A Cross-Sectional study of Eating Attitudes in Hong Kong Athletes

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Cheung, James W.H. Sze, Frankie P.L. Siu, Sophia L.Y. Li, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8839694/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 13 You are reading this latest preprint version Abstract Numerous studies have explored disordered eating (DE) in athletes, yet their findings frequently conflict. This research focused on examining the prevalence of DE among HK Chinese athletes. A sample of 100 athletes participated in the study, which employed a cross-sectional design using the EAT-26 questionnaire. The results revealed a prevalence rate of 4.0%, notably lower than global averages. Athletes with dieting experience scored higher on EAT-26 compared to those without (8.08 ± 9.03 vs. 4.92 ± 5.73, p 5) (9.91 ± 8.89 vs. 4.21 ± 5.51, p < 0.05). Pearson’s correlation analysis demonstrated that age and EAT-26 scores showed a weak negative correlation (r = -0.234, p < 0.05), while self-perceived BI had a moderate negative correlation with EAT-26 scores (r = -0.344, p < 0.01). Regression analysis identified age (β = -0.339, p < 0.001) and self-perceived BI (β = -0.226, p < 0.05) as predictors of EAT-26 scores. Results align with international studies indicating higher scores among younger athletes and those with dieting history, suggesting tailored health education programs for different groups may be beneficial. Level of Evidence: Level V, Descriptive Study. Hong Kong athletes HK athletes disordered eating EAT-26 Figures Figure 1 Figure 2 Figure 3 INTRODUCTION The term disordered eating (DE) or disordered eating behaviours (DEBs) generally refers to symptoms that include the unnecessary or excessive use of weight loss methods like dieting or over-exercising, the inappropriate use of diuretics or laxatives, self-induced vomiting, and in some cases, episodes of periodic binge eating [ 1 – 2 ]. A substantial body of literature exists on DE or DEBs among foreign athletes, though the findings are often inconsistent. Some studies indicate that athletes exhibit higher average levels of eating disorder psychopathology and a greater prevalence of DEBs when compared to non-athletes (e.g., Fortes, L. de S., et al ., 2014 [ 3 ]; Holm-Denoma et al ., 2009 [ 4 ]; Sundgot-Borgen & Torstveit, 2004 [ 5 ]). However, some studies, such as those by Martinsen et al . (2010) and Reinking & Alexander (2005), have shown contrasting findings, reporting either higher body satisfaction among athletes or no significant differences between athletes and non-athletes, as evidenced by works like Chapman and Woodman (2016) or Rosendahl et al . (2009). Moreover, there is a paucity of research on the prevalence of DEBs among Asian athletes, particularly in Chinese population. The purpose of this study was to determine the prevalence of DE among Hong Kong Chinese athletes and also examine the associations between EAT-26 scores and socio-demographic variables. METHODS 2.1. Experimental design This study was conducted as a cross-sectional survey utilizing the EAT-26 questionnaire as described in Section 2.3 . 2.2. Participants All athletes were invited to complete the questionnaire via an email sent to all coaches at The Hong Kong Sports Institute (HKSI). The participants were provided with full details of the study, including its purpose, potential risks, benefits, and their right to withdraw at any time. After being thoroughly informed, they willingly consented to participate by signing a consent form. In the end, the study examined 100 Chinese athletes, aged between 16 and 36. The inclusion and exclusion criteria for the participants are presented in Table 1 . Table 1 The inclusion and exclusion criteria for the participants The inclusion criteria for the participants were the following: (a) providing personal and parental/ guardian consent, (b) able to complete the questionnaires, and (c) a full-time or part-time athletes under training at the (THE NAME OF TRAINING INSTITUTE). The exclusion criteria for the participants were the following: (a) not providing personal and parental consent, (b) unable to provide information (i.e., complete the study’s questionnaires), or (c) having health-related problems or diagnosis (e.g., physical disabilities, diabetes mellitus, gastrointestinal diseases etc). 2.3. Questionnaires The questionnaire was utilized to gather data from February 22, 2024, to April 22, 2024, at HKSI. It comprised three sections: 2.3.1. Socio-demographic characteristics of participants The initial section focused on the demographic characteristics of the participants, covering details such as age, gender, year of birth, country of citizenship, education level, type of sports, along with their regular training frequency and duration. 2.3.2. Self-perceived body image, dieting methods and eating attitudes test The second section included questions regarding their dietary practices and the Eating Attitudes Test (EAT-26) [ 10 ]. The EAT-26 is a 26-item assessment designed to evaluate disordered eating attitudes and behaviours, which was incorporated into the questionnaire. In this study, the modified Chinese version of the EAT-26 [ 11 – 12 ], as outlined by Mak, K. K., and Lai, C. M. (2011) [ 13 ], was utilized and described in detail. This tool has shown strong validity and reliability among secondary school students and undergraduates in Hong Kong [ 14 – 15 ]. Additionally, participants rated their self-perceived body image (BI) using a numerical scale ranging from 0 (worst) to 9 (best). They were also asked to select their body type from four categories: athlete, fitness, average, and obese. 2.3.3. Anthropometric characteristics of participants The anthropometric characteristics of participants included height, weight, BF% and percentage of lean body mass were recorded. The participants’ standing heights were measured in bare feet to the nearest 0.1 cm with a tape fixed on a vertical wall. Their weights were measured with light clothes to the nearest 0.1 kg using a bioelectrical impedance analysis (BIA) (InBody 720, Biospace, Korea). Moreover, body fat percentage and percentage of lean body mass were obtained by the BIA. 2.4. Statistical Analysis Statistical analyses were performed using the Statistical Packages for Social Sciences (SPSS) version 31.0 (SPSS Inc., Chicago, IL, USA). For all analyses, the level of statistical significance was set at 0.05. Continuous variables were presented as means with standard deviation, while categorical variables were presented as frequencies and percentages. Data were analyzed using Independent samples t-tests, χ 2 analysis, one-way ANOVA, Pearson’s correlation analysis and multiple linear regression models. RESULTS 3.1. Demographical and anthropometric data of all participants Of the 102 eligible subjects, two were excluded because of incomplete questionnaires. A total of 100 HKSI athletes were included in the final analysis. The sample consisted of participants male (58.0%) appeared to be in the majority, identified as Hong Kong Chinese residents (99.0%), college graduates (62.0%), and the mean (SD) age was 22.5 (4.66) years. Male athletes were significantly heavier, taller and had higher lean body mass as well as lower body fat percentage than female athletes (p < 0.001). The comparisons were made between male and female participants with results shown in Table 2 . Table 2 Demographic and anthropometric characteristics Female athletes (n = 42) Male athletes (n = 58) p-value Total (n = 100) Age (years) 22.95 ± 4.77 22.16 ± 4.59 0.401 22.49 ± 4.66 Height (cm) 163.9 ± 5.24 174.7 ± 6.14 < 0.001*** 170.2 ± 7.86 Weight (kg) 56.75 ± 4.62 69.67 ± 8.12 < 0.001*** 62.24 ± 9.37 Body fat (%) 20.03 ± 4.05 12.97 ± 4.78 < 0.001*** 15.93 ± 5.68 Lean body mass (kg) 44.34 ± 6.51 60.47 ± 6.29 < 0.001*** 53.69 ± 10.2 BF% categories 0.131 Athletes 20 (47.6%) 35 (60.3%) 55 (55.0%) Fitness 18 (42.9%) 14 (24.1%) 32 (32.0%) Average 4 (9.5%) 9 (15.5%) 13 (13.0%) Hong Kong resident 0.392 Yes 42 (100%) 57 (98.3%) 99 (99.0%) No 0 (0%) 1 (1.7%) 1 (1.0%) Education 0.013* Secondary or below 10 (23.8%) 28 (48.3%) 38 (38.0%) Post-secondary or above 32 (76.2%) 30 (51.7%) 62 (62.0%) Mode of athlete type 0.379 Full-time 38 (90.5%) 49 (84.5%) 87 (87.0%) Part-time 4 (9.5%) 9 (15.5%) 13 (13.0%) Mean training hours per week 25.07 ± 7.84 25.47 ± 6.21 0.780 25.30 ± 6.91 Values are presented as mean and standard deviation for continuous or as number and percentage for categorical variables. P-value for independent sample t-test between male and female athletes for continuous and chi-square test for categorical variables. * p < 0.05; ** p < 0.01; *** p < 0.001. 3.2. Dieting methods among athletes Among the 100 participants, 4 (4.0%) reached the cut-off point for the disordered eating (EAT-26 score ≥ 20) (Table 3 ). The prevalence rate was higher in female athletes (7.1%) than in male athletes (1.7%), whereas there was no significant difference in the prevalence rates in both genders (Table 3 ). Thirty-nine participants (39.0%) reported that they have tried dieting methods in the past. Among them, 61.5% were female which was statistically higher than male (38.5%) (p < 0.01) (Table 3 ). Figure 1 illustrates the various types of dieting methods used by the participants. The most popular means were calorie restricted diet (59.0%), followed by low-carbohydrate diet (51.3%), intermittent caloric restriction (38.5%), low-fat diet (33.3%) and skipping breakfast (30.8%), whereas the vegetarian diet (0%) was the least common. In case of EAT-26 scores, Table 3 indicates that athletes those had ever tried dieting method showed significantly higher in EAT-26 scores than those had not tried dieting method (8.08 ± 9.03 vs 4.92 ± 5.73, p < 0.05). Table 3 Eating behaviours among Hong Kong athletes Female athletes (n = 42) Male athletes (n = 58) p-value Total (n = 100) Dieting method 0.002** Yes 24 (57.1%) 15 (25.9%) 39 (39.0%) No 18 (42.9%) 43 (74.1%) 61 (61.0%) Weight loss behaviours 0.403 Yes 3 (7.1%) 2 (3.4%) 5 (5.0%) No 39 (92.9%) 56 (96.6%) 95 (95.0%) Self-perceived body image 6.05 ± 1.77 6.28 ± 1.78 0.526 6.18 ± 1.77 EAT-26 total scores (score/78) 7.45 ± 8.11 5.21 ± 6.61 0.131 6.15 ± 7.32 EAT-26 score ≥ 20 (%) 0.172 Yes 3 (7.1%) 1 (1.7%) 4 (4.0%) No 39 (92.9%) 57 (98.3%) 96 (96.0%) Values are presented as mean and standard deviation for continuous or as number and percentage for categorical variables. P-value for independent sample t-test between male and female athletes for continuous and chi-square test for categorical variables. * p < 0.05; ** p < 0.01; *** p < 0.001. 3.3. Study variables associated with EAT-26 scores among athletes As shown in Table 4 , the results indicated that athletes those having lower body image (BI ≤ 5) had significantly higher EAT-26 scores than those having higher BS (BI > 5) (9.91 ± 8.89 vs 4.21 ± 5.51, p < 0.05). As shown in Table 5 , Pearson’s correlation analysis showed that a weak negative and significant association was identified between age and EAT-26 scores (r = -0.234, p < 0.05) (Fig. 2 ), and a moderate negative and significant association was identified between self-perceived BI and EAT-26 scores (r = -0.344, p 20 4.93 ± 5.41 p-value 0.055 Education Secondary or below 6.00 ± 7.16 Post-secondary or above 6.24 ± 7.48 p-value 0.874 BF% categories Athletes 5.89 ± 5.87 Fitness 5.91 ± 8.91 Average 7.85 ± 8.89 p-value 0.674 Self-perceived body image BI ≤ 5 (out of 9) 9.91 ± 8.89 BI > 5 (out of 9) 4.21 ± 5.51 p-value 0.001*** EAT-26 scores are presented as mean and standard deviation. P-value for independent sample t-test for two categorical variables and one-way ANOVA test and Duncan test as post-hoc for three or more categorical variables. * p < 0.05; ** p < 0.01; *** p < 0.001. Table 5 Person correlation between the study variable and EAT-26 scores Study variables Person correlation p-value Age -0.234 0.019* Height (cm) -0.091 0.367 Weight (kg) -0.113 0.263 Body fat mass (%) 0.093 0.358 Fat free mass (kg) -0.104 0.302 Training duration (hr) 0.074 0.466 Self-perceived body image -0.344 < 0.001*** * p < 0.05; ** p < 0.01; *** p < 0.001. 3.4. Prediction results of EAT-26 score by demographic characteristics From the stepwise multiple regression analysis, age and self-perceived BI emerged as significant predictors of EAT-26 (R 2 = 0.170, p < 0.05). According to multiple linear regression analysis, in the case of total EAT-26 score, age (β = -0.339, p < 0.001), and self-perceived BI (β = -0.226, p < 0.05) were negative predictors, as presented in Table 6 . Table 6 Multiple linear regression estimates for EAT-26 and subscale scores Study variables B SE β p-value Dependent variable: EAT-26 score (R 2 = 0.170) Constant 22.838 4.054 < 0.001*** Age − 1.406 0.384 − 0.339 < 0.001*** Self-perceived body image − 0.356 0.145 − 0.226 0.016* B: Unstandardized regression coefficient, SE: Standard Error, β: standardized regression coefficients. * p < 0.05; ** p < 0.01; *** p < 0.001. DISCUSSION This research indicates that the prevalence of DE among Hong Kong Chinese athletes is markedly lower (overall 4.0%: 1.7% in males and 7.1% in females) compared to the findings reported in previous meta-analyses, which documented higher prevalence rates (males: 16.8–17%; females: 24.1–30.0%) [ 16 – 18 ]. The significant disparity between these results and prior studies may be attributed to cultural differences, as the participants in the meta-analyses primarily originated from Western countries or Western Asia, including Iran, Israel, and Lebanon. However, studies specifically focusing on Asian athletes remain limited compared to those conducted on athletes from Western populations. In Hong Kong, earlier studies on DE have primarily targeted secondary school and university students. Mak and Lai (2011) [ 13 ] reported that 18.5% of boys and 26.6% of girls were found to be at risk of DE based on their EAT-26 scores (EAT-26 ≥ 20). These findings are broadly consistent with the meta-analyses conducted by Alfalahi et al. (2022) [ 16 ] and López-Gil et al. (2023) [ 17 ]. However, other local studies demonstrated significantly lower prevalence rates, with 6.5% of Chinese adolescent females [ 14 ] and 5.9% of female university students [ 15 ] categorized as high scorers on the EAT-26 scale. Notably, these figures are similar to the 7.1% prevalence identified in our research on female athletes in Hong Kong. However, no further updated local studies have been conducted in the area of DE or ED risk in Hong Kong for more than ten years. It is difficult to make a comparison of our findings with the local studies. Current literature suggests that cultural values emphasizing thinness or idealized body types—combined with the physical and psychological demands of competitive sports—may heighten the vulnerability to DE within this demographic. However, compared to findings from Western studies, it seems Hong Kong Chinese athletes might be better protected against DE or DEBs. This disparity highlights differences in the socio-cultural factors influencing the development of EDs between Chinese and Western athletes. Some studies, such as those by Chen and Swalm (1998) [ 19 ] and Kim et al. (2015) [ 20 ], suggest that Asian cultures, particularly Japanese and Chinese, often exhibit tendencies toward disorders that do not align with Western diagnostic frameworks. For instance, traditional Chinese cultural values associate fatness with good fortune, which may indicate a broader cultural acceptance of larger body types. Further research is needed to explore these cultural and contextual variations in depth. Furthermore, the findings of the present study align with prior research demonstrating elevated EAT-26 scores among adolescents and individuals with prior dieting experiences. This alignment highlights a persistent trend in the association between athletic engagement, especially among younger populations, and eating behaviors or tendencies influenced by dietary habits. In general, adolescents are particularly susceptible to the development of DE due to a confluence of biological, psychological, and social influences. The period of adolescence and early adulthood is marked by substantial physical and hormonal changes, often leading to increased self-consciousness and concerns regarding physical appearance. This vulnerability is further accentuated among young athletes and athletes who adopt dieting practices aimed at enhancing athletic performance or improving physical aesthetics, as they are more likely to experience heightened body dissatisfaction and a diminished perception of body image. As a result, they could be at an increased risk of developing DEBs. The results may suggest the need for different health education programs for young athletes and athletes who experience dieting and for those who do not. This approach may address their unique needs and promote better overall health outcomes. The main strengths of our study are the first study conducted in Hong Kong to investigate the prevalence of DE among local Chinese athletes, and it involved around 10% of target populations in HKSI. However, our study does have some limitations. It lacked control groups or non-athletes, focusing instead on comparing the prevalence of disordered eating with results from previous research. Moreover, this is not a random sampling method, as some athletes may choose not to participate in the study, leading to sampling bias. CONCLUSION This study revealed the prevalence of disordered eating from the Hong Kong Chinese athletes appeared to be lower than the global rates when scrutinized with self-reported questionnaires. It may reflect that Hong Kong Chinese athletes are more protected from DE or DEBs. As young athletes and those who had ever tried diet methods appeared to be more vulnerable to DEBs, appropriate educational intervention should be undertaken to promote the original dual concept of healthy body and mind. Declarations Authorship: Leo C.M. Cheung: Conceptualization, Methodology, Software, Validation, Investigation, Data Curation, Writing - Original Draft. Sophia L.Y. Li, James W.H. Sze, Gabriel T.K. Pun, Frankie P.L. Siu: Investigation, Reviewing and Editing. Dr. John O'Reilly, Dr. Bryan S.F. Lau, Dr. Margaret J. Kuo: Supervision. Clinical trial number: Not applicable. Consent to Publish declaration: not applicable. Ethics Approval: This study received approval from the Research Ethics Committee of HKU SPACE, following the guidelines and regulations outlined in the Operational Guidelines and Procedures of the Human Research Ethics Committee of the University. Informed Consent: The participants were fully informed consent of the study's purpose, procedures, risks, and benefits in a language they understand, and that they voluntarily gave consent. Conflict of interest: The authors declare no conflicts of interest regarding this manuscript. Data availability: Data is provided within the manuscript. Funding sources: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. References Ricciardelli, L. A., & McCabe, M. P. (2004). A biopsychosocial model of disordered eating and the pursuit of muscularity in adolescent boys. 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Kuo","email":"","orcid":"","institution":"Hong Kong Sports Institute","correspondingAuthor":false,"prefix":"","firstName":"Margaret","middleName":"J.","lastName":"Kuo","suffix":""}],"badges":[],"createdAt":"2026-02-10 11:04:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8839694/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8839694/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104779919,"identity":"9da72f0e-16f0-44e0-9ad8-8985dd2f71e5","added_by":"auto","created_at":"2026-03-17 07:48:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":52456,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWeight control methods used by athletes\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8839694/v1/d55e4271b35062722efb5c81.png"},{"id":104405762,"identity":"0ef93202-b26e-4a3b-a1be-3dfd4756fc7b","added_by":"auto","created_at":"2026-03-11 12:23:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":20645,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eScatter plot showing the relationship between EAT-26 scores and age\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8839694/v1/b0a18e7548292dcd8f9bdd8d.png"},{"id":104321419,"identity":"e36d93b4-ca43-46f6-96c7-186c4aedaef9","added_by":"auto","created_at":"2026-03-10 13:20:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":18378,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eScatter plot showing the relationship between EAT-26 scores and self-perceived body image\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8839694/v1/6c6b535c14b6884b29a2981d.png"},{"id":104785667,"identity":"82f24df5-7115-4aa0-ad0b-1a4a4e3388aa","added_by":"auto","created_at":"2026-03-17 08:12:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1024701,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8839694/v1/840f9544-94f4-4021-a157-d15889dc2b53.pdf"},{"id":104321422,"identity":"17499e3c-158c-4ca6-8d96-9caa34b9108d","added_by":"auto","created_at":"2026-03-10 13:20:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":50349,"visible":true,"origin":"","legend":"","description":"","filename":"ResearchethicalapprovalfromHKU.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8839694/v1/86a50a681288225818960473.pdf"},{"id":104321423,"identity":"1caa96c9-1566-4e62-84b3-ed0663c20f15","added_by":"auto","created_at":"2026-03-10 13:20:40","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":670693,"visible":true,"origin":"","legend":"","description":"","filename":"SurveyConsentForm.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8839694/v1/acf344b6f01c9b5667ca1de2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Cross-Sectional study of Eating Attitudes in Hong Kong Athletes","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe term disordered eating (DE) or disordered eating behaviours (DEBs) generally refers to symptoms that include the unnecessary or excessive use of weight loss methods like dieting or over-exercising, the inappropriate use of diuretics or laxatives, self-induced vomiting, and in some cases, episodes of periodic binge eating [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. A substantial body of literature exists on DE or DEBs among foreign athletes, though the findings are often inconsistent. Some studies indicate that athletes exhibit higher average levels of eating disorder psychopathology and a greater prevalence of DEBs when compared to non-athletes (e.g., Fortes, L. de S., \u003cem\u003eet al\u003c/em\u003e., 2014 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]; Holm-Denoma \u003cem\u003eet al\u003c/em\u003e., 2009 [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]; Sundgot-Borgen \u0026amp; Torstveit, 2004 [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]). However, some studies, such as those by Martinsen \u003cem\u003eet al\u003c/em\u003e. (2010) and Reinking \u0026amp; Alexander (2005), have shown contrasting findings, reporting either higher body satisfaction among athletes or no significant differences between athletes and non-athletes, as evidenced by works like Chapman and Woodman (2016) or Rosendahl \u003cem\u003eet al\u003c/em\u003e. (2009). Moreover, there is a paucity of research on the prevalence of DEBs among Asian athletes, particularly in Chinese population. The purpose of this study was to determine the prevalence of DE among Hong Kong Chinese athletes and also examine the associations between EAT-26 scores and socio-demographic variables.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Experimental design\u003c/h2\u003e \u003cp\u003eThis study was conducted as a cross-sectional survey utilizing the EAT-26 questionnaire as described in Section \u003cspan refid=\"Sec5\" class=\"InternalRef\"\u003e2.3\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Participants\u003c/h2\u003e \u003cp\u003eAll athletes were invited to complete the questionnaire via an email sent to all coaches at The Hong Kong Sports Institute (HKSI). The participants were provided with full details of the study, including its purpose, potential risks, benefits, and their right to withdraw at any time. After being thoroughly informed, they willingly consented to participate by signing a consent form. In the end, the study examined 100 Chinese athletes, aged between 16 and 36. The inclusion and exclusion criteria for the participants are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\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\u003eThe inclusion and exclusion criteria for the participants\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=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eThe inclusion criteria for the participants were the following:\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(a) providing personal and parental/ guardian consent,\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(b) able to complete the questionnaires, and\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(c) a full-time or part-time athletes under training at the (THE NAME OF TRAINING INSTITUTE).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eThe exclusion criteria for the participants were the following:\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(a) not providing personal and parental consent,\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(b) unable to provide information (i.e., complete the study\u0026rsquo;s questionnaires), or\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(c) having health-related problems or diagnosis (e.g., physical disabilities, diabetes mellitus, gastrointestinal diseases etc).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Questionnaires\u003c/h2\u003e \u003cp\u003eThe questionnaire was utilized to gather data from February 22, 2024, to April 22, 2024, at HKSI. It comprised three sections:\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1. Socio-demographic characteristics of participants\u003c/h2\u003e \u003cp\u003eThe initial section focused on the demographic characteristics of the participants, covering details such as age, gender, year of birth, country of citizenship, education level, type of sports, along with their regular training frequency and duration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2. Self-perceived body image, dieting methods and eating attitudes test\u003c/h2\u003e \u003cp\u003eThe second section included questions regarding their dietary practices and the Eating Attitudes Test (EAT-26) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The EAT-26 is a 26-item assessment designed to evaluate disordered eating attitudes and behaviours, which was incorporated into the questionnaire. In this study, the modified Chinese version of the EAT-26 [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], as outlined by Mak, K. K., and Lai, C. M. (2011) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], was utilized and described in detail. This tool has shown strong validity and reliability among secondary school students and undergraduates in Hong Kong [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Additionally, participants rated their self-perceived body image (BI) using a numerical scale ranging from 0 (worst) to 9 (best). They were also asked to select their body type from four categories: athlete, fitness, average, and obese.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.3.3. Anthropometric characteristics of participants\u003c/h2\u003e \u003cp\u003eThe anthropometric characteristics of participants included height, weight, BF% and percentage of lean body mass were recorded. The participants\u0026rsquo; standing heights were measured in bare feet to the nearest 0.1 cm with a tape fixed on a vertical wall. Their weights were measured with light clothes to the nearest 0.1 kg using a bioelectrical impedance analysis (BIA) (InBody 720, Biospace, Korea). Moreover, body fat percentage and percentage of lean body mass were obtained by the BIA.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Statistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using the Statistical Packages for Social Sciences (SPSS) version 31.0 (SPSS Inc., Chicago, IL, USA). For all analyses, the level of statistical significance was set at 0.05. Continuous variables were presented as means with standard deviation, while categorical variables were presented as frequencies and percentages. Data were analyzed using Independent samples t-tests, χ\u003csup\u003e2\u003c/sup\u003e analysis, one-way ANOVA, Pearson\u0026rsquo;s correlation analysis and multiple linear regression models.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Demographical and anthropometric data of all participants\u003c/h2\u003e \u003cp\u003eOf the 102 eligible subjects, two were excluded because of incomplete questionnaires. A total of 100 HKSI athletes were included in the final analysis. The sample consisted of participants male (58.0%) appeared to be in the majority, identified as Hong Kong Chinese residents (99.0%), college graduates (62.0%), and the mean (SD) age was 22.5 (4.66) years. Male athletes were significantly heavier, taller and had higher lean body mass as well as lower body fat percentage than female athletes (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The comparisons were made between male and female participants with results shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic and anthropometric characteristics\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale athletes\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;42)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eathletes\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;58)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;100)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.95\u0026thinsp;\u0026plusmn;\u0026thinsp;4.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.16\u0026thinsp;\u0026plusmn;\u0026thinsp;4.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.49\u0026thinsp;\u0026plusmn;\u0026thinsp;4.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e163.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e174.7\u0026thinsp;\u0026plusmn;\u0026thinsp;6.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt; 0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e170.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.75\u0026thinsp;\u0026plusmn;\u0026thinsp;4.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.67\u0026thinsp;\u0026plusmn;\u0026thinsp;8.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt; 0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62.24\u0026thinsp;\u0026plusmn;\u0026thinsp;9.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody fat (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.03\u0026thinsp;\u0026plusmn;\u0026thinsp;4.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.97\u0026thinsp;\u0026plusmn;\u0026thinsp;4.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt; 0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.93\u0026thinsp;\u0026plusmn;\u0026thinsp;5.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLean body mass (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.34\u0026thinsp;\u0026plusmn;\u0026thinsp;6.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.47\u0026thinsp;\u0026plusmn;\u0026thinsp;6.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.69\u0026thinsp;\u0026plusmn;\u0026thinsp;10.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBF% categories\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=\"char\" char=\".\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.131\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\u003eAthletes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (47.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (60.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55 (55.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFitness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (42.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (24.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32 (32.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (9.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (15.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13 (13.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHong Kong resident\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=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.392\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 (98.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99 (99.0%)\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\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=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.013*\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\u003eSecondary or below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (23.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (48.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38 (38.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-secondary or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (76.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (51.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62 (62.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMode of athlete type\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=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.379\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\u003eFull-time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (90.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49 (84.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e87 (87.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePart-time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (9.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (15.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13 (13.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean training hours per week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.07\u0026thinsp;\u0026plusmn;\u0026thinsp;7.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.47\u0026thinsp;\u0026plusmn;\u0026thinsp;6.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.30\u0026thinsp;\u0026plusmn;\u0026thinsp;6.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eValues are presented as mean and standard deviation for continuous or as number and percentage for categorical variables. P-value for independent sample t-test between male and female athletes for continuous and chi-square test for categorical variables. * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Dieting methods among athletes\u003c/h2\u003e \u003cp\u003eAmong the 100 participants, 4 (4.0%) reached the cut-off point for the disordered eating (EAT-26 score\u0026thinsp;\u0026ge;\u0026thinsp;20) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The prevalence rate was higher in female athletes (7.1%) than in male athletes (1.7%), whereas there was no significant difference in the prevalence rates in both genders (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Thirty-nine participants (39.0%) reported that they have tried dieting methods in the past. Among them, 61.5% were female which was statistically higher than male (38.5%) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the various types of dieting methods used by the participants. The most popular means were calorie restricted diet (59.0%), followed by low-carbohydrate diet (51.3%), intermittent caloric restriction (38.5%), low-fat diet (33.3%) and skipping breakfast (30.8%), whereas the vegetarian diet (0%) was the least common. In case of EAT-26 scores, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e indicates that athletes those had ever tried dieting method showed significantly higher in EAT-26 scores than those had not tried dieting method (8.08\u0026thinsp;\u0026plusmn;\u0026thinsp;9.03 vs 4.92\u0026thinsp;\u0026plusmn;\u0026thinsp;5.73, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\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\u003eEating behaviours among Hong Kong athletes\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=\"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 \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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale athletes\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;42)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eathletes\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;58)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;100)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDieting method\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=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.002**\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24 (57.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15 (25.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39 (39.0%)\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\u003e18 (42.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43 (74.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e61 (61.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight loss behaviours\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=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.403\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5 (5.0%)\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\u003e39 (92.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56 (96.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e95 (95.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-perceived body image\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.05\u0026thinsp;\u0026plusmn;\u0026thinsp;1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.28\u0026thinsp;\u0026plusmn;\u0026thinsp;1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.18\u0026thinsp;\u0026plusmn;\u0026thinsp;1.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEAT-26 total scores (score/78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.45\u0026thinsp;\u0026plusmn;\u0026thinsp;8.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.21\u0026thinsp;\u0026plusmn;\u0026thinsp;6.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.15\u0026thinsp;\u0026plusmn;\u0026thinsp;7.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEAT-26 score\u0026thinsp;\u0026ge;\u0026thinsp;20 (%)\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=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.172\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4 (4.0%)\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\u003e39 (92.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57 (98.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e96 (96.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eValues are presented as mean and standard deviation for continuous or as number and percentage for categorical variables. P-value for independent sample t-test between male and female athletes for continuous and chi-square test for categorical variables. * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Study variables associated with EAT-26 scores among athletes\u003c/h2\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the results indicated that athletes those having lower body image (BI\u0026thinsp;\u0026le;\u0026thinsp;5) had significantly higher EAT-26 scores than those having higher BS (BI\u0026thinsp;\u0026gt;\u0026thinsp;5) (9.91\u0026thinsp;\u0026plusmn;\u0026thinsp;8.89 vs 4.21\u0026thinsp;\u0026plusmn;\u0026thinsp;5.51, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). As shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Pearson\u0026rsquo;s correlation analysis showed that a weak negative and significant association was identified between age and EAT-26 scores (r = -0.234, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), and a moderate negative and significant association was identified between self-perceived BI and EAT-26 scores (r = -0.344, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;3).\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\u003eAnalysis of participants\u0026rsquo; characteristics among the EAT-26 scores\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=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal EAT-26 score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.77\u0026thinsp;\u0026plusmn;\u0026thinsp;9.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.93\u0026thinsp;\u0026plusmn;\u0026thinsp;5.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary or below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.00\u0026thinsp;\u0026plusmn;\u0026thinsp;7.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost-secondary or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.24\u0026thinsp;\u0026plusmn;\u0026thinsp;7.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.874\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eBF% categories\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAthletes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.89\u0026thinsp;\u0026plusmn;\u0026thinsp;5.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFitness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.91\u0026thinsp;\u0026plusmn;\u0026thinsp;8.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.85\u0026thinsp;\u0026plusmn;\u0026thinsp;8.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.674\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSelf-perceived body image\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBI\u0026thinsp;\u0026le;\u0026thinsp;5\u003c/p\u003e \u003cp\u003e(out of 9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.91\u0026thinsp;\u0026plusmn;\u0026thinsp;8.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBI\u0026thinsp;\u0026gt;\u0026thinsp;5\u003c/p\u003e \u003cp\u003e(out of 9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.21\u0026thinsp;\u0026plusmn;\u0026thinsp;5.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eEAT-26 scores are presented as mean and standard deviation. P-value for independent sample t-test for two categorical variables and one-way ANOVA test and Duncan test as post-hoc for three or more categorical variables. * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\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=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePerson correlation between the study variable and EAT-26 scores\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\u003eStudy variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePerson correlation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.019*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.367\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.263\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody fat mass (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.358\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat free mass (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTraining duration (hr)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.466\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-perceived body image\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e* p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Prediction results of EAT-26 score by demographic characteristics\u003c/h2\u003e \u003cp\u003eFrom the stepwise multiple regression analysis, age and self-perceived BI emerged as significant predictors of EAT-26 (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.170, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). According to multiple linear regression analysis, in the case of total EAT-26 score, age (β = -0.339, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and self-perceived BI (β = -0.226, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were negative predictors, as presented in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\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 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultiple linear regression estimates for EAT-26 and subscale scores\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=\"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 \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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eDependent variable: \u003cb\u003eEAT-26 score\u003c/b\u003e (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.170)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22.838\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;1.406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;0.339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-perceived body image\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;0.356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;0.226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.016*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eB: Unstandardized regression coefficient, SE: Standard Error, β: standardized regression coefficients. * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis research indicates that the prevalence of DE among Hong Kong Chinese athletes is markedly lower (overall 4.0%: 1.7% in males and 7.1% in females) compared to the findings reported in previous meta-analyses, which documented higher prevalence rates (males: 16.8\u0026ndash;17%; females: 24.1\u0026ndash;30.0%) [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The significant disparity between these results and prior studies may be attributed to cultural differences, as the participants in the meta-analyses primarily originated from Western countries or Western Asia, including Iran, Israel, and Lebanon. However, studies specifically focusing on Asian athletes remain limited compared to those conducted on athletes from Western populations. In Hong Kong, earlier studies on DE have primarily targeted secondary school and university students. Mak and Lai (2011) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] reported that 18.5% of boys and 26.6% of girls were found to be at risk of DE based on their EAT-26 scores (EAT-26\u0026thinsp;\u0026ge;\u0026thinsp;20). These findings are broadly consistent with the meta-analyses conducted by Alfalahi et al. (2022) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and L\u0026oacute;pez-Gil et al. (2023) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, other local studies demonstrated significantly lower prevalence rates, with 6.5% of Chinese adolescent females [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and 5.9% of female university students [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] categorized as high scorers on the EAT-26 scale. Notably, these figures are similar to the 7.1% prevalence identified in our research on female athletes in Hong Kong. However, no further updated local studies have been conducted in the area of DE or ED risk in Hong Kong for more than ten years. It is difficult to make a comparison of our findings with the local studies.\u003c/p\u003e \u003cp\u003eCurrent literature suggests that cultural values emphasizing thinness or idealized body types\u0026mdash;combined with the physical and psychological demands of competitive sports\u0026mdash;may heighten the vulnerability to DE within this demographic. However, compared to findings from Western studies, it seems Hong Kong Chinese athletes might be better protected against DE or DEBs. This disparity highlights differences in the socio-cultural factors influencing the development of EDs between Chinese and Western athletes. Some studies, such as those by Chen and Swalm (1998) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] and Kim et al. (2015) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], suggest that Asian cultures, particularly Japanese and Chinese, often exhibit tendencies toward disorders that do not align with Western diagnostic frameworks. For instance, traditional Chinese cultural values associate fatness with good fortune, which may indicate a broader cultural acceptance of larger body types. Further research is needed to explore these cultural and contextual variations in depth. Furthermore, the findings of the present study align with prior research demonstrating elevated EAT-26 scores among adolescents and individuals with prior dieting experiences. This alignment highlights a persistent trend in the association between athletic engagement, especially among younger populations, and eating behaviors or tendencies influenced by dietary habits. In general, adolescents are particularly susceptible to the development of DE due to a confluence of biological, psychological, and social influences. The period of adolescence and early adulthood is marked by substantial physical and hormonal changes, often leading to increased self-consciousness and concerns regarding physical appearance. This vulnerability is further accentuated among young athletes and athletes who adopt dieting practices aimed at enhancing athletic performance or improving physical aesthetics, as they are more likely to experience heightened body dissatisfaction and a diminished perception of body image. As a result, they could be at an increased risk of developing DEBs. The results may suggest the need for different health education programs for young athletes and athletes who experience dieting and for those who do not. This approach may address their unique needs and promote better overall health outcomes.\u003c/p\u003e \u003cp\u003eThe main strengths of our study are the first study conducted in Hong Kong to investigate the prevalence of DE among local Chinese athletes, and it involved around 10% of target populations in HKSI. However, our study does have some limitations. It lacked control groups or non-athletes, focusing instead on comparing the prevalence of disordered eating with results from previous research. Moreover, this is not a random sampling method, as some athletes may choose not to participate in the study, leading to sampling bias.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study revealed the prevalence of disordered eating from the Hong Kong Chinese athletes appeared to be lower than the global rates when scrutinized with self-reported questionnaires. It may reflect that Hong Kong Chinese athletes are more protected from DE or DEBs. As young athletes and those who had ever tried diet methods appeared to be more vulnerable to DEBs, appropriate educational intervention should be undertaken to promote the original dual concept of healthy body and mind.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthorship:\u0026nbsp;\u003c/strong\u003eLeo C.M. Cheung: Conceptualization, Methodology, Software, Validation, Investigation, Data Curation, Writing - Original Draft.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSophia L.Y. Li, James W.H. Sze, Gabriel T.K. Pun, Frankie P.L. Siu: Investigation, Reviewing and Editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDr. John O'Reilly, Dr. Bryan S.F. Lau, Dr. Margaret J. Kuo: Supervision. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish declaration:\u003c/strong\u003e not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval:\u0026nbsp;\u003c/strong\u003eThis study received approval from the Research Ethics Committee of HKU SPACE, following the guidelines and regulations outlined in the Operational Guidelines and Procedures of the Human Research Ethics Committee of the University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent:\u0026nbsp;\u003c/strong\u003eThe participants were fully informed consent of the study's purpose, procedures, risks, and benefits in a language they understand, and that they voluntarily gave consent.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u0026nbsp;\u003c/strong\u003eThe authors declare no conflicts of interest regarding this manuscript.\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u0026nbsp;\u003c/strong\u003eData is provided within the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding sources:\u0026nbsp;\u003c/strong\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003cem\u003e\u003cbr\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRicciardelli, L. A., \u0026amp; McCabe, M. P. (2004). A biopsychosocial model of disordered eating and the pursuit of muscularity in adolescent boys. Psychological bulletin, 130(2), 179\u0026ndash;205. https://doi.org/10.1037/0033-2909.130.2.179\u003c/li\u003e\n\u003cli\u003eToni, G., Berioli, M. G., Cerquiglini, L., Ceccarini, G., Grohmann, U., Principi, N., \u0026amp; Esposito, S. (2017). Eating Disorders and Disordered Eating Symptoms in Adolescents with Type 1 Diabetes. Nutrients, 9(8), 906. https://doi.org/10.3390/nu9080906\u003c/li\u003e\n\u003cli\u003eFortes, L.deS., Kakeshita, I. S., Almeida, S. S., Gomes, A. R., \u0026amp; Ferreira, M. E. (2014). Eating behaviours in youths: A comparison between female and male athletes and non-athletes. Scandinavian journal of medicine \u0026amp; science in sports, 24(1), e62\u0026ndash;e68. https://doi.org/10.1111/sms.12098\u003c/li\u003e\n\u003cli\u003eHolm-Denoma, J. M., Scaringi, V., Gordon, K. H., Van Orden, K. A., \u0026amp; Joiner, T. E., Jr, 2009. Eating disorder symptoms among undergraduate varsity athletes, club athletes, independent exercisers, and nonexercisers. The International journal of eating disorders, 42(1), pp.47\u0026ndash;53. https://doi.org/10.1002/eat.20560\u003c/li\u003e\n\u003cli\u003eSundgot-Borgen, J., \u0026amp; Torstveit, M. K., 2004. Prevalence of eating disorders in elite athletes is higher than in the general population. Clinical journal of sport medicine : official journal of the Canadian Academy of Sport Medicine, 14(1), pp.25\u0026ndash;32. https://doi.org/10.1097/00042752-200401000-00005\u003c/li\u003e\n\u003cli\u003eMartinsen, M., Bratland-Sanda, S., Eriksson, A. K., \u0026amp; Sundgot-Borgen, J., 2010. Dieting to win or to be thin? A study of dieting and disordered eating among adolescent elite athletes and non-athlete controls. British journal of sports medicine, 44(1), pp.70\u0026ndash;76. https://doi.org/10.1136/bjsm.2009.068668\u003c/li\u003e\n\u003cli\u003eReinking, M. F., \u0026amp; Alexander, L. E., 2005. Prevalence of Disordered-Eating Behaviors in Undergraduate Female Collegiate Athletes and Nonathletes. Journal of athletic training, 40(1), pp.47\u0026ndash;51\u003c/li\u003e\n\u003cli\u003eChapman, J., \u0026amp; Woodman, T. (2016). Disordered eating in male athletes: a meta-analysis. Journal of sports sciences, 34(2), 101\u0026ndash;109. https://doi.org/10.1080/02640414.2015.1040824\u003c/li\u003e\n\u003cli\u003eRosendahl, J., Bormann, B., Aschenbrenner, K., Aschenbrenner, F., \u0026amp; Strauss, B. (2009). Dieting and disordered eating in German high school athletes and non‐athletes. Scandinavian journal of medicine \u0026amp; science in sports, 19(5), 731-739.\u003c/li\u003e\n\u003cli\u003eGarner, D. M., \u0026amp; Garfinkel, P. E. (1979). The Eating Attitudes Test: an index of the symptoms of anorexia nervosa. Psychological medicine, 9(2), 273\u0026ndash;279. https://doi.org/10.1017/s0033291700030762\u003c/li\u003e\n\u003cli\u003eJin, L., Han, W., \u0026amp; Zheng, Z. (2023). Attentional vigilance of food information in disordered eating behaviors. Frontiers in Psychiatry, 14, 1108995.\u003c/li\u003e\n\u003cli\u003eKang, Q., Chan, R. C. K., Li, X., Arcelus, J., Yue, L., Huang, J., Gu, L., Fan, Q., Zhang, H., Xiao, Z., \u0026amp; Chen, J. (2017). Psychometric Properties of the Chinese Version of the Eating Attitudes Test in Young Female Patients with Eating Disorders in Mainland China.\u003c/li\u003e\n\u003cli\u003eMak, K. K., \u0026amp; Lai, C. M., 2011. The risks of disordered eating in Hong Kong adolescents. Eating and weight disorders: EWD, 16(4), pp.289\u0026ndash;292. https://doi.org/10.1007/BF03327475\u003c/li\u003e\n\u003cli\u003eLee, A. M., \u0026amp; Lee, S. (1996). Disordered eating and its psychosocial correlates among Chinese adolescent females in Hong Kong. The International journal of eating disorders, 20(2), 177\u0026ndash;183. https://doi.org/10.1002/(SICI)1098-108X(199609)20:2\u0026lt;177::AID-EAT8\u0026gt;3.0.CO;2-D\u003c/li\u003e\n\u003cli\u003eLee, S., Leung, T., Lee, A. M., Yu, H., \u0026amp; Leung, C. M., 1996. Body dissatisfaction among Chinese undergraduates and its implications for eating disorders in Hong Kong. The International journal of eating disorders, 20(1), pp.77\u0026ndash;84. https://doi.org/10.1002/(SICI)1098-108X(199607)20:1\u0026lt;77::AID-EAT9\u0026gt;3.0.CO;2-1\u003c/li\u003e\n\u003cli\u003eAlfalahi, M., Mahadevan, S., Balushi, R. A., Chan, M. F., Saadon, M. A., Al-Adawi, S., \u0026amp; Qoronfleh, M. W. (2022). Prevalence of eating disorders and disordered eating in Western Asia: a systematic review and meta-Analysis. Eating disorders, 30(5), 556\u0026ndash;585. https://doi.org/10.1080/10640266.2021.1969495\u003c/li\u003e\n\u003cli\u003eL\u0026oacute;pez-Gil, J. F., Garc\u0026iacute;a-Hermoso, A., Smith, L., Firth, J., Trott, M., Mesas, A. E., Jim\u0026eacute;nez-L\u0026oacute;pez, E., Guti\u0026eacute;rrez-Espinoza, H., T\u0026aacute;rraga-L\u0026oacute;pez, P. J., \u0026amp; Victoria-Montesinos, D. (2023). Global Proportion of Disordered Eating in Children and Adolescents: A Systematic Review and Meta-analysis. JAMA pediatrics, 177(4), 363\u0026ndash;372. https://doi.org/10.1001/jamapediatrics.2022.5848\u003c/li\u003e\n\u003cli\u003eMassaldjieva, R. I., Bakova, D., Semerdjieva, M., Torniova, B., Tilov, B., \u0026amp; Raykova, E. (2017). Disordered eating attitudes and behaviors: gender differences in adolescence and young adulthood. J. Women\u0026rsquo;s Health Care, 6(368), 2167-0420.\u003c/li\u003e\n\u003cli\u003eChen, W., \u0026amp; Swalm, R. L. (1998). Chinese and American college students\u0026apos; body-image: perceived body shape and body affect. Perceptual and motor skills, 87(2), 395\u0026ndash;403. https://doi.org/10.2466/pms.1998.87.2.395\u003c/li\u003e\n\u003cli\u003eKim, S. Y., Herrman, A., Song, H., Lim, T. S., Cramer, E., Ahn, S., Kim, J., Ota, H., Kim, H. J., \u0026amp; Kim, J. (2016). Exploring cultural differences in women\u0026apos;s body weight perception: The impact of self-construal on perceived overweight and engagement in health activities. Health care for women international, 37(11), 1203\u0026ndash;1220. https://doi.org/10.1080/07399332.2015.1107070\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"discpsy","sideBox":"Learn more about [Discover Psychology](https://www.springer.com/44202)","snPcode":"","submissionUrl":"","title":"Discover Psychology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Hong Kong athletes, HK athletes, disordered eating, EAT-26","lastPublishedDoi":"10.21203/rs.3.rs-8839694/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8839694/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNumerous studies have explored disordered eating (DE) in athletes, yet their findings frequently conflict. This research focused on examining the prevalence of DE among HK Chinese athletes. A sample of 100 athletes participated in the study, which employed a cross-sectional design using the EAT-26 questionnaire. The results revealed a prevalence rate of 4.0%, notably lower than global averages. Athletes with dieting experience scored higher on EAT-26 compared to those without (8.08 ± 9.03 vs. 4.92 ± 5.73, p \u0026lt; 0.05). Lower body image (BI ≤ 5 out of 9) was associated with higher EAT-26 scores compared to higher body image (BI \u0026gt; 5) (9.91 ± 8.89 vs. 4.21 ± 5.51, p \u0026lt; 0.05). Pearson’s correlation analysis demonstrated that age and EAT-26 scores showed a weak negative correlation (r = -0.234, p \u0026lt; 0.05), while self-perceived BI had a moderate negative correlation with EAT-26 scores (r = -0.344, p \u0026lt; 0.01). Regression analysis identified age (β = -0.339, p \u0026lt; 0.001) and self-perceived BI (β = -0.226, p \u0026lt; 0.05) as predictors of EAT-26 scores. Results align with international studies indicating higher scores among younger athletes and those with dieting history, suggesting tailored health education programs for different groups may be beneficial.\u003c/p\u003e\n\u003cp\u003eLevel of Evidence: Level V, Descriptive Study.\u003c/p\u003e","manuscriptTitle":"A Cross-Sectional study of Eating Attitudes in Hong Kong Athletes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-10 13:20:33","doi":"10.21203/rs.3.rs-8839694/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-14T22:35:26+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-15T14:56:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-14T22:26:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-10T14:39:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-06T18:06:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"190371414402217884208038874570464209406","date":"2026-03-06T12:25:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"296021509682971390526555707626678844304","date":"2026-03-06T05:56:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"240507297528150897621735790907936851927","date":"2026-03-05T20:35:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"237616566913337839131108141974600739631","date":"2026-03-04T13:18:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-04T12:12:05+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-23T08:13:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-20T12:52:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Psychology","date":"2026-02-20T12:47:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"discpsy","sideBox":"Learn more about [Discover Psychology](https://www.springer.com/44202)","snPcode":"","submissionUrl":"","title":"Discover Psychology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f0c51939-7234-4c05-b785-4f59243379ea","owner":[],"postedDate":"March 10th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-14T22:35:26+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T22:38:42+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-10 13:20:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8839694","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8839694","identity":"rs-8839694","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}