Gibson EL, Halford JC. Food neophobia and 'picky/fussy' eating in children: a review. Appetite. 2008;50(2-3):181-193. Rundle AG, Park Y, Herbstman JB. COVID‐19–Related School Closings and Risk of Weight Gain Among Children. Obesity. 2020; 28(6):1008-1009. Marsh HW, Muthén B, Asparouhov T, Lüdtke O, Robitzsch A, Morin AJS, et al. Exploratory Structural Equation Modeling, Integrating CFA and EFA: Application to Students’ Evaluations of University Teaching. Structural Equation Modeling: A Multidisciplinary Journal. 2009;16(3), 439–476. Cohen J. A power primer. Psychol Bull. 1992;112(1):155-159. Svensson V, Lundborg L, Cao Y, Nowicka P, Marcus C, Sobko T. Obesity related eating behaviour patterns in Swedish preschool children and association with age, gender, and parental weight—Data from the PRIMROSE trial. Appetite. 2011;57(2), 574–579. Zhou Y, Zhang J, Wang T, Zhang Y, Li L, Zhou L. Psychometric properties of the Chinese version of the Children’s Eating Behaviour Questionnaire (CEBQ) among children aged 3–6 years. Appetite. 2015;91, 232–239. Table 4 Table 4 is not available with this version Supplementary Files supplementaltable1cebq.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 15 Apr, 2026 Reviewers invited by journal 13 Apr, 2026 Editor assigned by journal 04 Apr, 2026 First submitted to journal 27 Mar, 2026 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-9150177","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":622533194,"identity":"fd790bfc-31f7-4f7d-b937-50dde034d269","order_by":0,"name":"GIUSEPPINA ROSARIA UMANO","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIiWNgGAWjYDACZiBOgDAZHwAJHj5StDAbgLSwkWIhmwSYJKRM3p3H+MMDhsPR/LObj1V+zbGTYWNgfvjoBh4thod5zCQSGA7nzrhzLO227LZkoMPYjI1z8Glp5jFjAGlpuJFjdltyGzNQCw+bNAEtxh9AWuYDtRRLbqsnrEWemccA7LANQC2MH7cdJqzFgJmtTCLBID134420ZGnGbcd52JgJ+EW+//Dmjz8qrHPn3Ug++PHntmp7fvbmh4/x2nIATEI4zDxgEo9ysC0NSBzGHwRUj4JRMApGwcgEAJcaQs+AYzkyAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-5570-6620","institution":"Universita degli Studi della Campania Luigi Vanvitelli","correspondingAuthor":true,"prefix":"","firstName":"GIUSEPPINA","middleName":"ROSARIA","lastName":"UMANO","suffix":""},{"id":622533195,"identity":"736c78af-39a5-4578-b0f9-28ef80197322","order_by":1,"name":"Giulia Rondinelli","email":"","orcid":"","institution":"University of Campania Luigi Vanvitelli: Universita degli Studi della Campania Luigi Vanvitelli","correspondingAuthor":false,"prefix":"","firstName":"Giulia","middleName":"","lastName":"Rondinelli","suffix":""},{"id":622533196,"identity":"33711df0-021e-4259-a71f-41e7e9fa92c7","order_by":2,"name":"Margherita Siciliano","email":"","orcid":"","institution":"University of Campania Luigi Vanvitelli: Universita degli Studi della Campania Luigi Vanvitelli","correspondingAuthor":false,"prefix":"","firstName":"Margherita","middleName":"","lastName":"Siciliano","suffix":""},{"id":622533197,"identity":"1c309cf8-4883-41b0-898a-828e160ad64f","order_by":3,"name":"Anna Di Sessa","email":"","orcid":"","institution":"Universita degli Studi della Campania Luigi Vanvitelli","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"Di","lastName":"Sessa","suffix":""},{"id":622533198,"identity":"5759eae1-4acc-4ac3-8a48-1c760a4cddbd","order_by":4,"name":"Pierluigi Marzuillo","email":"","orcid":"","institution":"University of Campania Luigi Vanvitelli: Universita degli Studi della Campania Luigi Vanvitelli","correspondingAuthor":false,"prefix":"","firstName":"Pierluigi","middleName":"","lastName":"Marzuillo","suffix":""},{"id":622533199,"identity":"3ce8e646-b0be-418e-9e57-048f2faa65f2","order_by":5,"name":"Grazia Cirillo","email":"","orcid":"","institution":"University of Campania Luigi Vanvitelli: Universita degli Studi della Campania Luigi Vanvitelli","correspondingAuthor":false,"prefix":"","firstName":"Grazia","middleName":"","lastName":"Cirillo","suffix":""},{"id":622533200,"identity":"46e77906-435c-4e7e-91cf-eb09b1cd805c","order_by":6,"name":"Emanuele Miraglia del Giudice","email":"","orcid":"","institution":"University of Campania Luigi Vanvitelli: Universita degli Studi della Campania Luigi Vanvitelli","correspondingAuthor":false,"prefix":"","firstName":"Emanuele","middleName":"Miraglia del","lastName":"Giudice","suffix":""},{"id":622533201,"identity":"1daff50e-65b9-46c9-a6e7-5c7b3ca49a74","order_by":7,"name":"Margherita Caroli","email":"","orcid":"","institution":": Independent","correspondingAuthor":false,"prefix":"","firstName":"Margherita","middleName":"","lastName":"Caroli","suffix":""}],"badges":[],"createdAt":"2026-03-17 14:50:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9150177/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9150177/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107500026,"identity":"439e4a2b-e429-489a-abc5-bf19b891538b","added_by":"auto","created_at":"2026-04-22 05:43:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":129984,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences in the Food liking and Food avoiding subscales in underweight, normal\u003c/p\u003e\n\u003cp\u003eweight, overweight, and obesity groups\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLegend:\u003c/em\u003e Panel A displays scores in “food liking” subscales and panel B reports scores in “food avoiding” groups according to weight status. Underweight is reported with circles, normal weight is reported with squares, overweight is reported with triangles, and obesity is reported with downward-pointing triangle. DD: desire to drink; EOE: emotional overeating; EUE: emotional undereating; FF: food fussiness; FR: food responsiveness; SR: satiety responsiveness.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9150177/v1/9b426cccc7c1705beaf09281.png"},{"id":107705612,"identity":"b3153ada-fdbe-4d1b-bd07-98e8b6ef024e","added_by":"auto","created_at":"2026-04-24 09:13:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":347001,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9150177/v1/ee1a5bc3-dc7b-4189-8486-e377b787dbd4.pdf"},{"id":107500024,"identity":"d29128a6-b1f2-4e08-bef9-c9568a53bec9","added_by":"auto","created_at":"2026-04-22 05:43:52","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":31742,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaltable1cebq.docx","url":"https://assets-eu.researchsquare.com/files/rs-9150177/v1/4b6b2ae0bc328f5512b5a089.docx"}],"financialInterests":"","formattedTitle":"Validation of the Children Eating Behaviour Questionnaire (CEBQ) in Italian children ​","fulltext":[{"header":"Plain English Summary","content":"\u003cp\u003eThis study looked at how well an Italian version of the Child Eating Behavior Questionnaire (CEBQ) works for understanding kids’ eating habits. CEBQ is a tool parents fill out to describe how their children behave around food (such as how much they enjoy eating or how emotions affects desire to eat). Researchers collected data from 184 Italian children aged 4 to 12, coming from both everyday families and clinical settings. Some parents filled out the questionnaire twice a month apart, to check whether the answers stayed consistent over time. The results showed good reliability, meaning parents’ responses were stable. Statistical analyses also confirmed that the Italian questionnaire kept the same structure as the original version. Overall, the findings show that this Italian CEBQ is a solid and trustworthy way to assess eating behaviors in Italian children and teens, making it useful for both research and practical evaluations.\u003c/p\u003e"},{"header":"Background","content":"\u003cp\u003eThe increasing prevalence of childhood obesity represents a significant challenge to public health globally [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In this context, assessing children's eating behaviors and lifestyles is fundamental to identifying the risk factors associated with obesity and developing targeted interventions [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eChildren\u0026rsquo;s eating behaviour is shaped by a complex interplay of biological, psychological, and environmental factors that often emerge early in life and can significantly contribute to the development of overweight and obesity [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Various theoretical frameworks highlight the central role of temperament, emotional regulation, and sensitivity to internal cues of hunger and satiety as core determinants of eating behaviour in childhood [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this context, understanding eating patterns is a key objective for both clinical research and early intervention. Numerous studies have shown that specific eating behaviour traits -such as heightened food responsiveness, difficulty recognizing satiety, and a tendency to eat in response to negative emotions- are associated with an increased risk of overweight in children [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The systematic assessment of these traits requires validated, standardized, and culturally adapted tools capable of capturing behavioural nuances across different sociocultural contexts. Over the years, the Children\u0026rsquo;s Eating Behaviour Questionnaire (CEBQ) has emerged as one of the most reliable and widely used instruments internationally for evaluating eating behaviours in children [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The questionnaire was designed to provide a reliable and validated instrument for measuring key dimensions of children\u0026rsquo;s eating behaviour. Based on parent-report, the CEBQ encompasses eight subscales grouped into two overarching dimensions: 'food approach' (propensity toward food) and 'food avoidance' (tendency to avoid food). Its multidimensional structure enables the assessment of various behavioural aspects, including emotional responsiveness to food, enjoyment of eating, self-regulation, and sensitivity to satiety cues. This facilitates a comprehensive analysis of the behavioural phenotype associated with obesity risk and might help in tailoring behavioural therapy [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMoreover, several studies conducted across diverse cultural contexts -including the Netherlands, Spain, Turkey, China, and Brazil -have confirmed the robustness of its factorial structure and the good reliability of its subscales [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. These studies have also reported significant correlations between CEBQ subscales and anthropometric indicators such as Body Mass Index (BMI) or BMI-z scores, further supporting the construct validity of the instrument [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, the validation of a psychometric instrument requires a specific process of linguistic and cultural adaptation, which cannot be assumed even in countries with seemingly similar sociocultural contexts. Factors such as the cultural meaning attributed to food, parental feeding practices, meal structure, and social norms can vary substantially, potentially affecting how questionnaire items are understood and interpreted [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Therefore, despite its widespread use, a validated Italian version of the CEBQ is not currently available, limiting its clinical and research application within the Italian context. This gap in the literature represents a significant limitation for the implementation of prevention and intervention programs based on valid and culturally sensitive tools.\u003c/p\u003e \u003cp\u003eIn light of these considerations, the present study aims to: 1) translate and culturally adapt the CEBQ for the Italian population, ensuring conceptual equivalence with the original version; 2) explore its factorial structure through both exploratory and confirmatory factor analyses, to determine whether the original eight-factor model is replicable in the Italian sample; 3) assess its internal reliability using Cronbach\u0026rsquo;s alpha for each subscale; 4) examine construct invariance according to socio-demographic and anthropometric variables, to evaluate the generalizability of the tool across different subgroups of the pediatric population.\u003c/p\u003e \u003cp\u003eTherefore, this study aims to provide an Italian version of the CEBQ that is psychometrically robust, theoretically sound, and clinically useful for professionals and researchers working to promote children\u0026rsquo;s nutritional health and well-being.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eThis study was based on a cross-sectional analysis of data collected from a total of 184 children (mean age 9.24\u0026thinsp;\u0026plusmn;\u0026thinsp;2.96 years, 51.6% males) in the South of Italy. A school-based cohort (n\u0026thinsp;=\u0026thinsp;88), consisting of children aged 9 to 10 years attending primary school in the Apulia region; and a clinical cohort (n\u0026thinsp;=\u0026thinsp;96), consisting of children and adolescents attending the Pediatric Clinic of the University Hospital 'Luigi Vanvitelli' in Naples because of overweight and obesity. Inclusion criteria were age between 4 to 12 years, parents able to speak, read, and understand Italian language and consent to participate. All participating children underwent an anthropometric evaluation. Weight was measured using a beam scale, with the child wearing lightweight clothing. Height was assessed using a Harpenden stadiometer. BMI Body Mass Index (BMI) was calculated using the standard formula: weight (kg) / height\u0026sup2; (m\u0026sup2;) and subsequently converted into age- and sex-standardized z-scores (z-score BMI), based on the WHO growth reference standards [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. A subgroup of parents in the school cohort (real word group) was used to assess the reliability of the test. In this subgroup, the questionnaire was administered twice, with a one-month interval between administrations. Participants were classified into five z-score BMI categories to reflect a continuum from severe underweight to severe obesity. The study was approved by the Ethic Committee (protocol n. 266/2018) and was conducted according to the Declaration of Helsinki.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eThe Children’s Eating Behaviour Questionnaire\u003c/h3\u003e\n\u003cp\u003eThe CEBQ is a parent-report instrument consisting of 35 items divided into eight subscales, with parents reporting on their child\u0026rsquo;s typical eating habits. For this study, the original version by Carnell \u0026amp; Wardle [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] was translated into Italian by two independent research groups. The translations were then compared and harmonized to adapt the 35 items into a common and easily understandable language for all participants (Supplemental Table\u0026nbsp;1). All translators approved the final version.\u003c/p\u003e \u003cp\u003eThe questionnaire comprises eight eating behaviour subscales, each consisting of 3 to 6 items: Food responsiveness (FR, 5 items), Enjoyment of food (EF, 4 items), Emotional overeating (EOE, 4 items), Desire to drink (DD, 3 items), Satiety responsiveness (SR, 5 items), Slowness in eating (SE, 4 items), Emotional undereating (EUE, 4 items), Food fussiness (FF, 6 items). Parents were asked to respond to 35 questions regarding their children's eating behaviour using a 5-point Likert scale, ranging from \"never\" (1) to \"always\" (5), as in the original version [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Higher scores on the sum (or average) of each subscale indicate a greater expression of the eating behaviour represented by that subscale (e.g., food responsiveness, desire to drink, etc.).\u003c/p\u003e \u003cp\u003eThe CEBQ subscales are categorized into \u0026ldquo;food liking\u0026rdquo; (EF, FR, EOE, DD) and \u0026ldquo;food avoiding\u0026rdquo; (SR, SE, EUE, FF) dimensions, with food liking behaviours showing a positive association, and food avoiding behaviours a negative association, with children\u0026rsquo;s relative weight. The EF subscale represents a general interest in food, while the FR subscale aims to measure eating in response to external food cues. It has been observed that these behaviours become more pronounced as children grow older [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The DD subscale measures preference for sugary beverages, indicating that this desire is driven by sweet taste rather than thirst. This increased intake of liquid calories may affect long-term weight [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The SR subscale reflects the ability to regulate food intake based on internal satiety signals. The SE subscale measures the speed of eating during a meal and reflects a gradually reduced interest in the meal. The FF subscale reflects a lack of interest in food and reluctance to try new foods (food neophobia), leading to an inadequate variety of foods [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Finally, the EOE and EUE scales are characterized by an increase or decrease in eating in response to emotions [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe original English questionnaire was translated into Italian by two independent bilingual translators. Their translations were reviewed and combined to produce a single Italian version. This version was then back-translated into English by two native English speakers proficient in Italian, and the back-translations were compared with the original questionnaire. A team of translators and researchers subsequently finalized the Italian form of the scale.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eTest\u0026ndash;retest reliability of the questionnaire was evaluated using three complementary indicators: the\u003c/p\u003e \u003cp\u003eintraclass correlation coefficient (ICC), Spearman correlations between pre- and post-scores, and\u003c/p\u003e \u003cp\u003epaired-samples t-tests comparing the means.\u003c/p\u003e \u003cp\u003eFor the classification of reliability, commonly used thresholds in the literature were adopted. For the\u003c/p\u003e \u003cp\u003eICC a two-way random-effects model with absolute agreement was performed. Intraclass correlation coefficient values\u0026thinsp;\u0026lt;\u0026thinsp;0.50 indicate poor reliability, 0.50\u0026ndash;0.75, moderate 0.75\u0026ndash;0.90 good, and ICC\u0026thinsp;\u0026gt;\u0026thinsp;0.90 excellent. For Spearman correlations, values between 0.10\u0026ndash;0.29 are considered low, 0.30\u0026ndash;0.49 moderate, 0.50\u0026ndash;0.69 good, and \u0026ge;\u0026thinsp;0.70 very good.\u003c/p\u003e \u003cp\u003eTo explore the factorial structure of the CEBQ questionnaire, a Principal Component Analysis (PCA) was initially conducted as a preliminary exploratory procedure. Moreover, since PCA considers total variance (common, specific, and error variance), an Exploratory Factor Analysis (EFA) was subsequently performed to identify the underlying latent factorial structure.\u003c/p\u003e \u003cp\u003eThe adequacy of the sample for factor analysis was assessed using the Kaiser-Meyer-Olkin (KMO) index and the Bartlett\u0026rsquo;s test of sphericity. EFA was conducted using the Minimum Residual extraction method with Varimax rotation. To evaluate the goodness of fit of the factorial structure emerging from the Exploratory Factor Analysis (EFA), a Confirmatory Factor Analysis (CFA) was performed. Several fit indices were used to evaluate how well the hypothesized model fits the observed data, including the RMSEA (Root Mean Square Error of Approximation), the SRMR (Standardized Root Mean Square Residual), the CFI (Comparative Fit Index), and the TLI (Tucker-Lewis Index) evaluate the approximation error; values below 0.08 are generally considered acceptable. The CFI (Comparative Fit Index) and TLI (Tucker-Lewis Index) assess model fit by comparing the tested model to a null model, with values\u0026thinsp;\u0026ge;\u0026thinsp;0.90 indicating acceptable fit and \u0026ge;\u0026thinsp;0.95 indicating good fit [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe internal reliability of the extracted dimensions was assessed using Cronbach\u0026rsquo;s α coefficient. Cronbach\u0026rsquo;s alpha is a measure of internal consistency, indicating how closely related a set of items are as a group. Values below 0.40 suggest low reliability; values between 0.40 and 0.60 indicate questionable reliability; values between 0.60 and 0.80 are considered acceptable; and values between 0.80 and 0.90 indicate good reliability.\u003c/p\u003e \u003cp\u003eSpearman\u0026rsquo;s rank-order correlation was conducted to examine the inter-correlation between subscales and the correlation between the eight subscale scores and continuous variables, namely age, BMI, and z-score BMI. A correlation coefficient\u0026thinsp;\u0026gt;\u0026thinsp;0.50 is considered a large effect, between 0.3 and 0.5 a medium effect [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The Mann-Whitney U test was conducted to test differences between the two groups (primary school and University Hospital) and sex in CEBQ subscales. The Kruskal-Wallis test was performed to test differences according to weight status (underweight, normal-weight, overweight, and obesity), the Dunn test was applied for post-hoc analysis and multiple comparison.\u003c/p\u003e \u003cp\u003eThe statistical procedures for exploratory factor analysis (EFA) and CFA were performed with Jamovi (version 2.6.44), while the statistical procedures for the correlation analyses were performed with SPSS (version 20).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 184 questionnaires were completed by parents. The mean age of the children in the sample was 9.24\u0026thinsp;\u0026plusmn;\u0026thinsp;2.96 years, 51.6% were males, mean BMI was 20.94\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3, and mean z-score BMI was 1.40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e describes the anthropometric and CEBQ subscales scores of the sample.\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\u003eCharacteristics of the cohort\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticipants\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;184\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup (primary school/University Hospital, n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88/96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.24\u0026thinsp;\u0026plusmn;\u0026thinsp;2.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (M/F, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.6/48.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.94\u0026thinsp;\u0026plusmn;\u0026thinsp;5.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZ-score BMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood Responsiveness (FR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.55\u0026thinsp;\u0026plusmn;\u0026thinsp;5.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood Fussiness (FF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.33\u0026thinsp;\u0026plusmn;\u0026thinsp;5.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSlowness in Eating (SE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.74\u0026thinsp;\u0026plusmn;\u0026thinsp;4.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmotional Under-Eating (EUE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.59\u0026thinsp;\u0026plusmn;\u0026thinsp;3.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDesire to Drink (DD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.02\u0026thinsp;\u0026plusmn;\u0026thinsp;3.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSatiety Responsiveness (SR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.72\u0026thinsp;\u0026plusmn;\u0026thinsp;4.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnjoyment of Food (EF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.09\u0026thinsp;\u0026plusmn;\u0026thinsp;3.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmotional Over-Eating (EOE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.04\u0026thinsp;\u0026plusmn;\u0026thinsp;3.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eData are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviations and as percentages for continuous variables\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eTest–retest reliability\u003c/h3\u003e\n\u003cp\u003eThe subscales demonstrated stability between test and re-test ranging from moderate to good. Specifically, the FR subscale showed ICC(2,1)\u0026thinsp;=\u0026thinsp;0.624 (95% C.I.: 0.462\u0026ndash;0.746, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), EOE ICC(2,1)\u0026thinsp;=\u0026thinsp;0.632 (95% C.I.: 0.472\u0026ndash;0.751, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), EF ICC(2,1)\u0026thinsp;=\u0026thinsp;0.697 (95% C.I.: 0.559\u0026ndash;0.797, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), DD ICC(2,1)\u0026thinsp;=\u0026thinsp;0.721 (95% C.I.: 0.591\u0026ndash;0.815, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), SR ICC(2,1)\u0026thinsp;=\u0026thinsp;0.741 (95% C.I.: 0.618\u0026ndash;0.828, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), SE ICC(2,1)\u0026thinsp;=\u0026thinsp;0.796, (95% C.I.: 0.692\u0026ndash;0.867, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) EUE ICC(2,1)\u0026thinsp;=\u0026thinsp;0.620 (95% C.I.: 0.459\u0026ndash;0.743, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and FF ICC(2,1)\u0026thinsp;=\u0026thinsp;0.711 (95% C.I.: 0.576\u0026ndash;0.808, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Overall, these values indicate satisfactory temporal stability for all subscales.\u003c/p\u003e \u003cp\u003eSpearman correlations between the two administrations confirmed the pattern observed with the ICCs, with values ranging from 0.54 to 0.77 (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Specifically: FR r\u0026thinsp;=\u0026thinsp;0.541; EOE r\u0026thinsp;=\u0026thinsp;0.618; EF r\u0026thinsp;=\u0026thinsp;0.727; DD r\u0026thinsp;=\u0026thinsp;0.679; SR r\u0026thinsp;=\u0026thinsp;0.690; SE r\u0026thinsp;=\u0026thinsp;0.771; EUE r\u0026thinsp;=\u0026thinsp;0.625; FF r\u0026thinsp;=\u0026thinsp;0.728. These results indicate high consistency between pre- and post-scores, ranging from good to very good.\u003c/p\u003e \u003cp\u003ePaired-samples t-tests revealed no significant differences between T1 and T2 for any subscale (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), indicating that scores did not change systematically between the two administrations.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eExploratory and Confirmatory Factor Analysis\u003c/h2\u003e \u003cp\u003eThe PCA analysis suggested the presence of eight main components (as expected from the original structure of the questionnaire from which it was translated), based on the Kaiser criterion (eigenvalue\u0026thinsp;\u0026gt;\u0026thinsp;1) and the inspection of the scree plot, with a total explained variance of 66.8%. The Kaiser-Meyer-Olkin index showed a value of 0.832, indicating a sufficient correlation among variables. Additionally, Bartlett\u0026rsquo;s test of sphericity was significant (χ\u0026sup2; =2947, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), confirming the presence of relationships between variables and supporting the suitability of factor analysis.\u003c/p\u003e \u003cp\u003eEFA confirmed the extraction of eight factors, consistent with the PCA results. The extracted factors explained 57.5% of the total variance, a lower value compared to PCA, as EFA extracts only common variance while excluding specific and error variance.\u003c/p\u003e \u003cp\u003eThe analysis of the factor loading matrix showed that the items clustered coherently with the theoretical dimensions of the questionnaire, with factor loadings above 0.40 for each item on its respective factor.\u003c/p\u003e \u003cp\u003eThe CFA analysis revealed an adequate model fit, with RMSEA\u0026thinsp;=\u0026thinsp;0.0668 and SRMR\u0026thinsp;=\u0026thinsp;0.0754. However, the CFI (0.851) and TLI (0.833) values are below the optimal threshold of 0.90, indicating some discrepancy between the theoretical model and the observed data (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\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\u003eModel fit indices from Confirmatory Factorial Analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eχ\u0026sup2; (degree of freedom)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e969 (532)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eχ\u0026sup2; p value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCFI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.851\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTLI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.833\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSRMR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0754\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRMSEA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0668\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eLegend: CFI: Comparative Fit Index; RMSEA: Root Mean Square Error of Approximation; SRMR: Standardized Root Mean Square Residual; TLI: Tucker-Lewis Index\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eReliability\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e displays the results of the reliability test. Cronbach\u0026rsquo;s α coefficient ranged between 0.70\u0026ndash;0.85 for all subscales. These values indicate good internal consistency of the scales, with coefficients exceeding the acceptability threshold of 0.70, except for the EOE factor (0.70), which still approaches an acceptable level of reliability.\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\u003eInternal reliability of the sample\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCEBQ Factor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (DS)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCronbach\u0026rsquo;s α coefficient\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood Responsiveness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.55 (5.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.849\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood Fussiness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.33 (5.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.833\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSlowness in Eating\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.74 (4.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.831\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmotional Under-Eating\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.59 (3.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.725\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDesire to Drink\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.02 (3.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.772\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSatiety Responsiveness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.72 (4.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.767\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnjoyment of Food\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.09 (3.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.823\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmotional Over-Eating\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.04 (3.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.697\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\u003eSpearman correlation analyses showed that the \u0026ldquo;food avoiding\u0026rdquo; subscales (FF, SE, SR, and EUE) and the \u0026ldquo;food approach\u0026rdquo; subscales were positively inter-correlated (Table\u0026nbsp;4). Moreover, we observed an inverse correlation between the \u0026ldquo;food liking\u0026rdquo; and the \u0026ldquo;food avoiding\u0026rdquo; subscales, except for EOE and EUE that were positively correlated (r\u0026thinsp;=\u0026thinsp;0.42, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The EOE-FR, EF-SR, EF-FR, and SR-SE showed a large inter-correlation, whereas the EOE-EUE, SE-EF, FF-EF, FF-FR, and FR-SE a moderate correlation. The DD subscale showed no significant correlation with any of the other subscales.\u003c/p\u003e\n\u003ch3\u003eAge, gender, and weight differences\u003c/h3\u003e\n\u003cp\u003eWe observed a direct correlation between children\u0026rsquo;s age and EOE subscale (r\u0026thinsp;=\u0026thinsp;0.19, p\u0026thinsp;=\u0026thinsp;0.008), no other significant were observed between age and the other subscales (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Moreover, no differences were observed between males and females. Conversely, z-score BMI was positively correlated with FR (r\u0026thinsp;=\u0026thinsp;0.41, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), EOE (r\u0026thinsp;=\u0026thinsp;0.28, p\u0026thinsp;=\u0026thinsp;0.0002), and EF (r\u0026thinsp;=\u0026thinsp;0.44, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). An inverse correlation between z-score BMI an SR (r= -0.40, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and SE (r= -0.36, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) was observed. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the differences in median scores for the \u0026ldquo;food liking\u0026rdquo; (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, panel A) and \u0026ldquo;food avoiding\u0026rdquo; (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, panel B) subscales according to weight status.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe Kruskal-Wallis test showed a significant difference in 5 out of the 8 subscales [FR: χ2(4)\u0026thinsp;=\u0026thinsp;33.769, p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; EOE: χ2(4)\u0026thinsp;=\u0026thinsp;17.229, p\u0026thinsp;=\u0026thinsp;0.0008; EF: χ2(4)\u0026thinsp;=\u0026thinsp;33.611, p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; SR χ2(4)\u0026thinsp;=\u0026thinsp;28.085, p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; SE χ2(4)\u0026thinsp;=\u0026thinsp;25.213, p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.0001]. The post-hoc analysis revealed that Children with obesity showed significantly higher scores compared to normal-weight and overweight group in FR (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 and p\u0026thinsp;=\u0026thinsp;0.0008, respectively), EOE (p\u0026thinsp;=\u0026thinsp;0.003 and p\u0026thinsp;=\u0026thinsp;0.01, respectively), and EF (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 and p\u0026thinsp;=\u0026thinsp;0.005, respectively). Accordingly, children with obesity showed lower scores in SR compared to normal-weight (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and overweight group (p\u0026thinsp;=\u0026thinsp;0.04) and SE compared to normal-weight group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Moreover, underweight group showed significantly lower score in EF compared to obesity group (p\u0026thinsp;=\u0026thinsp;0.02). No differences were observed for DD, EUE, and FF (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe aim of the present study was to validate the Italian version of the Children\u0026rsquo;s Eating Behaviour Questionnair in a sample of Italian children aged 4 to 12 years, in order to provide a reliable tool for assessing eating behaviours in the paediatric population. The findings largely support the original theoretical structure proposed by Wardle et al. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], confirming the applicability of the CEBQ within the Italian context.\u003c/p\u003e \u003cp\u003eThe test\u0026ndash;retest analysis indicated that the questionnaire exhibits generally satisfactory temporal stability. Subscales showed ICC coefficients from moderate to good, while pre\u0026ndash;post correlations confirmed high consistency across administrations. Furthermore, the absence of significant differences in t-tests suggests no systematic changes in scores over time. These findings suggest that the instrument reliably measures the targeted constructs over time, making it suitable for both clinical assessment and research. Notably, the SE subscale, with particularly high ICC and correlation values, demonstrates greater stability than other subscales, suggesting that some construct dimensions may be more robust over time. Overall, these results support the use of the questionnaire as a reliable tool for detecting stable individual differences across administrations, providing confidence in the validity of longitudinal data collected.\u003c/p\u003e \u003cp\u003eExploratory factor analysis confirmed the presence of eight core factors, corresponding to the theoretical subscales of the questionnaire. The factor loadings were consistent with international literature, indicating a sound latent structure of the construct. Additionally, the KMO index of 0.832 and a significant Bartlett\u0026rsquo;s test of sphericity supported the adequacy of the sample for factor analysis.\u003c/p\u003e \u003cp\u003eSubsequent CFA yielded acceptable fit indices for the RMSEA and SRMR, while the CFI and TLI, though below optimal thresholds, fall within a range reported in similar studies conducted on non-English-speaking populations [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. It is plausible that the relatively small sample size may have negatively influenced these latter indices. Nonetheless, the fidelity to the original theoretical model and the observed cross-cultural replicability suggest that the factor structure is sufficiently robust in the Italian context.\u003c/p\u003e \u003cp\u003eRegarding internal consistency, all subscales demonstrated Cronbach\u0026rsquo;s alpha values\u0026thinsp;\u0026ge;\u0026thinsp;0.70 that indicate a generally good internal reliability of the Italian version of the questionnaire.\u003c/p\u003e \u003cp\u003eNo significant gender differences were found across the CEBQ subscales, in line with the findings of Wardle et al. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This suggests that the eating behaviours assessed by the CEBQ are not strongly influenced by sex in this age range.\u003c/p\u003e \u003cp\u003eWith regard to BMI-z categories, the analysis revealed patterns consistent with existing literature: children with severe obesity reported significantly higher scores on food liking subscales such as Food Responsiveness, Enjoyment of Food, and Emotional Overeating, and lower scores on inhibitory subscales such as Satiety Responsiveness and Slowness in Eating. These findings support the hypothesis that childhood obesity is associated with increased food orientation and reduced internal appetite regulation, in line with previous research [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe findings of this study confirm that the Italian version of the CEBQ is a valid and reliable tool for assessing eating behaviours in paediatric populations. Its ease of administration, combined with the ability to differentiate between obesogenic and protective eating behaviours, makes it suitable for both clinical and preventive settings.\u003c/p\u003e \u003cp\u003eRoutine use of the CEBQ by paediatricians, nutritionists, and psychologists may facilitate the early identification of children at risk for eating-related disorders or overweight, enabling the development of tailored interventions targeting specific behavioural patterns.\u003c/p\u003e \u003cp\u003eThis study presents several limitations. First, the sample size, although sufficient for preliminary analyses, limits the generalizability of the findings and may have contributed to the suboptimal model fit in the confirmatory factor analysis (CFA). Second, the sample is not representative of the entire Italian population, as participants were recruited from only two geographic areas and included a high proportion of children with elevated BMI. Additionally, the cross-sectional design of the study precludes assessment of the sensitivity to behavioural changes over time.\u003c/p\u003e \u003cp\u003eDespite these limitations, the results support the use of the CEBQ Italian version as a valid instrument for measuring eating behaviours in children. The questionnaire might be helpful in highlight changes in eating habits, both physiological or pathological, in the long term and then, in early diagnose eating behaviour disorders in free living subjects. Moreover, it would be useful for assessing the effects io behavioural therapy on eating habits in the multidisciplinary treatment of childhood/adolescence obesity.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCEBQ\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChild Eating Behavior Questionnaire\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCFI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eComparative Fit Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDesire to drink\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEnjoyment of food\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEFA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eExploratory Factor Analysis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEOE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEmotional overeating\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEUE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEmotional undereating\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFood fussiness\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFood responsiveness\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntraclass correlation coefficient\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKMO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKaiser-Meyer-Olkin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePrincipal Component Analysis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRMSEA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRoot Mean Square Error of Approximation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSlowness in eating\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSatiety responsiveness\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSRMR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandardized Root Mean Square Residual\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTLI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTucker-Lewis Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003eWe acknowledge all the families and participants that contributed to the study\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGRU: supervision, conception, first draft writing; GR and GC: data curation; MS: investigation; ADS and PM statistical analyses; EMDG: writing editing final draft; MC: conception, writing editing final draft. All the authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset(s) supporting the conclusions of this article is(are) available upon reasonable request to the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures performed in the present study were in accordance with the Declaration of Helsinki. Ethical approval was obtained from the Institutional Ethic Committee (protocol n. 266/2018). Written informed consent was collected from each participant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare that they have no competing interests\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003ePulungan AB, Puteri HA, Ratnasari AF, Hoey H, Utari A, Darendeliler F, et al. Childhood Obesity as a Global Problem: a Cross-sectional Survey on Global Awareness and National Program Implementation. J Clin Res Pediatr Endocrinol. 2023;16(1):31-40.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eScaglioni S, De Cosmi V, Ciappolino V, Parazzini F, Brambilla P, Agostoni C. Factors Influencing Children\u0026apos;s Eating Behaviours. Nutrients.2018;10(6):706.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eBlissett J, Fogel A. Emotional eating and obesity in children: The role of parenting. International Journal of Obesity. 2023;37(7), 765\u0026ndash;771.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCarnell S, Wardle J. Appetitive traits in children. New evidence for associations with weight and a common, behavioral phenotype in early childhood. International Journal of Obesity. 2008;32(3), 343\u0026ndash;351.\u003c/li\u003e\n \u003cli\u003eWebber L, Hill C, Cooke L, Carnell S, Wardle J. Associations between child weight and maternal feeding styles are mediated by maternal perceptions and concerns. European Journal of Clinical Nutrition. 2009; 64(3), 259\u0026ndash;265.\u003c/li\u003e\n \u003cli\u003eWardle J, Guthrie CA, Sanderson S, Rapoport L. Development of the Children\u0026rsquo;s Eating Behaviour Questionnaire. The Journal of Child Psychology and Psychiatry. 2001;42(7), 963\u0026ndash;970.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eS\u0026aacute;nchez U, Weisstaub G, Santos JL, Corval\u0026aacute;n C, Uauy R. GOCS cohort: Children\u0026rsquo;s Eating Behaviour Questionnaire (CEBQ) and BMI in Chilean preschool children. Appetite. 2016;100, 32\u0026ndash;36.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eViana V, Sinde S, Saxton, JC. Children\u0026apos;s Eating Behaviour Questionnaire: Associations with BMI in Portuguese children. Br J Nutr. 2008;00(2), 445\u0026ndash;450.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eGao M, Xue K, Guo H. Reliability and Validity Study of the Children\u0026apos;s Eating Behavior Questionnaire in Chinese School-Age Children. J Nutr Sci Vitaminol (Tokyo). 2020;66(Supplement):S82-S86.\u003c/li\u003e\n \u003cli\u003eSleddens EFC, Kremers SPJ, Thijs C. The Children\u0026rsquo;s Eating Behaviour Questionnaire: Factorial validity and association with Body Mass Index in Dutch children aged 6\u0026ndash;7. nt J Behav Nutr Phys Act. 2008;20;5:49.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eBirch LL, Ventura AK. Preventing childhood obesity: What works? International Journal of Obesity. 2009;33(S1), S74\u0026ndash;S81.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003ede Onis M, Onyango AW, Borghi E, Siyam A, Nishida C, Siekmann J. Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ. 2007;85(9):660-7.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCole TJ. The LMS method for constructing normalized growth standards. Eur J Clin Nutr. 1990;44(1):45-60.\u003c/li\u003e\n \u003cli\u003ePietrobelli A, Pecoraro L, Ferruzzi A. Effects of COVID‐19 Lockdown on Life-style Behaviors in Children with Obesity Living in Verona, Italy: A Longitudinal Study. Obesity. 2020;28:1382-1385. \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSweetman C, Wardle J, Cooke L. Soft drinks and \u0026apos;desire to drink\u0026apos; in preschoolers. International Journal of Behavioral Nutrition and Physical Activity. 2008;2;5:60.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eDovey TM, Staples PA, Gibson EL, Halford JC. Food neophobia and \u0026apos;picky/fussy\u0026apos; eating in children: a review. Appetite. 2008;50(2-3):181-193.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eRundle AG, Park Y, Herbstman JB. COVID‐19\u0026ndash;Related School Closings and Risk of Weight Gain Among Children. Obesity. 2020; 28(6):1008-1009.\u003c/li\u003e\n \u003cli\u003eMarsh HW, Muth\u0026eacute;n B, Asparouhov T, L\u0026uuml;dtke O, Robitzsch A, Morin AJS, et al. Exploratory Structural Equation Modeling, Integrating CFA and EFA: Application to Students\u0026rsquo; Evaluations of University Teaching. Structural Equation Modeling: A Multidisciplinary Journal. 2009;16(3), 439\u0026ndash;476.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCohen J. A power primer. Psychol Bull. 1992;112(1):155-159.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSvensson V, Lundborg L, Cao Y, Nowicka P, Marcus C, Sobko T. Obesity related eating behaviour patterns in Swedish preschool children and association with age, gender, and parental weight\u0026mdash;Data from the PRIMROSE trial. Appetite. 2011;57(2), 574\u0026ndash;579.\u003c/li\u003e\n \u003cli\u003eZhou Y, Zhang J, Wang T, Zhang Y, Li L, Zhou L. Psychometric properties of the Chinese version of the Children\u0026rsquo;s Eating Behaviour Questionnaire (CEBQ) among children aged 3\u0026ndash;6 years. Appetite. 2015;91, 232\u0026ndash;239.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 4","content":"\u003cp\u003eTable 4 is not available with this version\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"italian-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"itjp","sideBox":"Learn more about [Italian Journal of Pediatrics](http://ijponline.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ITJP/default.aspx","title":"Italian Journal of Pediatrics","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"CEBQ, children and adolescents, eating behaviours","lastPublishedDoi":"10.21203/rs.3.rs-9150177/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9150177/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eChildhood eating patterns play a crucial role in shaping long-term health and well-being, underscoring the importance of reliable assessment tools. The Child Eating Behavior Questionnaire (CEBQ) is a widely used parent-report measure that has been validated across numerous languages and populations. This study examines the validity of an Italian version of the CEBQ for use in Italian-speaking populations.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eUsing a cross-sectional design, 184 children (51.6% males) aged 4\u0026ndash;12 years were recruited from both clinical and community settings. Parents completed the CEBQ to report their child\u0026rsquo;s eating behaviors across the \u0026ldquo;food liking\u0026rdquo; and four \u0026ldquo;food avoiding\u0026rdquo; subscales. In a subgroup of parents, the questionnaire was administered twice (after one month) for test-retest reliability assessment. Factorial analysis was performed to test questionnaire structure consistency with the original CEBQ. Children\u0026rsquo;s height and weight were recorded to calculate BMI and BMI z-scores.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe test-retest analysis confirmed the reliability of the questionnaires. The r spearman correlation between the two administrations ranged from 0.54 to 0.77. The ICCs ranged from 0.62 to 0.796. The Principal Component Analysis (PCA) identified eight principal components (matching the original questionnaire structure) with a total explained variance of 66.8%. The Kaiser-Meyer-Olkin value (0.832) indicated adequate sampling, and Bartlett\u0026rsquo;s test was significant, confirming sufficient correlations for factor analysis. The Exploratory Factor Analysis further supported the extraction of eight factors, consistent with the PCA findings.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis Italian version of the CEBQ is a valid and reliable instrument for the evaluation of eating behaviours in Italian children and adolescents.\u003c/p\u003e","manuscriptTitle":"Validation of the Children Eating Behaviour Questionnaire (CEBQ) in Italian children ​","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-22 05:43:48","doi":"10.21203/rs.3.rs-9150177/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2026-04-15T04:51:47+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-13T19:44:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-04T04:37:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"Italian Journal of Pediatrics","date":"2026-03-27T07:57:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"italian-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"itjp","sideBox":"Learn more about [Italian Journal of Pediatrics](http://ijponline.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ITJP/default.aspx","title":"Italian Journal of Pediatrics","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fecdf17c-847b-41ea-8e27-136f9eeb4cc4","owner":[],"postedDate":"April 22nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T05:43:48+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-22 05:43:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9150177","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9150177","identity":"rs-9150177","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}