Emotional eating and adolescents body weight: the mediating role of dietary patterns in Taizhou, China

Emotional eating and adolescents body weight: the mediating role of dietary patterns in Taizhou, China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Emotional eating and adolescents body weight: the mediating role of dietary patterns in Taizhou, China Meixian Zhang, Dan Wang, Huiyan Yin, Huanhuan Shi, Hailing Fan, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6468108/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background/Objectives: Emotional eating has been linked to obesity. Although many studies have examined this association, the underlying mechanisms remain unclear . This study aimed to investigate whether dietary patterns mediate the relationship between emotional eating and body weight among adolescents. Subjects/Methods: This cross-sectional study utilized convenience sampling to recruit students from a middle school in Taizhou City, Zhejiang Province, China, between September 2022 and October 2022. This study adhered to the STROBE guidelines. Emotional eating was evaluated using the Emotional Eating Scale for Chinese Adolescents, and dietary patterns were derived through principal component analysis of data from the Food Frequency Questionnaire. Body mass index Z-scores (BMIZs) and waist-to-height ratios (WHtR) were used as indicators of body weight. Mediation analysis was applied to explore the indirect effects. Interventions: Not applicable. Results: Two dietary patterns were identified: traditional and modern. The modern pattern—characterised by high consumption of snacks, carbohydrate, fats, and sugars—was substantially linked to emotional eating and body weight (p < 0.001). Mediation analysis showed that this dietary pattern partially mediated the relationship between emotional eating and body weight, with indirect effects of 0.020 (95% confidence interval [CI] [0.016, 0.023]) for WHtR and 0.446 (95% CI [0.387, 0.509]) for BMIZ. Conclusions: Emotional eating in adolescents is associated with increased body weight, and this relationship is partially mediated by a modern dietary pattern rich in snacks, carbohydrates, fats, and sugars. These results suggest that clinical interventions targeting emotional eating should also consider underlying dietary behaviours to more effectively support healthy weight management in adolescents. Health sciences/Health care/Paediatrics Health sciences/Endocrinology/Endocrine system and metabolic diseases/Obesity Health sciences/Health care/Public health/Epidemiology Health sciences/Health care/Nutrition adolescents emotional eating dietary pattern obesity mediation analysis public health Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Emotional eating (EE) is the tendency to consume or increase food intake in response to negative emotional states without physiological hunger [ 1 ] and plays a major role in recurrent weight gain [ 2 ]. The emotional expression hypothesis states that people who eat high-calorie, sweet, and/or high-fat meals experience relief from unpleasant feelings [ 3 ]. Adolescents undergo a substantial period of physical and emotional growth throughout puberty. Given their increased control over what they consume and how they choose to eat it, they can better act on their emotions [ 4 ]. Consequently, adolescence is crucial for the emergence of emotional eating behaviours [ 5 ]. The question of whether this eating pattern raises an adolescent's chance of being overweight or obese is increasingly relevant [ 6 ]. Several studies have supported the link between energy intake, particular food choices, and emotional eating. Emotional eating is associated with snacking [ 7 ], high-fat sweets [ 8 ], fast food [ 9 ], and high-energy foods [ 10 ], such as cereals and tubers [ 11 ], chocolate, ice cream [ 11 ], and added sugar [ 12 ]. In addition, abdominal obesity is strongly correlated with emotional eating [ 13 ], body mass index (BMI) [ 11 ], and body fat percentage [ 14 ]. Over 7 years, a prospective adult cohort study verified a significant correlation between negative emotional eating, elevated BMI, and abdominal circumference [ 15 ]. Studies have also shown no association between emotional eating and BMI [ 9 ]; however, their significance is noteworthy and implies that additional factors may influence the relationship between emotional eating and (abdominal) obesity. An individual's dietary pattern, which integrates combinations of various nutrients, is defined as the quantity, proportion, kind, and mix of foods, drinks, and nutrients consumed during a specific period [ 16 , 17 ]. Emotional eating is associated with unhealthy eating patterns when people consume copious amounts of delicious, high-energy meals rich in fat and sugar. This trend is observed in both men and women [ 2 ]. Furthermore, another study found that while vegetarian patterns are linked to a reduced risk of depression in Chinese teenagers, modern and snack-based aquatic food habits are associated with an increased risk of depression [ 18 ]. According to another study, adults with emotional eating disorders and abdominal obesity have a greater inclination for fast food and snacking [ 13 ]. A prospective study in an adolescent population showed that a dietary pattern consisting of foods high in energy density, fat, sugar, and fibre affects adolescents' body mass index Z-scores (BMIZs) over time [ 19 ]. As a result, eating patterns—a collection of regular eating behaviours and preferences—are probably key factors in the relationship between emotional eating and obesity. This indirect association shows that emotional eating habits may increase an individual's risk of obesity by altering eating patterns, which raises the risk of obesity rather than directly causing obesity. Numerous studies have examined the correlations between emotional eating behaviours, eating patterns, and obesity. However, few studies on the adolescent population have analysed whether specific eating patterns mediate the underlying mechanisms between emotional eating and weight status. Consequently, we posited the theoretical model summarised in Fig. 1 and hypothesised the following: (Hypothesis 1) emotional eating would be strongly correlated with obesity, and (Hypothesis 2) eating patterns would mediate the relationship between emotional eating and obesity. The current study aimed to investigate the association between emotional eating and weight status and to explore the ways in which eating habits affect this relationship. Materials and methods Design This cross-sectional study was conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology guidelines and checklist (Appendix S1). Setting and sample A survey was conducted from September 2022 to October 2022 among seventh- and eighth-grade middle school students in Taizhou City, Zhejiang Province, using convenience sampling. Before conducting the formal survey, one class (n = 42) was selected for a pilot survey to test the reliability of the scale. The preliminary results showed that Cronbach's alpha of the EES-CA was 0.891. We distributed 1016 questionnaires, of which 981 were recovered. According to the nano-exclusion criteria (see Supplementary Information 1), 862 valid questionnaires were finally included after the exclusion of invalid questionnaires. The rate of valid questionnaire completion was 84.8%. The study protocol was approved by the Ethics Committee of Taizhou Hospital of Zhejiang Province (approval no. K20220932). All participants and their guardians provided written informed consent prior to the study. Study instruments Demographic data included sex, grade, age, height, weight, waist circumference, residence, only child, type of family, living conditions, monthly family income, father's and mother's educational background, number of exercises, amount of exercise time, screen time, and sleep time. Weight status indicators included height, weight, and waist circumference. Uniformly trained nurses measured the height, weight, and waist circumference of students using standardised methods. Participants were instructed to wear minimal clothing, remove their shoes, and stand straight with their heels together and their heels, sacrum, and scapula in contact with a height scale, resulting in a height reading accurate to 0.1 cm and a weight reading accurate to 0.1 kg. After one exhalation with normal breathing, the waist circumference was measured using a fiberglass tape measure at a point halfway between the ilium and lower ribs (the 10th rib) [ 20 ]. The BMIZ was calculated using the World Health Organization (WHO) Anthro software (5–19 years old) [ 21 ]. The diagnosis of overweight and obesity was categorised with reference to WHO criteria [ 22 ]: BMIZ ≤ 1 was considered as the normal group; 1 2 identified the obese group. The waist/height ratio was calculated. Abdominal obesity was classified as waist-to-height ratio (WHtR) ≥ 0.46 for girls and WHtR ≥ 0.48 for males, as per the "Prevention and Control of Metabolic Syndrome in Chinese Children" criteria [ 23 ]. Dietary patterns were assessed using a previously studied Food Frequency Questionnaire (FFQ) [ 18 ], which was adapted from the Chinese version of the Adolescent FFQ [ 24 ] and intended to gauge teenagers' eating patterns over the previous 3 months. Based on similarities in nutritional content and cooking techniques, 13 preset categories were created for single meals from the FFQ (Table 1 ). Students were asked how frequently, how many times in a given time frame, and how many portions at each sitting they would consume of each food type. The frequency of eating was categorised as follows: 7, daily; 1, weekly; 0.25, monthly; and 0, annually. The students selected the number of servings they ate each day, week, month, and year, which was based on how frequently they ate the food type. Considering the difficulty of the students' cognitive ability to recognise the number of food portions and understand the concept of average intake. For this study, each portion of each food item was standardised, and colour pictures were made using the same food containers as a reference. Students were then asked to choose the average number of servings based on these pictures. The following formula was used to determine the average number of servings per day for each food group: frequency of eating × number of times eaten × number of servings/7 = total number of servings per day. Table 1 Food grouping used in dietary pattern analysis Food Groups Food Items Rice flour Rice, buns, noodles, pancakes, bread Livestock meat Chicken and duck, pork, beef and lamb Eggs Eggs, duck eggs Legumes Soybean milk, soybean skin, tofu, dried beans Aquatic products Fish, shrimp, crab, squid Dairy products Plain milk, yogurt, cheese Non-starchy vegetables Spinach, Chinese cabbage, mini Chinese cabbage, beans, tomatoes, carrots Root vegetables Potatoes, lotus root Bacteria and algae Needle mushrooms, mushrooms and seaweed Nuts Melon seeds, badam, almonds, cashews Rough food Oats, maize, sweet potato Fruit Apples, oranges, pears, blueberries, dragon fruit Snacks Instant noodles, sweets, fried snacks Emotional eating was assessed using EES-CA. The scale was revised by Kraft et al. [ 25 ] and translated into Chinese by Chen et al. [ 26 ] in 2013. The scale is a self-report scale for assessing children and adolescents aged 11–18 years old, including three dimensions of depression, anger/rage, and anxiety, with a total of 18 entries, scored on a 5-point Likert scale (i.e. 1 = not at all, 2 = somewhat, 3 = fairly, 4 = strongly, 5 = very strongly); the impulse to spend in the face of negativity increases with a higher overall score. Cronbach's α for this scale was 0.936. Data analysis Data were analysed using SPSS Statistics for Windows (version 27.0; IBM Corp., Armonk, NY, USA) and PROCESS macros. Statistical significance was set at p < 0.05. Descriptive statistics were analysed to present the demographic information of the participants and their parents. Univariate analyses were performed using the independent samples t-test, one-way analysis of variance, or the Mann–Whitney U-test/Kruskal–Wallis H-test, depending on the sample distribution. Principal component analysis was used to determine participants’ dietary patterns. Prior to the adoption of this statistical technique, the feasibility of multivariate analysis using these variables was assessed using the Bartlett sphericity test and Kaiser–Meyer–Olkin (KMO) analysis. Because the results of the KMO analysis (0.70) and Bartlett's test of sphericity (p < 0.001) were satisfactory, multivariate analysis was conducted [ 27 ]. Common factors were extracted based on the principle of eigenvalues greater than one. Loading factors were obtained from the component matrix, and factor loadings between each food category that were 0.3 or higher (positive or negative) were deemed significant and were retained in the model [ 28 ]. The dietary patterns of the groups were identified using entries with high factor coefficients. Pearson’s or Spearman’s correlation analysis was used to investigate the correlation among emotional eating, eating patterns, and weight status. Correlation coefficient values 0.7 [ 29 ]. Hayes developed the SPSS macro program PROCESS [ 30 ] to mediate and moderate analyses. Variables with p < 0.1 in univariate analysis were chosen and added to the model as covariates. Model 4 in the SPSS macro program PROCESS was used to test whether eating patterns mediated the relationship between emotional eating (independent variable) and weight (dependent variable). Bootstrapping of 5000 samples was performed. Percentile bootstrapping was used to calculate the mediating effect, and indirect effects were considered significant when the 95% bootstrap confidence interval (95% CI) was not zero [ 30 ]. Results Demographic information In total, 862 participants, including 482 (55.9%) boys and 380 (44.1%) girls, with a mean age of 13.11 ± 0.70 years, participated in this study (Table 2 ). For this sample, BMIZ was 0.32 ± 1.28, and WHtR was 0.42 (0.39, 0.47). The participant recruitment and retention procedures are illustrated in Fig. 2 . Table 2 Demographic information of participants (N = 862) Item Number (%)/ mean ± Sd OR median (IQR) / range adolescent Sex Boy 482 (55.9) Girl 380 (44.1) Grade level Grade 7 462 (53.6) Grade 8 400 (46.4) Age (y) 13.11 ± 0.70 BMIZ 0.32 ± 1.28 WHtR 0.42 (0.39, 0.47) Residential Yes 220 (25.5) No 642 (74.5) The only child Yes 134 (15.5) No 728 (84.5) Place of residence City 450 (52.2) Rural 412 (47.8) Type of family Two-parent families 707 (82.0) Single parent families 120 (13.9) Reorganized families 35 (4.1) Living condition Living with parents 462 (53.6) Living with parents and grandparents 126 (14.6) Living with relatives 274 (31.8) Number of exercises < 3 514 (59.6) ≥ 3 348 (40.4) Exercise time < 60 min 796 (92.3) ≥ 60 min 66 (7.7) Screen time (h) < 2 432 (50.1) ≥ 2 430 (49.9) Sleep time (h) < 8 180 (20.9) ≥ 8 682 (79.1) Parents Monthly family income (CNY) < 5,000 405 (47.0) 5,000–9,999 341 (39.6) ≥ 10,000 116 (13.4) Education of the father Primary school and below 135 (15.7) Lower secondary 536 (62.2) High School 168 (19.5) College and above 23 (2.6) Education of the mother Primary school and below 177 (20.5) Lower secondary 483 (56.0) High School 173 (20.1) College and above 29 (3.4) Note: BMIZ, body mass index Z score; WHtR, waist-to-height ratio; CNY, Chinese Yuan. Further demographic information was subjected to the Mann–Whitney U test and Kruskal–Wallis H test to identify factors that may influence the BMIZ/WHtR. The results of this analysis are presented in Table 3 . Sex, age, type of family, screen time, and education of the father were the influencing factors of BMIZ. Age, screen time, and education of the father were influencing factors of WHtR. Table 3 Influencing factors of BMIZ/WHtR (N = 862) Item BMIZ t/F p WHtR Z/H p adolescent Sex 1.808 0.071 -0.955 0.339 Boy 0.39 ± 1.37 0.42 (0.39, 0.48) Girl 0.24 ± 1.14 0.42 (0.40, 0.47) Grade level 0.042 0.967 -0.091 0.928 Grade 7 0.33 ± 1.29 0.42 (0.39, 0.48) Grade 8 0.32 ± 1.27 0.42 (0.40, 0.47) Age (y) 5.449 0.004 9.970 0.007 12 0.61 ± 1.40 0.44 (0.40, 0.50) 13 0.28 ± 1.28 0.42 (0.39, 0.47) 14 0.22 ± 1.17 0.42 (0.39, 0.46) Residential 0.908 0.364 -0.390 0.697 Yes 0.39 ± 1.24 0.42 (0.40, 0.47) No 0.30 ± 1.29 0.42 (0.39, 0.48) The only child 0.411 0.682 -0.241 0.809 Yes 0.37 ± 1.46 0.42 (0.39–0.49) No 0.32 ± 1.24 0.42 (0.40–0.47) Place of residence 0.507 0.613 -0.722 0.470 City 0.35 ± 1.26 0.42 (0.40–0.48) Rural 0.30 ± 1.30 0.42 (0.39–0.47) Type of family 2.998 0.050 2.393 0.302 Two-parent families 0.37 ± 1.28 0.42 (0.40, 0.48) Single parent families 0.14 ± 1.24 0.42 (0.39, 0.46) Reorganized families -0.01 ± 1.35 0.41 (0.39, 0.46) Living condition 1.132 0.323 3.82 0.148 Living with parents 0.26 ± 1.30 0.42 (0.39–0.47) Living with parents and grandparents 0.39 ± 1.23 0.43 (0.40, 0.47) Living with relatives 0.40 ± 1.26 0.43 (0.40, 0.48) Number of exercises 1.272 0.204 -1.445 0.149 <3 0.37 ± 1.25 0.42 (0.40, 0.48) ≥3 0.26 ± 1.31 0.42 (0.39, 0.47) Exercise time 0.353 0.724 -0.006 0.995 <60 min 0.33 ± 1.27 0.42 (0.39, 0.47) ≥60 min 0.27 ± 1.42 0.42 (0.40, 0.48) Screen time (h) -2.235 0.026 -2.266 0.023 <2 0.23 ± 1.24 0.42 (0.39–0.47) ≥2 0.42 ± 1.30 0.43 (0.40–0.48) Sleep time (h) 0.879 0.380 -0.921 0.357 <8 0.39 ± 1.15 0.43 (0.40–0.48) ≥8 0.31 ± 1.31 0.42 (0.39–0.47) Parents Monthly family income(CNY) 0.997 0.369 1.114 0.573 <5,000 0.26 ± 1.30 0.42 (0.39, 0.47) 5,000–9,999 0.40 ± 1.20 0.43 (0.40, 0.48) ≥10,000 0.33 ± 1.44 0.42 (0.39, 0.48) Education of the father 2.900 0.034 7.307 0.063 Primary school and below 0.46 ± 1.22 0.43 (0.40, 0.47) Lower secondary 0.31 ± 1.29 0.42 (0.39, 0.48) High School 0.35 ± 1.28 0.42 (0.40, 0.47) College and above -0.38 ± 1.12 0.40 (0.38, 0.43) Education of the mother 1.960 0.118 3.243 0.356 Primary school and below 0.39 ± 1.22 0.43 (0.40, 0.47) Lower secondary 0.33 ± 1.29 0.42 (0.39, 0.48) High School 0.34 ± 1.27 0.42 (0.39, 0.48) College and above -0.23 ± 1.45 0.40 (0.39, 0.46) Note: BMIZ, body mass index Z score; WHtR, waist-to-height ratio; CNY, Chinese Yuan. Analysis of adolescent dietary patterns Dietary patterns in this study were determined using principal component analysis. To test the suitability of the data for principal component analysis, the KMO test and Bartlett's test of sphericity were performed, with KMO = 0.872 and p < 0.001, indicating that the data supported the principal component analysis. Two public factors were extracted based on the principle that eigenvalues are greater than 1. The component matrices for each dietary pattern are presented in Table 4 . Two dietary patterns were identified in this study. Dietary pattern 1, the traditional dietary pattern, was defined as a diet containing high-protein foods, such as eggs, beans, dairy products, aquatic items, root vegetables, bacteria and algae, nuts, and coarse cereals. Dietary pattern 2, the modern dietary pattern, was defined as consisting of high-load staple meals, animal and poultry meat, snacks, and high vegetable load. These two dietary patterns explained 45.62% of the food group differences. The dietary pattern characteristics of the normal-weight and overweight/obese groups are shown in Fig. 3 . Table 4 Factor loadings for two dietary patterns derived from principal component analysis Food Dietary pattern 1 Dietary pattern 2 Rice flour 0.032 0.688 Livestock meat -0.010 0.723 Eggs 0.507 0.004 Legumes 0.747 -0.020 Aquatic products 0.744 0.015 Dairy products 0.600 -0.025 Non-starchy vegetables -0.036 -0.618 Root vegetables 0.622 0.001 Bacteria and algae 0.758 -0.073 Nuts 0.629 -0.041 Rough food 0.770 -0.019 Fruit 0.580 0.145 Snacks -0.013 0.711 Note: The bold value indicates that the item is one of the representative foods under the corresponding dietary pattern. Correlations between study variables The Spearman correlation coefficients between the main study variables are shown in Table 5 − 1. Emotional eating was strongly correlated with BMIZ (r = 0.754, p < 0.001) and moderately positively correlated with eating pattern 2 (r = 0.676, p 0.05). BMIZ was significantly and strongly correlated with Dietary Pattern 2 (r = 0.800, p 0.05). Table 5 − 1 Correlations between the main study variables (N = 862) EES-CA Dietary pattern 1 Dietary pattern 2 BMIZ EES-CA 1 Dietary pattern 1 0.018 1 Dietary pattern 2 0.676** 0.090** 1 BMIZ 0.754** 0.051 0.800** 1 Note: ***, p < 0.01; BMIZ, body mass index Z score; EES-CA, Emotion Eating Scale for Chinese Adolescents Table 5 − 2 Correlations between the main study variables (N = 862) EES-CA Dietary pattern 1 Dietary pattern 2 WHtR EES-CA 1 Dietary pattern 1 0.018 1 Dietary pattern 2 0.676** 0.090** 1 WHtR 0.623** 0.059 0.671** 1 Note: ***, p < 0.01; BMIZ, body mass index Z score; EES-CA, Emotion Eating Scale for Chinese Adolescents As shown in Table 5 − 2, WHtR was somewhat positively correlated with emotional eating (r = 0.623, p < 0.001). The WHtR and Dietary Pattern 2 showed a moderate and significant correlation (r = 0.671, p 0.05). Overall, the results of the correlation analysis indicated that the pairwise combinations of emotional eating, Dietary pattern 2, and BMIZ/WHtR variables were significant and indicated a correlation between the three variables. Multiple hierarchical linear regression models A plug-in for Process 4.1 in SPSS was used to test the hypotheses. Adolescents’ sex, age, family type, screen time, and father's education level were associated with the BMIZ, while adolescents’ age, screen time, and father's education level were associated with WHtR (Table 3 ). We considered the potential confounding effects of demographic variables and included them as covariates to test for associations among emotional eating habits, eating patterns, and weight status. In addition, eating patterns were tested as potential mediators of the association between emotional eating and weight. Subsequent studies showed that the relationship between emotional eating and the BMIZ/WHtR was significantly influenced by eating patterns. Dietary pattern 2 seemed to be a major mediating factor among the eating patterns examined in this study. We found that adolescents who ate more emotionally were more prone to developing obesogenic eating practices. The substantial indirect effects of 0.446 for BMIZ and 0.020 for WHtR (both statistically significant at p < 0.001) indicate that this pattern later impacted their weight status. Dietary pattern 1, however, had no discernible impact (Fig. 4 ). Discussion In the present study, we identified two dietary patterns: traditional and modern. Modern dietary patterns were significantly and positively associated with the BMIZ/WHtR (Hypothesis 1) and were a mediator between emotional eating and the BMIZ/WHtR (Hypothesis 2). This suggests that weight status can be influenced by a modern dietary pattern characterised by high loads of snacks, rice flour, livestock meat, and non-starchy vegetables. These characteristics may be key targets for interventions aimed at preventing (abdominal) obesity. To the best of our knowledge, limited research has been conducted on teenage populations that characterise diets as eating patterns or show a connection between certain eating patterns and emotional eating [ 9 , 10 , 31 , 32 ]. These studies have demonstrated a favourable correlation between eating patterns, including meals high in fat or sugar, and emotional eating. In contrast, this study generated distinct eating patterns for different diets using principal component analysis. Consequently, highly appealing, energy-dense eating behaviours are positively associated with emotional eating [ 33 ]. Super-palatable, high-energy, and high-fat meals (rich in sugar and fat) are a hallmark of highly palatable, energy-dense eating behaviours [ 33 ]. These meals mostly consist of staples, such as rice, buns, noodles, pancakes, bread, and animal and poultry meat, including chicken, duck, hog, beef, and lamb, as well as snacks, such as instant noodles, chocolate, cakes, fried foods, and sugary drinks. In line with previous studies, this study showed a positive correlation between emotional eating and BMIZ levels, which can lead to weight gain [ 34 , 35 ]. Adolescence is a unique stage of physical and mental development for teenagers. During this time, they acquire long-term food-related habits and experience an increase in unhealthy eating habits, a loss of parental supervision, and an increase in independence [ 14 ]. Teenagers may have more opportunities to control their emotions and eating habits when parental supervision decreases. According to self-regulation theory, emotional eating may be caused by problems with emotion management, according to self-regulation theory [ 1 ]. Emotional episodes sometimes involve the consumption of significant quantities of sugary, calorie-dense, and/or high-fat meals [ 36 ]. Research has indicated that individuals with elevated emotional eating scores typically experience heightened appetites during depressive states, are more likely to overindulge, and exhibit specific desires for high-energy and sweet foods, which contribute to the accumulation of excess calories and the potential for obesity [ 37 ]. These beautiful meals deliver instant gratification and delightful sensations, which can help divert attention from unpleasant feelings. Moreover, both acute and long-term stress have an impact on reward/motivation and inhibition-control pathways and are risk factors for the emergence of emotional eating, as well as providing stimulation of the hypothalamic–pituitary–adrenal axis [ 38 ]. Following the establishment of this route, those who are triggered by food cues engage in the food reward system, which raises their desire to eat and results in better awareness of food signals. Therefore, in the future, we can conduct interdisciplinary studies between dietary, psychological, and brain sciences, as well as teenage obesity. In addition, several stress-related mental issues, including anxiety, depression, and sleep difficulties, have been brought about by the coronavirus disease 2019 (COVID-19) pandemic. Emotional eating has become common as a coping mechanism for people's feelings. When coupled with a decline in physical activity, it leads to an increase in the incidence of overweight and obesity [ 39 ]. Following the outbreak, there was a 25.2% worldwide detection rate of melancholic mood in children and adolescents, with a double incidence of 43.7% among Chinese secondary school students [ 40 ]. Anxiety was the cause in 31.9% of the cases [ 41 ]. According to the current research, teenage emotion management may play a significant role in the pathways leading to obesity risk. Adolescents who struggle with emotional control may be more likely to overindulge in emotional eating, which puts them at risk of obesity [ 14 ]. Therefore, future therapies aimed at preventing teenage obesity should focus on mood management and emotional eating behaviours. Furthermore, following such significant public health incidents, families, schools, and hospitals should pay close attention to the mental health issues teenagers face and quickly establish coping mechanisms. In contrast to other research studies [ 35 , 42 ], we also discovered a relationship between WHtR and emotional eating. This finding implies that teenagers' WHtR is more relevant when they have high emotional eating scores. Although BMI is a commonly used indicator of obesity, it does not differentiate between lean and fat mass, nor does it identify the location of adiposity [ 43 ]. Conversely, the WHtR is a significant marker for centripetal obesity, which is a stronger predictor of the risk of conditions, including diabetes and cardiovascular disease [ 44 ]. Therefore, considering both body fat distribution and BMI in future studies is imperative. Additionally, the current study discovered a substantial and favourable correlation between the BMIZ/WHtR and contemporary dietary patterns. High and low loads of vegetables, snack items, animal and poultry meats, and staple foods typified the study's dietary patterns. Evaluating dietary patterns is intriguing because they represent the entire diet or the assortment of foods that people usually eat as opposed to concentrating on specific nutrients or foods [ 45 ]. Adolescents who consume more processed meats, fried potatoes, refined cereals, and added sugars and more whole grains than fruits, vegetables, whole grains, and low-fat dairy products have been shown to have higher body and fat mass indices [ 17 ], which is generally consistent with the findings of this study; moreover, consuming many ultra-processed meals high in fat, salt, and refined carbohydrates has been linked to a higher risk of cardiometabolic changes in teenagers [ 46 ]. Additionally, teenage obesity in outpatient clinics is associated with an excessive consumption of meat and sugary foods [ 47 ]. Consequently, because it captures the intricate relationships between various food intakes more accurately, studying and evaluating the dietary patterns of particular communities can offer thorough insights into the impact of diet on health. Furthermore, investigating the relationship between these eating patterns and obesity will eventually offer a scientific foundation for multimodal health education on childhood obesity that is centred on family, school, and society, as well as nutritional treatments. Consequently, because it captures the intricate relationships between various food intakes more accurately, studying and evaluating the dietary patterns of particular communities can offer thorough insights into the impact of diet on health. Investigating the link between these eating patterns and obesity will provide a scientific foundation for multimodal health education on childhood obesity and nutritional treatments shared by families, schools, and society. Additionally, the association between emotional eating and BMIZ/WHtR is partially mediated by contemporary eating practices. According to the reinforcement theory, people choose to eat to reduce their negative emotions. This leads to an increase in the amount of food consumed during negative emotions, which solidifies into specific eating patterns over time. This theory is supported by research [ 48 ]. Moreover, earlier research revealed that reactive eating habits in children and teenagers buffer the link between food addiction and BMIZ [ 49 ]. However, emotional eating was documented in 46% of teenagers [ 50 ]. Over time, good energy balance is facilitated by the eating habits of emotional eaters who tend to select high-carbohydrate, high-fat, and sugary meals and snacks more often to ease negative feelings [ 7 ]. Therefore, it is not possible to gain a thorough understanding of complicated eating behaviours by concentrating on only one area. Calorie-restricted diets, as well as emotion-regulation strategies and the rationality of meal pairings, should be the main focus of treatment and care for obese children who exhibit high levels of emotional expression. To help children learn more about emotional eating, we can investigate positive thinking-based therapies in the future, such as positive thinking eating exercises [ 51 ], positive thinking meditation training [ 52 ], and positive thinking-based emotional eating awareness training [ 53 ]. Furthermore, nutritional health education programs may be established in schools and hospitals, aiding teenagers in the development of healthy eating habits, helping them make informed food choices, and lowering the prevalence of overweight and obesity. This study has several limitations. First, the cross-sectional design can only account for correlation rather than causation, which is more useful when guiding interventions. Second, Hawthorne effects are inevitable based on convenience sampling techniques, in addition to selection bias introduced by the study population [ 54 ]. This limitation may be addressed in future studies using randomised sampling techniques. Third, this study was limited to a single Taizhou school, which may have limited the extent to which the results can be applied. To obtain more representative results, multicentre studies are necessary. Fourth, a self-reported questionnaire was used to evaluate eating behaviours, which may have obscured the data gathered. To increase the reliability of these findings, reliable objective measurements should be used in future studies. Finally, dietary pattern analysis was limited to broad food groups, complicating the identification of foods that increase risk. In conclusion, teenagers with high emotional eating scores tend to follow dietary patterns linked to obesity, including the consumption of snacks, carbs, fats, and sugars. This highlights problematic areas for weight loss efforts, such as emotional eating patterns and the traits that accompany them. This study also emphasises the need for policies that promote healthy food and lifestyle choices in teenagers and address obesity prevention and management. Declarations Acknowledgments This research was supported by the Enze Medical Centre Scientific Research Fund (grant number 22EZC12) and Taizhou Municipal Science and Technology Bureau of Zhejiang Province (grant numbers 24ywb19 and 24ywb21) Author contributions DW and MXZ conceived and designed the study. DW drafted the manuscript. DW, HYY, and HHS collected the data and controlled their quality. DW and HLF conducted the data analyses. TTH, LZW, and MXZ revised the manuscript. All authors contributed to publishing the final manuscript. All authors reviewed and approved the final manuscript. Data availability statement The data that support the findings of this study are available from the corresponding author upon reasonable request. Ethics approval and consent to participate The study protocol was approved by the Ethics Committee of Taizhou Hospital of Zhejiang Province, China (approval no. K20220932) and was conducted in accordance with the guidelines of the institutional ethics committee and the principles outlined in the Declaration of Helsinki. Informed consent was obtained from all participants. All participants and their guardians provided written informed consent prior to the study. The integrity of all participant information was strictly maintained, and each participant had the right to withdraw from the study at any time. Consent for publication Not applicable. References van Strien T. Causes of emotional eating and matched treatment of obesity. Curr Diab Rep. 2018;18(6):35. doi: 10.1007/s11892-018-1000-x , PMID 29696418. Dakanalis A, Mentzelou M, Papadopoulou SK, Papandreou D, Spanoudaki M, Vasios GK, et al. The association of emotional eating with overweight/obesity, depression, anxiety/stress, and dietary patterns: a review of the current clinical evidence. Nutrients. 2023;15(5):1173. doi: 10.3390/nu15051173 , PMID 36904172. Kaplan HI, Kaplan HS. The psychosomatic concept of obesity. J Nerv Ment Dis. 1957;125(2):181–201. doi: 10.1097/00005053-195704000-00004 , PMID 13481715. Muha J, Schumacher A, Campisi SC, Korczak DJ. Depression and emotional eating in children and adolescents: A systematic review and meta-analysis. Appetite. 2024;200:107511. doi: 10.1016/j.appet.2024.107511 , PMID 38788931. Braet C, Claus L, Goossens L, Moens E, Van Vlierberghe L, Soetens B. Differences in eating style between overweight and normal-weight youngsters. J Health Psychol. 2008;13(6):733–743. doi: 10.1177/1359105308093850, PMID 18697886. Limbers CA, Summers E. Emotional eating and weight status in adolescents: a systematic review. Int J Environ Res Public Health. 2021;18(3):991. doi: 10.3390/ijerph18030991 , PMID 33498603. Braden A, Musher-Eizenman D, Watford T, Emley E. Eating when depressed, anxious, bored, or happy: are emotional eating types associated with unique psychological and physical health correlates? Appetite. 2018;125:410–417. doi: 10.1016/j.appet.2018.02.022 , PMID 29476800. Camilleri GM, Méjean C, Kesse-Guyot E, Andreeva VA, Bellisle F, Hercberg S, et al. The associations between emotional eating and consumption of energy-dense snack foods are modified by sex and depressive symptomatology. J Nutr. 2014;144(8):1264–1273. doi: 10.3945/jn.114.193177 , PMID 24850627. Jalo E, Konttinen H, Vepsäläinen H, Chaput JP, Hu G, Maher C, et al. Emotional eating, health behaviours, and obesity in children: a 12-country cross-sectional study. Nutrients. 2019;11(2):351. doi: 10.3390/nu11020351 , PMID 30736444. Nguyen-Michel ST, Unger JB, Spruijt-Metz D. Dietary correlates of emotional eating in adolescence. Appetite. 2007;49(2):494–499. doi: 10.1016/j.appet.2007.03.005 , PMID 17466408. Chew HS, Lau ST, Lau Y. Weight-loss interventions for improving emotional eating among adults with high body mass index: a systematic review with meta-analysis and meta-regression. Eur Eat Disord Rev. 2022;30(4):304–327. doi: 10.1002/erv.2906 , PMID 35460323. Ruiz LD, Zuelch ML, Dimitratos SM, Scherr RE. Adolescent obesity: diet quality, psychosocial health, and cardiometabolic risk factors. Nutrients. 2019;12(1):43. doi: 10.3390/nu12010043 , PMID 31877943. Betancourt-Núñez A, Torres-Castillo N, Martínez-López E, De Loera-Rodríguez CO, Durán-Barajas E, Márquez-Sandoval F, et al. Emotional eating and dietary patterns: reflecting food choices in people with and without abdominal obesity. Nutrients. 2022;14(7):1371. doi: 10.3390/nu14071371 , PMID 35405983. Shriver LH, Dollar JM, Lawless M, Calkins SD, Keane SP, Shanahan L, et al. Longitudinal associations between emotion regulation and adiposity in late adolescence: indirect effects through eating behaviors. Nutrients. 2019;11(3):517. doi: 10.3390/nu11030517 , PMID 30823405. Konttinen H, van Strien T, Männistö S, Jousilahti P, Haukkala A. Depression, emotional eating and long-term weight changes: a population-based prospective study. Int J Behav Nutr Phys Act. 2019;16(1):28. doi: 10.1186/s12966-019-0791-8 , PMID 30894189. Liberali R, Kupek E, Assis MA. Dietary patterns and childhood obesity risk: a systematic review. Child Obes. 2020;16(2):70–85. doi: 10.1089/chi.2019.0059 , PMID 31742427. Boushey C, Ard J, Bazzano L, Heymsfield S, Mayer-Davis E, Sabaté J, et al. Dietary patterns and growth, size, body composition, and/or risk of overweight or obesity: a systematic review. Alexandria (VA): USDA Nutrition Evidence Systematic Review; 2020. PMID: 35129906. Qian K, Wang D, Sun Y, Ye X, Wang D, Xu H. Association of dietary patterns with depressive symptoms in Chinese adolescents: a cross-sectional study. Front Nutr. 2023;10:1180858. doi: 10.3389/fnut.2023.1180858 , PMID 37497054. Arruda Neta AC, Farias Junior JC, Lima Ferreira FE, Marchioni DM. Prospective association between dietary patterns and BMI Z-score in Brazilian adolescents. Public Health Nutr. 2021;24(13):4230–4237. doi: 10.1017/S1368980021000252, PMID 33472719. Nishida C, Ko GT, Kumanyika S. Body fat distribution and noncommunicable diseases in populations: overview of the 2008 WHO Expert Consultation on Waist Circumference and Waist-Hip Ratio. Eur J Clin Nutr. 2010;64(1):2–5. doi: 10.1038/ejcn.2009.139 , PMID 19935820. WHO. Anthro Survey Analyser; n.d. [cited Dec 20 2023] Available from: https://worldhealthorg.shinyapps.io/anthro/ . Lohman TG, Roche AF, Martorell R. Anthropometric standardization reference manual. Champaign, IL: Human Kinetics Publishers; 1988. Liang L, Fu JF, Du JB. Significance of exploring the definition of metabolic syndrome in Chinese children and adolescents. Zhonghua Er Ke Za Zhi. 2012;50(6):401–404. PMID 22931932. Wang WP, Cheng H, Zhao XY, et al. Study on the reliability and validity of the food frequency questionnaire for children and adolescents in Beijing. Chin J Child Health. 2016;24:8–11. Tanofsky-Kraff M, Theim KR, Yanovski SZ, Bassett AM, Burns NP, Ranzenhofer LM, et al. Validation of the emotional eating scale adapted for use in children and adolescents (EES-C). Int J Eat Disord. 2007;40(3):232–240. doi: 10.1002/eat.20362 , PMID 17262813. Gui C, Tai SC, Feng JH, et al. Revision of the emotional eating scale in Chinese adolescents. Chin J Clin Psychol. 2013;21:572–575. Ben Salem K, Ben Abdelaziz A. Principal component analysis (PCA). Tunis Med. 2021;99(4):383–389. PMID 35244921. Sakaluk JK, Short SD. A Methodological review of exploratory factor analysis in sexuality research: used practices, best practices, and data analysis resources. J Sex Res. 2017;54(1):1–9. doi: 10.1080/00224499.2015.1137538, PMID 26886499. Akoglu H. User’s guide to correlation coefficients. Turk J Emerg Med. 2018;18(3):91–93. doi: 10.1016/j.tjem.2018.08.001, PMID 30191186. Igartua JJ, Hayes AF. Mediation, moderation, and conditional process analysis: concepts, computations, and some common confusions. Span J Psychol. 2021;24:e49. doi: 10.1017/SJP.2021.46 , PMID 35923144. Di Renzo L, Gualtieri P, Cinelli G, Bigioni G, Soldati L, Attinà A, et al. Psychological aspects and eating habits during COVID-19 home confinement: results of EHLC-COVID-19 Italian online survey. Nutrients. 2020;12(7):2152. doi: 10.3390/nu12072152 , PMID 32707724. Sosa-Cordobés E, García-Padilla FM, Ortega-Galán ÁM, Sánchez-Alcón M, Garrido-Fernández A, Ramos-Pichardo JD. Psychometric properties of the emotional eater questionnaire in university students. Int J Environ Res Public Health. 2022;19(17):10965. doi: 10.3390/ijerph191710965 , PMID 36078680. Fuente González CE, Chávez-Servín JL, de la Torre-Carbot K, Ronquillo González D, Aguilera Barreiro ML, Ojeda Navarro LR. Relationship between emotional eating, consumption of hyperpalatable energy-dense foods, and indicators of nutritional status: a systematic review. J Obes. 2022;2022:4243868. doi: 10.1155/2022/4243868 , PMID 35634585. WHO. Obesidad Y sobrepeso. Geneva, Switzerland: World Health Organization; 2021. Available from: https://www.who.int/es/news-room/fact-sheets/detail/obesity-and-overweight . Farhangi MA. Night Eating Syndrome and its relationship with emotional eating, sleep quality and nutritional status among adolescents’ boys. Community Ment Health J. 2019;55(8):1411–1418. doi: 10.1007/s10597-019-00395-8 , PMID 30879161. van Strien T, Cebolla A, Etchemendy E, Gutiérrez-Maldonado J, Ferrer-García M, Botella C, et al. Emotional eating and food intake after sadness and joy. Appetite. 2013;66:20–25. doi: 10.1016/j.appet.2013.02.016, PMID 23470231. Penaforte FR, Minelli MC, Anastácio LR, Japur CC. Anxiety symptoms and emotional eating are independently associated with sweet craving in young adults. Psychiatry Res. 2019;271:715–720. doi: 10.1016/j.psychres.2018.11.070, PMID 30791346. Maier SU, Makwana AB, Hare TA. Acute stress impairs self-control in goal-directed choice by altering multiple functional connections within the brain’s decision circuits. Neuron. 2015;87(3):621–631. doi: 10.1016/j.neuron.2015.07.005, PMID 26247866. Burnatowska E, Surma S, Olszanecka-Glinianowicz M. Relationship between mental health and emotional eating during the COVID-19 pandemic: a systematic review. Nutrients. 2022;14(19):3989. doi: 10.3390/nu14193989 , PMID 36235642. Racine N, McArthur BA, Cooke JE, Eirich R, Zhu J, Madigan S. Global prevalence of depressive and anxiety symptoms in children and adolescents during COVID-19: a meta-analysis. JAMA Pediatr. 2021;175(11):1142–1150. doi: 10.1001/jamapediatrics.2021.2482 , PMID 34369987. Wu T, Jia X, Shi H, Niu J, Yin X, Xie J, et al. Prevalence of mental health problems during the COVID-19 pandemic: A systematic review and meta-analysis. J Affect Disord. 2021;281:91–98. doi: 10.1016/j.jad.2020.11.117, PMID 33310451. Grajek M, Krupa-Kotara K, Białek-Dratwa A, Staśkiewicz W, Rozmiarek M, Misterska E, et al. Prevalence of emotional eating in groups of students with varied diets and physical activity in Poland. Nutrients. 2022;14(16):3289. doi: 10.3390/nu14163289 , PMID 36014794. Nuttall FQ. Body mass index: obesity, BMI, and health: a critical review. Nutr Today. 2015;50(3):117–128. doi: 10.1097/NT.0000000000000092, PMID 27340299. Browning LM, Hsieh SD, Ashwell M. A systematic review of waist-to-height ratio as a screening tool for the prediction of cardiovascular disease and diabetes: 0·5 could be a suitable global boundary value. Nutr Res Rev. 2010;23(2):247–269. doi: 10.1017/S0954422410000144, PMID 20819243. Hu FB. Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol. 2002;13(1):3–9. doi: 10.1097/00041433-200202000-00002 , PMID 11790957. Rocha NP, Milagres LC, Longo GZ, Ribeiro AQ, Novaes JF. Association between dietary pattern and cardiometabolic risk in children and adolescents: a systematic review. J Pediatr (Rio J). 2017;93(3):214–222. doi: 10.1016/j.jped.2017.01.002, PMID 28238682. Brauchmann J, Bau AM, Mensink GB, Richter A, Ernert A, Keller T, et al. Dietary patterns in adolescent obesity as predictors of long-term success following an intensive inpatient lifestyle programme. Int J Environ Res Public Health. 2022;19(24):16613. doi: 10.3390/ijerph192416613 , PMID 36554494. Becker KD, Fischer S, Smith GT, Miller JD. The influence of negative urgency, attentional bias, and emotional dimensions on palatable food consumption. Appetite. 2016;100:236–243. doi: 10.1016/j.appet.2016.02.019 , PMID 26877214. Wang D, Wang D, Ye X, Chen J, Fu J, Xu H. Food addiction and its impact on weight status in children and adolescents: the mediating role of responsive eating pattern. Pediatr Obes. 2024;19(2):e13090. doi: 10.1111/ijpo.13090 , PMID 38148618. Joseph PL, Gonçalves C, Fleary SA. Psychosocial correlates in patterns of adolescent emotional eating and dietary consumption. PLOS One. 2023;18(5):e0285446. doi: 10.1371/journal.pone.0285446 , PMID 37224099. Hendrickson KL, Rasmussen EB. Mindful eating reduces impulsive food choice in adolescents and adults. Health Psychol. 2017;36(3):226–235. doi: 10.1037/hea0000440 , PMID 27808529. Torske A, Bremer B, Hölzel BK, Maczka A, Koch K. Mindfulness meditation modulates stress-eating and its neural correlates. Sci Rep. 2024;14(1):7294. doi: 10.1038/s41598-024-57687-7 , PMID 38538663. Lattimore P. Mindfulness-based emotional eating awareness training: taking the emotional out of eating. Eat Weight Disord. 2020;25(3):649–657. doi: 10.1007/s40519-019-00667-y , PMID 30859465. Yeh MY, Wu SC, Tung TH. The relation between patient education, patient empowerment and patient satisfaction: a cross-sectional-comparison study. Appl Nurs Res. 2018;39:11–17. doi: 10.1016/j.apnr.2017.10.008 , PMID 29422144. Additional Declarations There is NO conflict of interest to disclose Supplementary Files Supplementaryinformation.docx Supplementary information Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6468108","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":452267573,"identity":"b6fb780b-ba72-48f7-9774-77ead0c39616","order_by":0,"name":"Meixian Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIiWNgGAWjYDACCQhVz8/f//ABVMyAKC0JkjPOMMOUEqnF4EAOmwRRWuRnNz97+DXncJ7BgbPHKj7uqJPTbW/ewPCjYhtOLYxzjpkby25LK5Y83Jd2c+YZNmOzM8cKGHvO3MaphVkiwUxacpsNY9+BA2a3edt4ErfdyDFgZmzDrYVNIv0bUIsEY8OBBLPiv20S9dvuv8GvhUcix0zy4zabxAkHcsyAKg0SzG7w4NciIZFTJs24Lc1YcsaxZMnetgTDbWfSCg7i84v8jPRtkj+3HZbj528++OFnW5282fHDGx/8qMCtBRwEPOgiB/CqBwLGH4RUjIJRMApGwcgGAGkHW8luN6baAAAAAElFTkSuQmCC","orcid":"","institution":"[email protected]","correspondingAuthor":true,"prefix":"","firstName":"Meixian","middleName":"","lastName":"Zhang","suffix":""},{"id":452267574,"identity":"4cfd010d-2015-4db9-b91f-caa8c8934837","order_by":1,"name":"Dan Wang","email":"","orcid":"","institution":"13758628901","correspondingAuthor":false,"prefix":"","firstName":"Dan","middleName":"","lastName":"Wang","suffix":""},{"id":452267575,"identity":"a2e38837-3673-4e40-95eb-58b9451ff735","order_by":2,"name":"Huiyan Yin","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Huiyan","middleName":"","lastName":"Yin","suffix":""},{"id":452267576,"identity":"d383d1ba-69d6-4786-81bf-dbf9719a8f89","order_by":3,"name":"Huanhuan Shi","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Huanhuan","middleName":"","lastName":"Shi","suffix":""},{"id":452267577,"identity":"9d8cc375-c7ba-44e2-b758-51d9feb4830f","order_by":4,"name":"Hailing Fan","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Hailing","middleName":"","lastName":"Fan","suffix":""},{"id":452267578,"identity":"3897bfb6-ada4-4205-9faa-1527d0f6e7f4","order_by":5,"name":"TaoHsin Tung","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"TaoHsin","middleName":"","lastName":"Tung","suffix":""},{"id":452267579,"identity":"bfd5bff2-91e8-4d0d-89d1-1098f66cdf51","order_by":6,"name":"Li-Zhen Wang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Li-Zhen","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-04-17 05:20:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6468108/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6468108/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82289428,"identity":"9e4ab3ca-5740-43ae-8360-c2e6a2eff201","added_by":"auto","created_at":"2025-05-08 17:10:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":7587,"visible":true,"origin":"","legend":"\u003cp\u003eEmotional eating and obesity: a hypothetical theoretical model of the role of dietary patterns. BMIZ, body mass index Z-score.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6468108/v1/9fc6f9b0671f17f6ecbeba17.png"},{"id":82289429,"identity":"f9bfc000-b6ec-40e4-b288-037a1948f07c","added_by":"auto","created_at":"2025-05-08 17:10:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":21756,"visible":true,"origin":"","legend":"\u003cp\u003eParticipant recruitment and retention. BMIZ, body mass index Z-score; WHtR, waist-to-height ratio\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6468108/v1/166cf007e8424ac7a1cc4e79.png"},{"id":82289928,"identity":"c1a2b73f-15fc-4215-8360-318f18e776ce","added_by":"auto","created_at":"2025-05-08 17:18:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":141846,"visible":true,"origin":"","legend":"\u003cp\u003eThe dietary pattern characteristics of adolescents in different weight states\u003c/p\u003e\n\u003cp\u003eNote: BMIZ ≤ 1, normal-weight; BMIZ \u0026gt; 1, adolescents with overweight and obesity\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6468108/v1/58907ab885aa7dbc026ce842.png"},{"id":82289924,"identity":"c8bf1025-abcb-41d6-815c-37c5a9133900","added_by":"auto","created_at":"2025-05-08 17:18:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":22085,"visible":true,"origin":"","legend":"\u003cp\u003eThe correlation between EES-CA, dietary patterns, and weight status\u003c/p\u003e\n\u003cp\u003eNote: In medium analysis, the healthy dietary pattern is encoded as 1, while the adolescents with overweight and obesity dietary pattern is encoded as 2. CI, confidence interval; EES-CA, Emotion Eating Scale for Chinese Adolescents; WHtR, waist-to-height ratio.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6468108/v1/09f0743e778ad0817381e502.png"},{"id":86951100,"identity":"70d006d2-5dc3-4716-912c-6d617a5eefa8","added_by":"auto","created_at":"2025-07-17 14:14:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1312863,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6468108/v1/941cde68-8414-4e2a-bba0-a1de54530b91.pdf"},{"id":82290347,"identity":"c84150ac-0733-4d39-bb74-a3edad92a98e","added_by":"auto","created_at":"2025-05-08 17:26:50","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":33023,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary information\u003c/p\u003e","description":"","filename":"Supplementaryinformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-6468108/v1/18ead4e7c603671ded8d6e62.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose","formattedTitle":"Emotional eating and adolescents body weight: the mediating role of dietary patterns in Taizhou, China","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEmotional eating (EE) is the tendency to consume or increase food intake in response to negative emotional states without physiological hunger [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] and plays a major role in recurrent weight gain [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The emotional expression hypothesis states that people who eat high-calorie, sweet, and/or high-fat meals experience relief from unpleasant feelings [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Adolescents undergo a substantial period of physical and emotional growth throughout puberty. Given their increased control over what they consume and how they choose to eat it, they can better act on their emotions [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Consequently, adolescence is crucial for the emergence of emotional eating behaviours [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The question of whether this eating pattern raises an adolescent's chance of being overweight or obese is increasingly relevant [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral studies have supported the link between energy intake, particular food choices, and emotional eating. Emotional eating is associated with snacking [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], high-fat sweets [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], fast food [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], and high-energy foods [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], such as cereals and tubers [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], chocolate, ice cream [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], and added sugar [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In addition, abdominal obesity is strongly correlated with emotional eating [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], body mass index (BMI) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], and body fat percentage [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Over 7 years, a prospective adult cohort study verified a significant correlation between negative emotional eating, elevated BMI, and abdominal circumference [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Studies have also shown no association between emotional eating and BMI [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]; however, their significance is noteworthy and implies that additional factors may influence the relationship between emotional eating and (abdominal) obesity.\u003c/p\u003e \u003cp\u003eAn individual's dietary pattern, which integrates combinations of various nutrients, is defined as the quantity, proportion, kind, and mix of foods, drinks, and nutrients consumed during a specific period [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Emotional eating is associated with unhealthy eating patterns when people consume copious amounts of delicious, high-energy meals rich in fat and sugar. This trend is observed in both men and women [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Furthermore, another study found that while vegetarian patterns are linked to a reduced risk of depression in Chinese teenagers, modern and snack-based aquatic food habits are associated with an increased risk of depression [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. According to another study, adults with emotional eating disorders and abdominal obesity have a greater inclination for fast food and snacking [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. A prospective study in an adolescent population showed that a dietary pattern consisting of foods high in energy density, fat, sugar, and fibre affects adolescents' body mass index Z-scores (BMIZs) over time [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. As a result, eating patterns\u0026mdash;a collection of regular eating behaviours and preferences\u0026mdash;are probably key factors in the relationship between emotional eating and obesity. This indirect association shows that emotional eating habits may increase an individual's risk of obesity by altering eating patterns, which raises the risk of obesity rather than directly causing obesity.\u003c/p\u003e \u003cp\u003eNumerous studies have examined the correlations between emotional eating behaviours, eating patterns, and obesity. However, few studies on the adolescent population have analysed whether specific eating patterns mediate the underlying mechanisms between emotional eating and weight status.\u003c/p\u003e \u003cp\u003eConsequently, we posited the theoretical model summarised in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and hypothesised the following: (Hypothesis 1) emotional eating would be strongly correlated with obesity, and (Hypothesis 2) eating patterns would mediate the relationship between emotional eating and obesity. The current study aimed to investigate the association between emotional eating and weight status and to explore the ways in which eating habits affect this relationship.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDesign\u003c/h2\u003e \u003cp\u003e This cross-sectional study was conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology guidelines and checklist (Appendix S1).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSetting and sample\u003c/h3\u003e\n\u003cp\u003eA survey was conducted from September 2022 to October 2022 among seventh- and eighth-grade middle school students in Taizhou City, Zhejiang Province, using convenience sampling. Before conducting the formal survey, one class (n\u0026thinsp;=\u0026thinsp;42) was selected for a pilot survey to test the reliability of the scale. The preliminary results showed that Cronbach's alpha of the EES-CA was 0.891. We distributed 1016 questionnaires, of which 981 were recovered. According to the nano-exclusion criteria (see Supplementary Information 1), 862 valid questionnaires were finally included after the exclusion of invalid questionnaires. The rate of valid questionnaire completion was 84.8%.\u003c/p\u003e \u003cp\u003e The study protocol was approved by the Ethics Committee of Taizhou Hospital of Zhejiang Province (approval no. K20220932). All participants and their guardians provided written informed consent prior to the study.\u003c/p\u003e\n\u003ch3\u003eStudy instruments\u003c/h3\u003e\n\u003cp\u003eDemographic data included sex, grade, age, height, weight, waist circumference, residence, only child, type of family, living conditions, monthly family income, father's and mother's educational background, number of exercises, amount of exercise time, screen time, and sleep time. Weight status indicators included height, weight, and waist circumference. Uniformly trained nurses measured the height, weight, and waist circumference of students using standardised methods. Participants were instructed to wear minimal clothing, remove their shoes, and stand straight with their heels together and their heels, sacrum, and scapula in contact with a height scale, resulting in a height reading accurate to 0.1 cm and a weight reading accurate to 0.1 kg. After one exhalation with normal breathing, the waist circumference was measured using a fiberglass tape measure at a point halfway between the ilium and lower ribs (the 10th rib) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The BMIZ was calculated using the World Health Organization (WHO) Anthro software (5\u0026ndash;19 years old) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The diagnosis of overweight and obesity was categorised with reference to WHO criteria [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]: BMIZ\u0026thinsp;\u0026le;\u0026thinsp;1 was considered as the normal group; 1\u0026thinsp;\u0026lt;\u0026thinsp;BMIZ\u0026thinsp;\u0026le;\u0026thinsp;2 was regarded as the overweight group; and BMIZ\u0026thinsp;\u0026gt;\u0026thinsp;2 identified the obese group. The waist/height ratio was calculated. Abdominal obesity was classified as waist-to-height ratio (WHtR)\u0026thinsp;\u0026ge;\u0026thinsp;0.46 for girls and WHtR\u0026thinsp;\u0026ge;\u0026thinsp;0.48 for males, as per the \"Prevention and Control of Metabolic Syndrome in Chinese Children\" criteria [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDietary patterns were assessed using a previously studied Food Frequency Questionnaire (FFQ) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], which was adapted from the Chinese version of the Adolescent FFQ [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and intended to gauge teenagers' eating patterns over the previous 3 months. Based on similarities in nutritional content and cooking techniques, 13 preset categories were created for single meals from the FFQ (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Students were asked how frequently, how many times in a given time frame, and how many portions at each sitting they would consume of each food type. The frequency of eating was categorised as follows: 7, daily; 1, weekly; 0.25, monthly; and 0, annually. The students selected the number of servings they ate each day, week, month, and year, which was based on how frequently they ate the food type. Considering the difficulty of the students' cognitive ability to recognise the number of food portions and understand the concept of average intake. For this study, each portion of each food item was standardised, and colour pictures were made using the same food containers as a reference. Students were then asked to choose the average number of servings based on these pictures. The following formula was used to determine the average number of servings per day for each food group: frequency of eating \u0026times; number of times eaten \u0026times; number of servings/7\u0026thinsp;=\u0026thinsp;total number of servings per day.\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\u003eFood grouping used in dietary pattern 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\u003eFood Groups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFood Items\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRice flour\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRice, buns, noodles, pancakes, bread\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLivestock meat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChicken and duck, pork, beef and lamb\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEggs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEggs, duck eggs\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLegumes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSoybean milk, soybean skin, tofu, dried beans\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAquatic products\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFish, shrimp, crab, squid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDairy products\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlain milk, yogurt, cheese\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-starchy vegetables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpinach, Chinese cabbage, mini Chinese cabbage, beans, tomatoes, carrots\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoot vegetables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePotatoes, lotus root\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBacteria and algae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeedle mushrooms, mushrooms and seaweed\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNuts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMelon seeds, badam, almonds, cashews\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRough food\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOats, maize, sweet potato\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFruit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eApples, oranges, pears, blueberries, dragon fruit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnacks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInstant noodles, sweets, fried snacks\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\u003eEmotional eating was assessed using EES-CA. The scale was revised by Kraft et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] and translated into Chinese by Chen et al. [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] in 2013. The scale is a self-report scale for assessing children and adolescents aged 11\u0026ndash;18 years old, including three dimensions of depression, anger/rage, and anxiety, with a total of 18 entries, scored on a 5-point Likert scale (i.e. 1\u0026thinsp;=\u0026thinsp;not at all, 2\u0026thinsp;=\u0026thinsp;somewhat, 3\u0026thinsp;=\u0026thinsp;fairly, 4\u0026thinsp;=\u0026thinsp;strongly, 5\u0026thinsp;=\u0026thinsp;very strongly); the impulse to spend in the face of negativity increases with a higher overall score. Cronbach's α for this scale was 0.936.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eData were analysed using SPSS Statistics for Windows (version 27.0; IBM Corp., Armonk, NY, USA) and PROCESS macros. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Descriptive statistics were analysed to present the demographic information of the participants and their parents. Univariate analyses were performed using the independent samples t-test, one-way analysis of variance, or the Mann\u0026ndash;Whitney U-test/Kruskal\u0026ndash;Wallis H-test, depending on the sample distribution.\u003c/p\u003e \u003cp\u003e Principal component analysis was used to determine participants\u0026rsquo; dietary patterns. Prior to the adoption of this statistical technique, the feasibility of multivariate analysis using these variables was assessed using the Bartlett sphericity test and Kaiser\u0026ndash;Meyer\u0026ndash;Olkin (KMO) analysis. Because the results of the KMO analysis (0.70) and Bartlett's test of sphericity (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were satisfactory, multivariate analysis was conducted [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Common factors were extracted based on the principle of eigenvalues greater than one. Loading factors were obtained from the component matrix, and factor loadings between each food category that were 0.3 or higher (positive or negative) were deemed significant and were retained in the model [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The dietary patterns of the groups were identified using entries with high factor coefficients.\u003c/p\u003e \u003cp\u003ePearson\u0026rsquo;s or Spearman\u0026rsquo;s correlation analysis was used to investigate the correlation among emotional eating, eating patterns, and weight status. Correlation coefficient values\u0026thinsp;\u0026lt;\u0026thinsp;0.3 were interpreted as weak and as strong when they were \u0026gt;\u0026thinsp;0.7 [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Hayes developed the SPSS macro program PROCESS [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] to mediate and moderate analyses. Variables with p\u0026thinsp;\u0026lt;\u0026thinsp;0.1 in univariate analysis were chosen and added to the model as covariates. Model 4 in the SPSS macro program PROCESS was used to test whether eating patterns mediated the relationship between emotional eating (independent variable) and weight (dependent variable). Bootstrapping of 5000 samples was performed. Percentile bootstrapping was used to calculate the mediating effect, and indirect effects were considered significant when the 95% bootstrap confidence interval (95% CI) was not zero [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDemographic information\u003c/h2\u003e \u003cp\u003eIn total, 862 participants, including 482 (55.9%) boys and 380 (44.1%) girls, with a mean age of 13.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70 years, participated in this study (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). For this sample, BMIZ was 0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28, and WHtR was 0.42 (0.39, 0.47). The participant recruitment and retention procedures are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" 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\u003eDemographic information of participants (N\u0026thinsp;=\u0026thinsp;862)\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber (%)/ mean\u0026thinsp;\u0026plusmn;\u0026thinsp;Sd OR median (IQR) / range\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eadolescent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e482 (55.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGirl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e380 (44.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e462 (53.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e400 (46.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (y)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMIZ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWHtR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.42 (0.39, 0.47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidential\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e220 (25.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e642 (74.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe only child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e134 (15.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e728 (84.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlace of residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e450 (52.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e412 (47.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of family\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTwo-parent families\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e707 (82.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle parent families\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e120 (13.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReorganized families\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35 (4.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving condition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with parents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e462 (53.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with parents and grandparents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e126 (14.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with relatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e274 (31.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of exercises\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e514 (59.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e348 (40.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 60 min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e796 (92.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; 60 min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66 (7.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScreen time (h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e432 (50.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e430 (49.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep time (h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e180 (20.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e682 (79.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParents\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonthly family income (CNY)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e405 (47.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5,000\u0026ndash;9,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e341 (39.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;10,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e116 (13.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation of the father\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary school and below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e135 (15.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLower secondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e536 (62.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e168 (19.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23 (2.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation of the mother\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary school and below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e177 (20.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLower secondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e483 (56.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e173 (20.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29 (3.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eNote: BMIZ, body mass index Z score; WHtR, waist-to-height ratio; CNY, Chinese Yuan.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFurther demographic information was subjected to the Mann\u0026ndash;Whitney U test and Kruskal\u0026ndash;Wallis H test to identify factors that may influence the BMIZ/WHtR. The results of this analysis are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Sex, age, type of family, screen time, and education of the father were the influencing factors of BMIZ. Age, screen time, and education of the father were influencing factors of WHtR.\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\u003eInfluencing factors of BMIZ/WHtR (N\u0026thinsp;=\u0026thinsp;862)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMIZ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003et/F\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWHtR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eZ/H\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eadolescent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.808\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.339\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.39, 0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGirl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.40, 0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.928\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.39, 0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.40, 0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (y)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.970\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.44 (0.40, 0.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.28\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.39, 0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.39, 0.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidential\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.697\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.40, 0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.39, 0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe only child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.682\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.809\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.39\u0026ndash;0.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.40\u0026ndash;0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlace of residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.722\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.470\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.40\u0026ndash;0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.39\u0026ndash;0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of family\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTwo-parent families\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.40, 0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle parent families\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.39, 0.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReorganized families\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.41 (0.39, 0.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving condition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.148\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with parents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.39\u0026ndash;0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with parents and grandparents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.43 (0.40, 0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with relatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.43 (0.40, 0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of exercises\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-1.445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.40, 0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.39, 0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.724\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.995\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;60 min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.39, 0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;60 min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;1.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.40, 0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScreen time (h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-2.235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-2.266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.39\u0026ndash;0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.43 (0.40\u0026ndash;0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep time (h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.879\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.357\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.43 (0.40\u0026ndash;0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.39\u0026ndash;0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParents\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonthly family income(CNY)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.573\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;5,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.39, 0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5,000\u0026ndash;9,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.43 (0.40, 0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;10,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.39, 0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation of the father\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary school and below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.43 (0.40, 0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLower secondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.39, 0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.40, 0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.40 (0.38, 0.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation of the mother\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.356\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary school and below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.43 (0.40, 0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLower secondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.39, 0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.34\u0026thinsp;\u0026plusmn;\u0026thinsp;1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42 (0.39, 0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.40 (0.39, 0.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: BMIZ, body mass index Z score; WHtR, waist-to-height ratio; CNY, Chinese Yuan.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAnalysis of adolescent dietary patterns\u003c/h3\u003e\n\u003cp\u003eDietary patterns in this study were determined using principal component analysis. To test the suitability of the data for principal component analysis, the KMO test and Bartlett's test of sphericity were performed, with KMO\u0026thinsp;=\u0026thinsp;0.872 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, indicating that the data supported the principal component analysis. Two public factors were extracted based on the principle that eigenvalues are greater than 1. The component matrices for each dietary pattern are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Two dietary patterns were identified in this study. Dietary pattern 1, the traditional dietary pattern, was defined as a diet containing high-protein foods, such as eggs, beans, dairy products, aquatic items, root vegetables, bacteria and algae, nuts, and coarse cereals. Dietary pattern 2, the modern dietary pattern, was defined as consisting of high-load staple meals, animal and poultry meat, snacks, and high vegetable load. These two dietary patterns explained 45.62% of the food group differences. The dietary pattern characteristics of the normal-weight and overweight/obese groups are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactor loadings for two dietary patterns derived from principal component analysis\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\u003eFood\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDietary pattern 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDietary pattern 2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRice flour\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.688\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLivestock meat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.723\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEggs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.507\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLegumes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.747\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAquatic products\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.744\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDairy products\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-starchy vegetables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-0.618\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoot vegetables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.622\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBacteria and algae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.758\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.073\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNuts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.629\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.041\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRough food\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.770\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFruit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.580\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.145\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnacks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.711\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eNote: The bold value indicates that the item is one of the representative foods under the corresponding dietary pattern.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eCorrelations between study variables\u003c/h3\u003e\n\u003cp\u003eThe Spearman correlation coefficients between the main study variables are shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u0026thinsp;\u0026minus;\u0026thinsp;1. Emotional eating was strongly correlated with BMIZ (r\u0026thinsp;=\u0026thinsp;0.754, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and moderately positively correlated with eating pattern 2 (r\u0026thinsp;=\u0026thinsp;0.676, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, it was not associated with Dietary Pattern 1 (r\u0026thinsp;=\u0026thinsp;0.018, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). BMIZ was significantly and strongly correlated with Dietary Pattern 2 (r\u0026thinsp;=\u0026thinsp;0.800, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) but not with Dietary Pattern 1 (r\u0026thinsp;=\u0026thinsp;0.052, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026thinsp;\u003cb\u003e\u0026minus;\u0026thinsp;1\u003c/b\u003e Correlations between the main study variables (N\u0026thinsp;=\u0026thinsp;862)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEES-CA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDietary pattern 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDietary pattern 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBMIZ\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEES-CA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDietary pattern 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDietary pattern 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.676**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.090**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMIZ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.754**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.800**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: ***, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; BMIZ, body mass index Z score; EES-CA, Emotion Eating Scale for Chinese Adolescents\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026thinsp;\u003cb\u003e\u0026minus;\u0026thinsp;2\u003c/b\u003e Correlations between the main study variables (N\u0026thinsp;=\u0026thinsp;862)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEES-CA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDietary pattern 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDietary pattern 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWHtR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEES-CA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDietary pattern 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDietary pattern 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.676**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.090**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWHtR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.623**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.671**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: ***, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; BMIZ, body mass index Z score; EES-CA, Emotion Eating Scale for Chinese Adolescents\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u0026thinsp;\u0026minus;\u0026thinsp;2, WHtR was somewhat positively correlated with emotional eating (r\u0026thinsp;=\u0026thinsp;0.623, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The WHtR and Dietary Pattern 2 showed a moderate and significant correlation (r\u0026thinsp;=\u0026thinsp;0.671, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but this was not the case for Dietary Pattern 1 (r\u0026thinsp;=\u0026thinsp;0.059, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Overall, the results of the correlation analysis indicated that the pairwise combinations of emotional eating, Dietary pattern 2, and BMIZ/WHtR variables were significant and indicated a correlation between the three variables.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMultiple hierarchical linear regression models\u003c/h2\u003e \u003cp\u003eA plug-in for Process 4.1 in SPSS was used to test the hypotheses. Adolescents\u0026rsquo; sex, age, family type, screen time, and father's education level were associated with the BMIZ, while adolescents\u0026rsquo; age, screen time, and father's education level were associated with WHtR (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). We considered the potential confounding effects of demographic variables and included them as covariates to test for associations among emotional eating habits, eating patterns, and weight status. In addition, eating patterns were tested as potential mediators of the association between emotional eating and weight.\u003c/p\u003e \u003cp\u003eSubsequent studies showed that the relationship between emotional eating and the BMIZ/WHtR was significantly influenced by eating patterns. Dietary pattern 2 seemed to be a major mediating factor among the eating patterns examined in this study. We found that adolescents who ate more emotionally were more prone to developing obesogenic eating practices. The substantial indirect effects of 0.446 for BMIZ and 0.020 for WHtR (both statistically significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) indicate that this pattern later impacted their weight status. Dietary pattern 1, however, had no discernible impact (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the present study, we identified two dietary patterns: traditional and modern. Modern dietary patterns were significantly and positively associated with the BMIZ/WHtR (Hypothesis 1) and were a mediator between emotional eating and the BMIZ/WHtR (Hypothesis 2). This suggests that weight status can be influenced by a modern dietary pattern characterised by high loads of snacks, rice flour, livestock meat, and non-starchy vegetables. These characteristics may be key targets for interventions aimed at preventing (abdominal) obesity.\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, limited research has been conducted on teenage populations that characterise diets as eating patterns or show a connection between certain eating patterns and emotional eating [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. These studies have demonstrated a favourable correlation between eating patterns, including meals high in fat or sugar, and emotional eating. In contrast, this study generated distinct eating patterns for different diets using principal component analysis. Consequently, highly appealing, energy-dense eating behaviours are positively associated with emotional eating [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Super-palatable, high-energy, and high-fat meals (rich in sugar and fat) are a hallmark of highly palatable, energy-dense eating behaviours [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. These meals mostly consist of staples, such as rice, buns, noodles, pancakes, bread, and animal and poultry meat, including chicken, duck, hog, beef, and lamb, as well as snacks, such as instant noodles, chocolate, cakes, fried foods, and sugary drinks.\u003c/p\u003e \u003cp\u003eIn line with previous studies, this study showed a positive correlation between emotional eating and BMIZ levels, which can lead to weight gain [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Adolescence is a unique stage of physical and mental development for teenagers. During this time, they acquire long-term food-related habits and experience an increase in unhealthy eating habits, a loss of parental supervision, and an increase in independence [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Teenagers may have more opportunities to control their emotions and eating habits when parental supervision decreases. According to self-regulation theory, emotional eating may be caused by problems with emotion management, according to self-regulation theory [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Emotional episodes sometimes involve the consumption of significant quantities of sugary, calorie-dense, and/or high-fat meals [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Research has indicated that individuals with elevated emotional eating scores typically experience heightened appetites during depressive states, are more likely to overindulge, and exhibit specific desires for high-energy and sweet foods, which contribute to the accumulation of excess calories and the potential for obesity [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. These beautiful meals deliver instant gratification and delightful sensations, which can help divert attention from unpleasant feelings. Moreover, both acute and long-term stress have an impact on reward/motivation and inhibition-control pathways and are risk factors for the emergence of emotional eating, as well as providing stimulation of the hypothalamic\u0026ndash;pituitary\u0026ndash;adrenal axis [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Following the establishment of this route, those who are triggered by food cues engage in the food reward system, which raises their desire to eat and results in better awareness of food signals. Therefore, in the future, we can conduct interdisciplinary studies between dietary, psychological, and brain sciences, as well as teenage obesity.\u003c/p\u003e \u003cp\u003eIn addition, several stress-related mental issues, including anxiety, depression, and sleep difficulties, have been brought about by the coronavirus disease 2019 (COVID-19) pandemic. Emotional eating has become common as a coping mechanism for people's feelings. When coupled with a decline in physical activity, it leads to an increase in the incidence of overweight and obesity [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Following the outbreak, there was a 25.2% worldwide detection rate of melancholic mood in children and adolescents, with a double incidence of 43.7% among Chinese secondary school students [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Anxiety was the cause in 31.9% of the cases [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. According to the current research, teenage emotion management may play a significant role in the pathways leading to obesity risk. Adolescents who struggle with emotional control may be more likely to overindulge in emotional eating, which puts them at risk of obesity [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Therefore, future therapies aimed at preventing teenage obesity should focus on mood management and emotional eating behaviours. Furthermore, following such significant public health incidents, families, schools, and hospitals should pay close attention to the mental health issues teenagers face and quickly establish coping mechanisms.\u003c/p\u003e \u003cp\u003eIn contrast to other research studies [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], we also discovered a relationship between WHtR and emotional eating. This finding implies that teenagers' WHtR is more relevant when they have high emotional eating scores. Although BMI is a commonly used indicator of obesity, it does not differentiate between lean and fat mass, nor does it identify the location of adiposity [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Conversely, the WHtR is a significant marker for centripetal obesity, which is a stronger predictor of the risk of conditions, including diabetes and cardiovascular disease [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Therefore, considering both body fat distribution and BMI in future studies is imperative.\u003c/p\u003e \u003cp\u003eAdditionally, the current study discovered a substantial and favourable correlation between the BMIZ/WHtR and contemporary dietary patterns. High and low loads of vegetables, snack items, animal and poultry meats, and staple foods typified the study's dietary patterns. Evaluating dietary patterns is intriguing because they represent the entire diet or the assortment of foods that people usually eat as opposed to concentrating on specific nutrients or foods [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Adolescents who consume more processed meats, fried potatoes, refined cereals, and added sugars and more whole grains than fruits, vegetables, whole grains, and low-fat dairy products have been shown to have higher body and fat mass indices [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], which is generally consistent with the findings of this study; moreover, consuming many ultra-processed meals high in fat, salt, and refined carbohydrates has been linked to a higher risk of cardiometabolic changes in teenagers [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Additionally, teenage obesity in outpatient clinics is associated with an excessive consumption of meat and sugary foods [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Consequently, because it captures the intricate relationships between various food intakes more accurately, studying and evaluating the dietary patterns of particular communities can offer thorough insights into the impact of diet on health. Furthermore, investigating the relationship between these eating patterns and obesity will eventually offer a scientific foundation for multimodal health education on childhood obesity that is centred on family, school, and society, as well as nutritional treatments. Consequently, because it captures the intricate relationships between various food intakes more accurately, studying and evaluating the dietary patterns of particular communities can offer thorough insights into the impact of diet on health. Investigating the link between these eating patterns and obesity will provide a scientific foundation for multimodal health education on childhood obesity and nutritional treatments shared by families, schools, and society.\u003c/p\u003e \u003cp\u003eAdditionally, the association between emotional eating and BMIZ/WHtR is partially mediated by contemporary eating practices. According to the reinforcement theory, people choose to eat to reduce their negative emotions. This leads to an increase in the amount of food consumed during negative emotions, which solidifies into specific eating patterns over time. This theory is supported by research [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Moreover, earlier research revealed that reactive eating habits in children and teenagers buffer the link between food addiction and BMIZ [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. However, emotional eating was documented in 46% of teenagers [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Over time, good energy balance is facilitated by the eating habits of emotional eaters who tend to select high-carbohydrate, high-fat, and sugary meals and snacks more often to ease negative feelings [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Therefore, it is not possible to gain a thorough understanding of complicated eating behaviours by concentrating on only one area. Calorie-restricted diets, as well as emotion-regulation strategies and the rationality of meal pairings, should be the main focus of treatment and care for obese children who exhibit high levels of emotional expression. To help children learn more about emotional eating, we can investigate positive thinking-based therapies in the future, such as positive thinking eating exercises [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], positive thinking meditation training [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], and positive thinking-based emotional eating awareness training [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Furthermore, nutritional health education programs may be established in schools and hospitals, aiding teenagers in the development of healthy eating habits, helping them make informed food choices, and lowering the prevalence of overweight and obesity.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, the cross-sectional design can only account for correlation rather than causation, which is more useful when guiding interventions. Second, Hawthorne effects are inevitable based on convenience sampling techniques, in addition to selection bias introduced by the study population [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. This limitation may be addressed in future studies using randomised sampling techniques. Third, this study was limited to a single Taizhou school, which may have limited the extent to which the results can be applied. To obtain more representative results, multicentre studies are necessary. Fourth, a self-reported questionnaire was used to evaluate eating behaviours, which may have obscured the data gathered. To increase the reliability of these findings, reliable objective measurements should be used in future studies. Finally, dietary pattern analysis was limited to broad food groups, complicating the identification of foods that increase risk.\u003c/p\u003e \u003cp\u003eIn conclusion, teenagers with high emotional eating scores tend to follow dietary patterns linked to obesity, including the consumption of snacks, carbs, fats, and sugars. This highlights problematic areas for weight loss efforts, such as emotional eating patterns and the traits that accompany them. This study also emphasises the need for policies that promote healthy food and lifestyle choices in teenagers and address obesity prevention and management.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the Enze Medical Centre Scientific Research Fund (grant number 22EZC12) and Taizhou Municipal Science and Technology Bureau of Zhejiang Province (grant numbers 24ywb19 and 24ywb21)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDW and MXZ conceived and designed the study. DW drafted the manuscript. DW, HYY, and HHS collected the data and controlled their quality. DW and HLF conducted the data analyses. TTH, LZW, and MXZ revised the manuscript. All authors contributed to publishing the final manuscript. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the Ethics Committee of Taizhou Hospital of Zhejiang Province, China (approval no. K20220932) and was conducted in accordance with the guidelines of the institutional ethics committee and the principles outlined in the Declaration of Helsinki. Informed consent was obtained from all participants. All participants and their guardians provided written informed consent prior to the study. The integrity of all participant information was strictly maintained, and each participant had the right to withdraw from the study at any time.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003evan Strien T. Causes of emotional eating and matched treatment of obesity. Curr Diab Rep. 2018;18(6):35. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11892-018-1000-x\u003c/span\u003e\u003cspan address=\"10.1007/s11892-018-1000-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 29696418.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDakanalis A, Mentzelou M, Papadopoulou SK, Papandreou D, Spanoudaki M, Vasios GK, et al. The association of emotional eating with overweight/obesity, depression, anxiety/stress, and dietary patterns: a review of the current clinical evidence. Nutrients. 2023;15(5):1173. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/nu15051173\u003c/span\u003e\u003cspan address=\"10.3390/nu15051173\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 36904172.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaplan HI, Kaplan HS. The psychosomatic concept of obesity. J Nerv Ment Dis. 1957;125(2):181\u0026ndash;201. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/00005053-195704000-00004\u003c/span\u003e\u003cspan address=\"10.1097/00005053-195704000-00004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 13481715.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuha J, Schumacher A, Campisi SC, Korczak DJ. Depression and emotional eating in children and adolescents: A systematic review and meta-analysis. Appetite. 2024;200:107511. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.appet.2024.107511\u003c/span\u003e\u003cspan address=\"10.1016/j.appet.2024.107511\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 38788931.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBraet C, Claus L, Goossens L, Moens E, Van Vlierberghe L, Soetens B. Differences in eating style between overweight and normal-weight youngsters. J Health Psychol. 2008;13(6):733\u0026ndash;743. doi: 10.1177/1359105308093850, PMID 18697886.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLimbers CA, Summers E. Emotional eating and weight status in adolescents: a systematic review. Int J Environ Res Public Health. 2021;18(3):991. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph18030991\u003c/span\u003e\u003cspan address=\"10.3390/ijerph18030991\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 33498603.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBraden A, Musher-Eizenman D, Watford T, Emley E. Eating when depressed, anxious, bored, or happy: are emotional eating types associated with unique psychological and physical health correlates? Appetite. 2018;125:410\u0026ndash;417. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.appet.2018.02.022\u003c/span\u003e\u003cspan address=\"10.1016/j.appet.2018.02.022\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 29476800.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCamilleri GM, M\u0026eacute;jean C, Kesse-Guyot E, Andreeva VA, Bellisle F, Hercberg S, et al. The associations between emotional eating and consumption of energy-dense snack foods are modified by sex and depressive symptomatology. J Nutr. 2014;144(8):1264\u0026ndash;1273. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3945/jn.114.193177\u003c/span\u003e\u003cspan address=\"10.3945/jn.114.193177\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 24850627.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJalo E, Konttinen H, Veps\u0026auml;l\u0026auml;inen H, Chaput JP, Hu G, Maher C, et al. Emotional eating, health behaviours, and obesity in children: a 12-country cross-sectional study. Nutrients. 2019;11(2):351. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/nu11020351\u003c/span\u003e\u003cspan address=\"10.3390/nu11020351\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 30736444.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNguyen-Michel ST, Unger JB, Spruijt-Metz D. Dietary correlates of emotional eating in adolescence. Appetite. 2007;49(2):494\u0026ndash;499. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.appet.2007.03.005\u003c/span\u003e\u003cspan address=\"10.1016/j.appet.2007.03.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 17466408.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChew HS, Lau ST, Lau Y. Weight-loss interventions for improving emotional eating among adults with high body mass index: a systematic review with meta-analysis and meta-regression. Eur Eat Disord Rev. 2022;30(4):304\u0026ndash;327. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/erv.2906\u003c/span\u003e\u003cspan address=\"10.1002/erv.2906\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 35460323.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRuiz LD, Zuelch ML, Dimitratos SM, Scherr RE. Adolescent obesity: diet quality, psychosocial health, and cardiometabolic risk factors. Nutrients. 2019;12(1):43. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/nu12010043\u003c/span\u003e\u003cspan address=\"10.3390/nu12010043\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 31877943.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBetancourt-N\u0026uacute;\u0026ntilde;ez A, Torres-Castillo N, Mart\u0026iacute;nez-L\u0026oacute;pez E, De Loera-Rodr\u0026iacute;guez CO, Dur\u0026aacute;n-Barajas E, M\u0026aacute;rquez-Sandoval F, et al. Emotional eating and dietary patterns: reflecting food choices in people with and without abdominal obesity. Nutrients. 2022;14(7):1371. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/nu14071371\u003c/span\u003e\u003cspan address=\"10.3390/nu14071371\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 35405983.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShriver LH, Dollar JM, Lawless M, Calkins SD, Keane SP, Shanahan L, et al. Longitudinal associations between emotion regulation and adiposity in late adolescence: indirect effects through eating behaviors. Nutrients. 2019;11(3):517. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/nu11030517\u003c/span\u003e\u003cspan address=\"10.3390/nu11030517\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 30823405.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKonttinen H, van Strien T, M\u0026auml;nnist\u0026ouml; S, Jousilahti P, Haukkala A. Depression, emotional eating and long-term weight changes: a population-based prospective study. Int J Behav Nutr Phys Act. 2019;16(1):28. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12966-019-0791-8\u003c/span\u003e\u003cspan address=\"10.1186/s12966-019-0791-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 30894189.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiberali R, Kupek E, Assis MA. Dietary patterns and childhood obesity risk: a systematic review. Child Obes. 2020;16(2):70\u0026ndash;85. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1089/chi.2019.0059\u003c/span\u003e\u003cspan address=\"10.1089/chi.2019.0059\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 31742427.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoushey C, Ard J, Bazzano L, Heymsfield S, Mayer-Davis E, Sabat\u0026eacute; J, et al. Dietary patterns and growth, size, body composition, and/or risk of overweight or obesity: a systematic review. Alexandria (VA): USDA Nutrition Evidence Systematic Review; 2020. PMID: 35129906.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQian K, Wang D, Sun Y, Ye X, Wang D, Xu H. Association of dietary patterns with depressive symptoms in Chinese adolescents: a cross-sectional study. Front Nutr. 2023;10:1180858. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fnut.2023.1180858\u003c/span\u003e\u003cspan address=\"10.3389/fnut.2023.1180858\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 37497054.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArruda Neta AC, Farias Junior JC, Lima Ferreira FE, Marchioni DM. Prospective association between dietary patterns and BMI Z-score in Brazilian adolescents. Public Health Nutr. 2021;24(13):4230\u0026ndash;4237. doi: 10.1017/S1368980021000252, PMID 33472719.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNishida C, Ko GT, Kumanyika S. Body fat distribution and noncommunicable diseases in populations: overview of the 2008 WHO Expert Consultation on Waist Circumference and Waist-Hip Ratio. Eur J Clin Nutr. 2010;64(1):2\u0026ndash;5. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/ejcn.2009.139\u003c/span\u003e\u003cspan address=\"10.1038/ejcn.2009.139\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 19935820.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWHO. Anthro Survey Analyser; n.d. [cited Dec 20 2023] Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://worldhealthorg.shinyapps.io/anthro/\u003c/span\u003e\u003cspan address=\"https://worldhealthorg.shinyapps.io/anthro/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLohman TG, Roche AF, Martorell R. Anthropometric standardization reference manual. Champaign, IL: Human Kinetics Publishers; 1988.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiang L, Fu JF, Du JB. Significance of exploring the definition of metabolic syndrome in Chinese children and adolescents. Zhonghua Er Ke Za Zhi. 2012;50(6):401\u0026ndash;404. PMID 22931932.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang WP, Cheng H, Zhao XY, et al. Study on the reliability and validity of the food frequency questionnaire for children and adolescents in Beijing. Chin J Child Health. 2016;24:8\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTanofsky-Kraff M, Theim KR, Yanovski SZ, Bassett AM, Burns NP, Ranzenhofer LM, et al. Validation of the emotional eating scale adapted for use in children and adolescents (EES-C). Int J Eat Disord. 2007;40(3):232\u0026ndash;240. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/eat.20362\u003c/span\u003e\u003cspan address=\"10.1002/eat.20362\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 17262813.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGui C, Tai SC, Feng JH, et al. Revision of the emotional eating scale in Chinese adolescents. Chin J Clin Psychol. 2013;21:572\u0026ndash;575.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBen Salem K, Ben Abdelaziz A. Principal component analysis (PCA). Tunis Med. 2021;99(4):383\u0026ndash;389. PMID 35244921.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSakaluk JK, Short SD. A Methodological review of exploratory factor analysis in sexuality research: used practices, best practices, and data analysis resources. J Sex Res. 2017;54(1):1\u0026ndash;9. doi: 10.1080/00224499.2015.1137538, PMID 26886499.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkoglu H. User\u0026rsquo;s guide to correlation coefficients. Turk J Emerg Med. 2018;18(3):91\u0026ndash;93. doi: 10.1016/j.tjem.2018.08.001, PMID 30191186.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIgartua JJ, Hayes AF. Mediation, moderation, and conditional process analysis: concepts, computations, and some common confusions. Span J Psychol. 2021;24:e49. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/SJP.2021.46\u003c/span\u003e\u003cspan address=\"10.1017/SJP.2021.46\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 35923144.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDi Renzo L, Gualtieri P, Cinelli G, Bigioni G, Soldati L, Attin\u0026agrave; A, et al. Psychological aspects and eating habits during COVID-19 home confinement: results of EHLC-COVID-19 Italian online survey. Nutrients. 2020;12(7):2152. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/nu12072152\u003c/span\u003e\u003cspan address=\"10.3390/nu12072152\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 32707724.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSosa-Cordob\u0026eacute;s E, Garc\u0026iacute;a-Padilla FM, Ortega-Gal\u0026aacute;n \u0026Aacute;M, S\u0026aacute;nchez-Alc\u0026oacute;n M, Garrido-Fern\u0026aacute;ndez A, Ramos-Pichardo JD. Psychometric properties of the emotional eater questionnaire in university students. Int J Environ Res Public Health. 2022;19(17):10965. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph191710965\u003c/span\u003e\u003cspan address=\"10.3390/ijerph191710965\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 36078680.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFuente Gonz\u0026aacute;lez CE, Ch\u0026aacute;vez-Serv\u0026iacute;n JL, de la Torre-Carbot K, Ronquillo Gonz\u0026aacute;lez D, Aguilera Barreiro ML, Ojeda Navarro LR. Relationship between emotional eating, consumption of hyperpalatable energy-dense foods, and indicators of nutritional status: a systematic review. J Obes. 2022;2022:4243868. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1155/2022/4243868\u003c/span\u003e\u003cspan address=\"10.1155/2022/4243868\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 35634585.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWHO. Obesidad Y sobrepeso. Geneva, Switzerland: World Health Organization; 2021. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/es/news-room/fact-sheets/detail/obesity-and-overweight\u003c/span\u003e\u003cspan address=\"https://www.who.int/es/news-room/fact-sheets/detail/obesity-and-overweight\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFarhangi MA. Night Eating Syndrome and its relationship with emotional eating, sleep quality and nutritional status among adolescents\u0026rsquo; boys. Community Ment Health J. 2019;55(8):1411\u0026ndash;1418. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10597-019-00395-8\u003c/span\u003e\u003cspan address=\"10.1007/s10597-019-00395-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 30879161.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Strien T, Cebolla A, Etchemendy E, Guti\u0026eacute;rrez-Maldonado J, Ferrer-Garc\u0026iacute;a M, Botella C, et al. Emotional eating and food intake after sadness and joy. Appetite. 2013;66:20\u0026ndash;25. doi: 10.1016/j.appet.2013.02.016, PMID 23470231.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePenaforte FR, Minelli MC, Anast\u0026aacute;cio LR, Japur CC. Anxiety symptoms and emotional eating are independently associated with sweet craving in young adults. Psychiatry Res. 2019;271:715\u0026ndash;720. doi: 10.1016/j.psychres.2018.11.070, PMID 30791346.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaier SU, Makwana AB, Hare TA. Acute stress impairs self-control in goal-directed choice by altering multiple functional connections within the brain\u0026rsquo;s decision circuits. Neuron. 2015;87(3):621\u0026ndash;631. doi: 10.1016/j.neuron.2015.07.005, PMID 26247866.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurnatowska E, Surma S, Olszanecka-Glinianowicz M. Relationship between mental health and emotional eating during the COVID-19 pandemic: a systematic review. Nutrients. 2022;14(19):3989. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/nu14193989\u003c/span\u003e\u003cspan address=\"10.3390/nu14193989\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 36235642.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRacine N, McArthur BA, Cooke JE, Eirich R, Zhu J, Madigan S. Global prevalence of depressive and anxiety symptoms in children and adolescents during COVID-19: a meta-analysis. JAMA Pediatr. 2021;175(11):1142\u0026ndash;1150. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jamapediatrics.2021.2482\u003c/span\u003e\u003cspan address=\"10.1001/jamapediatrics.2021.2482\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 34369987.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu T, Jia X, Shi H, Niu J, Yin X, Xie J, et al. Prevalence of mental health problems during the COVID-19 pandemic: A systematic review and meta-analysis. J Affect Disord. 2021;281:91\u0026ndash;98. doi: 10.1016/j.jad.2020.11.117, PMID 33310451.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrajek M, Krupa-Kotara K, Białek-Dratwa A, Staśkiewicz W, Rozmiarek M, Misterska E, et al. Prevalence of emotional eating in groups of students with varied diets and physical activity in Poland. Nutrients. 2022;14(16):3289. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/nu14163289\u003c/span\u003e\u003cspan address=\"10.3390/nu14163289\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 36014794.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNuttall FQ. Body mass index: obesity, BMI, and health: a critical review. Nutr Today. 2015;50(3):117\u0026ndash;128. doi: 10.1097/NT.0000000000000092, PMID 27340299.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrowning LM, Hsieh SD, Ashwell M. A systematic review of waist-to-height ratio as a screening tool for the prediction of cardiovascular disease and diabetes: 0\u0026middot;5 could be a suitable global boundary value. Nutr Res Rev. 2010;23(2):247\u0026ndash;269. doi: 10.1017/S0954422410000144, PMID 20819243.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu FB. Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol. 2002;13(1):3\u0026ndash;9. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/00041433-200202000-00002\u003c/span\u003e\u003cspan address=\"10.1097/00041433-200202000-00002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 11790957.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRocha NP, Milagres LC, Longo GZ, Ribeiro AQ, Novaes JF. Association between dietary pattern and cardiometabolic risk in children and adolescents: a systematic review. J Pediatr (Rio J). 2017;93(3):214\u0026ndash;222. doi: 10.1016/j.jped.2017.01.002, PMID 28238682.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrauchmann J, Bau AM, Mensink GB, Richter A, Ernert A, Keller T, et al. Dietary patterns in adolescent obesity as predictors of long-term success following an intensive inpatient lifestyle programme. Int J Environ Res Public Health. 2022;19(24):16613. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph192416613\u003c/span\u003e\u003cspan address=\"10.3390/ijerph192416613\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 36554494.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBecker KD, Fischer S, Smith GT, Miller JD. The influence of negative urgency, attentional bias, and emotional dimensions on palatable food consumption. Appetite. 2016;100:236\u0026ndash;243. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.appet.2016.02.019\u003c/span\u003e\u003cspan address=\"10.1016/j.appet.2016.02.019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 26877214.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang D, Wang D, Ye X, Chen J, Fu J, Xu H. Food addiction and its impact on weight status in children and adolescents: the mediating role of responsive eating pattern. Pediatr Obes. 2024;19(2):e13090. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/ijpo.13090\u003c/span\u003e\u003cspan address=\"10.1111/ijpo.13090\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 38148618.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoseph PL, Gon\u0026ccedil;alves C, Fleary SA. Psychosocial correlates in patterns of adolescent emotional eating and dietary consumption. PLOS One. 2023;18(5):e0285446. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0285446\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0285446\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 37224099.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHendrickson KL, Rasmussen EB. Mindful eating reduces impulsive food choice in adolescents and adults. Health Psychol. 2017;36(3):226\u0026ndash;235. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/hea0000440\u003c/span\u003e\u003cspan address=\"10.1037/hea0000440\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 27808529.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTorske A, Bremer B, H\u0026ouml;lzel BK, Maczka A, Koch K. Mindfulness meditation modulates stress-eating and its neural correlates. Sci Rep. 2024;14(1):7294. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-024-57687-7\u003c/span\u003e\u003cspan address=\"10.1038/s41598-024-57687-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 38538663.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLattimore P. Mindfulness-based emotional eating awareness training: taking the emotional out of eating. Eat Weight Disord. 2020;25(3):649\u0026ndash;657. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s40519-019-00667-y\u003c/span\u003e\u003cspan address=\"10.1007/s40519-019-00667-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 30859465.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYeh MY, Wu SC, Tung TH. The relation between patient education, patient empowerment and patient satisfaction: a cross-sectional-comparison study. Appl Nurs Res. 2018;39:11\u0026ndash;17. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.apnr.2017.10.008\u003c/span\u003e\u003cspan address=\"10.1016/j.apnr.2017.10.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, PMID 29422144.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"adolescents, emotional eating, dietary pattern, obesity, mediation analysis, public health","lastPublishedDoi":"10.21203/rs.3.rs-6468108/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6468108/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground/Objectives: \u003c/strong\u003eEmotional eating has been linked to obesity. Although many studies have examined this association, the underlying mechanisms remain unclear . This study aimed to investigate whether dietary patterns mediate the relationship between emotional eating and body weight among adolescents.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSubjects/Methods: \u003c/strong\u003eThis cross-sectional study utilized convenience sampling to recruit students from a middle school in Taizhou City, Zhejiang Province, China, between September 2022 and October 2022. This study adhered to the STROBE guidelines. Emotional eating was evaluated using the Emotional Eating Scale for Chinese Adolescents, and dietary patterns were derived through principal component analysis of data from the Food Frequency Questionnaire. Body mass index Z-scores (BMIZs) and waist-to-height ratios (WHtR) were used as indicators of body weight. Mediation analysis was applied to explore the indirect effects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInterventions: \u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eTwo dietary patterns were identified: traditional and modern. The modern pattern—characterised by high consumption of snacks, carbohydrate, fats, and sugars—was substantially linked to emotional eating and body weight (p \u0026lt; 0.001). Mediation analysis showed that this dietary pattern partially mediated the relationship between emotional eating and body weight, with indirect effects of 0.020 (95% confidence interval [CI] [0.016, 0.023]) for WHtR and 0.446 (95% CI [0.387, 0.509]) for BMIZ.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eEmotional eating in adolescents is associated with increased body weight, and this relationship is partially mediated by a modern dietary pattern rich in snacks, carbohydrates, fats, and sugars. These results suggest that clinical interventions targeting emotional eating should also consider underlying dietary behaviours to more effectively support healthy weight management in adolescents.\u003c/p\u003e","manuscriptTitle":"Emotional eating and adolescents body weight: the mediating role of dietary patterns in Taizhou, China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-08 17:10:45","doi":"10.21203/rs.3.rs-6468108/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a1781e1a-c8b0-443e-b59d-a9e5d45b3aeb","owner":[],"postedDate":"May 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":48098591,"name":"Health sciences/Health care/Paediatrics"},{"id":48098592,"name":"Health sciences/Endocrinology/Endocrine system and metabolic diseases/Obesity"},{"id":48098593,"name":"Health sciences/Health care/Public health/Epidemiology"},{"id":48098594,"name":"Health sciences/Health care/Nutrition"}],"tags":[],"updatedAt":"2025-07-17T14:06:46+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-08 17:10:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6468108","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6468108","identity":"rs-6468108","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}