Prevalence and predictors of Eating Disorders’ risk in medical students at Damascus University: a cross-sectional study

Prevalence and predictors of Eating Disorders’ risk in medical students at Damascus University: a cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prevalence and predictors of Eating Disorders’ risk in medical students at Damascus University: a cross-sectional study Lujain Nahas, Lama Mohamad, Jameel Soqia, Laila Yakoub Agha, Mehdy Nahas, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4232158/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: Eating disorders are among the most important psychiatric problems, and they are triggered by a complex network of factors. These disorders also seem to affect medical field students far more than others. Objective: To determine the point prevalence of the risk of disordered eating behaviors in medical students at Damascus University and to study the possible reasons for this risk. Methods: A cross-sectional study at Damascus University, Faculty of Medicine, was carried out between October and December of 2023. Data were collected from randomly sampled students from the second to sixth years via online surveys using the Eating Attitudes Test-26 (EAT-26) and the Sick, Control, One, Fat, Food (SCOFF) questionnaires as primary screening tools . Binary logistic regression was used to determine possible influencing factors on eating disorders. Results: Among the 829 participants, 11.3% had a greater risk of disordered eating behavior according to the EAT-26, and 20.3% had a greater risk according to the SCOFF. The average age was 21.29 years (1.76), and 67.6% of the participants’ body mass index (BMI) was within the normal range. Preclinical-aged female students (OR=1.89, p=0.009 for SCOFF and OR=0.66, p=0.017 for SCOFF) were at greater risk. Another important correlation was found between BMI and exposure to recent stressors (p<0.001 in both comparisons). However, age did not demonstrate any traceable importance (p=0.17) in addition to living or marital status (p=0.13 and p=0.18, respectively). Conclusion: There is a risk of developing eating disorders among medical students, which might go unrecognized due to a lack of awareness of the importance of their detection. This risk also seems to stem from multiple risk factors that still require further research. Improving the relationship with psychological disorders and working on changing their rooted stigmatization will most likely prevent the escalation of these disorders in the future. eating disorders medical students BMI eating behaviors risk factors What is already known about the subject Eating disorders are serious mental health conditions that can have a significant impact on a person's physical and emotional well-being. We were interested in understanding the prevalence of these disorders in medical students because they are known to be at greater risk due to the stress and pressure of their studies, among other factors. What this study adds: By understanding how common eating disorders are among medical students, healthcare professionals can better identify and support those who may be struggling. Additionally, addressing eating disorders in medical students can help prevent future healthcare providers from experiencing these challenges themselves, ultimately improving the overall well-being of the healthcare workforce. Ultimately, this research has the potential to improve the mental health and overall well-being of medical students, leading to better patient care and outcomes in the long run. Introduction Eating disorders (EDs) consist of a spectrum of presentations for which a number of factors, such as genetic and environmental factors, are combined to create a predisposition ( 1 ). This may be a subthreshold risk or a full-on disorder that disrupts life and threatens high levels of mortality, psychological distress and impairment. However, there are relatively fewer studies in this field than in the field of other mental disorders ( 2 , 3 ). A large study identified a number of possible triggers and participating factors and grouped them into nine categories: genetics, gastrointestinal microbiota and autoimmune reactions, childhood and early adolescent exposures, personality traits and comorbid health conditions, gender, socioeconomic status, ethnic minority, body image and social influence and elite sports. This implies a vast variety of related factors that require testing for possible and degree of influence in different populations ( 4 ). Compared to a global general population prevalence of 5.7% and 2.2% in females and males, respectively, a 10.4% prevalence was found among medical students who are generally more predisposed to disordered eating behaviors, and this is attributable to various factors and coexisting or preceding elements (5,6). This observation highlights multiple added predisposing factors that medical students are subjected to in addition to generally noted factors, as they are generally recognized to be more susceptible to psychological distress ( 7 ). In Syria, there is a shortage of research in terms of providing a recent estimate of prevalence, with gross meta-analyses finding a (22.3%) prevalence percentage in 2022 depending on only one study ( 8 ). This paucity of research and delay of recognition is also met with minimal recognition of the mental health sector in Syrian society, as it is generally stigmatized and marginalized, which makes this study necessary. Furthermore, to our knowledge, no similar studies concerning Syrian medical students have been conducted, which makes ours the first to study the prevalence of risk and associated predisposing factors and to compare our findings with international literature to determine how our results align. Methods Study design: This cross-sectional study took place in the Faculty of Medicine of Damascus University in Syria to inspect the prevalence and predictors of the risk of disordered eating behaviors using online surveys over a three-month period (October to December 2023). Test scores were used to classify high-risk and low-risk groups and to understand the differences between them and how both groups correlate wit \(\) h the studied risk factors. Sample size and participants: The sample size was calculated using Robert Mason’s formula (M = 5991, s 2 = 0.00065, p = q = 0.50), and a minimum size of n = 374 was recommended ( 9 ). The number of participants from each year and the overall number used in the formula can be seen in Table 1 . \(\) \(n=\frac{M}{\left[({S}^{2 }\times \left(M-1\right))÷pq\right]+1 }\) Table 1 Sample size and overall population year Total number of students Required number for the sample Our sample 2 1300 81 196 3 1150 72 131 4 1100 68 126 5 1175 73 196 6 1266 80 180 total 5991 374 829 All male and female students from the second to sixth years at Damascus University were eligible to participate, and students were chosen randomly from private study groups for each year. They were asked to complete an online survey sent to each of them with a personally customized message between 6:00 and 9:00 PM over a period of three months spanning from October to December 2023. The first year was excluded because it encompasses a large number of students who will eventually be sorted into three medical faculties (Faculty of Pharmacy, Dentistry and Medicine). The response rate was estimated at 87.81%, as 829 students completed the survey from a total of 944 messages sent. Measurements The survey included two eating disorder risk assessment questionnaires: the Eating Attitude Test-26 (EAT-26) and Sick, Control, One, Fat, Food (SCOFF). At the beginning of the survey, participants were asked to answer demographic questions concerning exposure to recent stressors, past or current use of mental health services and medications, current school year, living circumstances, and medical and family histories of mental and eating disorders. Body mass index (BMI) was subsequently calculated using the required height and weight. The EAT-26 is a shorter version of the 40-item questionnaire and is self-administered. It is used for the determination of individuals with high ED risk. It starts with 26 questions. Each item is scored on a six-point scale ranging from always to never. It can be divided into three subgroups: dieting questions, bulimia and food preoccupation and oral control. The total sum of the Eat-26 scores ranges from 0 to 78. With a cutoff point of 20, a score of 20 or higher is classified as high risk ( 10 ). The second part investigated behaviors related to weight-control patterns, including binge eating episodes, self-induced vomiting, the use of laxatives or diuretics and excessive exercise to control shape and weight, in addition to drastic weight loss of more than 9 kilograms over the past 6 months. The EAT-26 is considered a psychometrically reliable instrument (Cronbach’s α = 0.90) ( 11 ). The validated Arabic version of the EAT-10 was used in this study ( 12 ). The SCOFF questionnaire is another widely used self-administered screening questionnaire and is among the most sensitive ( 13 ). The results of these five questions were added, and a score of 2 or more was considered high risk ( 14 ). This tool is credible and has reliable psychometric properties (kappa statistic = 0.73 to 0.82) ( 15 ). A validated Arabic version was also used in our study ( 16 ). Ethical considerations Students who agreed to participate were asked to complete an online questionnaire administered personally to each participant. Informed consent was obtained, and participants were reminded that their responses would not be shared or used outside the scope of this research. The study was approved by the ethical committee of Damascus University (ID number: 241023-130, session 8 on 24/10/2024) and was conducted in accordance with the ethical standards of the Helsinki II Declaration about informed consent, voluntariness and anonymity. Surveys and questionnaires containing no information were used to identify participants; henceforth, their responses remained anonymous. Participants understood that their contribution was purely voluntary. Data Analysis: All analyses were performed using IBM SPSS Statistics for Windows, version 25 (IBM Corp., Armonk, N.Y., USA). Google Forms were used to collect the data online. Prevalence rates were calculated based on the recommended cut-offs for Eat-26 and SCOFF. Separate logistic regressions were conducted to identify predictors of high ED risk according to the Eat-26 and SCOFF scores. In each regression, sex, age, year of medical school, BMI, recent stressors, place of residence, marital status, visiting a health care professional, taking psychiatric medication, personal positive mental history and positive family history of eating disorders were entered as predictors in step 1. Results Demographic characteristics Overall, of the 829 participating students , 48.9% were males and 51.1% were females. The ages ranged from 18 to 30 years, with a mean of 21.29 years (SD = 1.76). The BMI of the participants ranged from 14.04 to 50.26, with a mean of 22.56 (SD = 3.79). The majority of the participants were single (91.0%) and had been subjected to recent stressors in the past six months (67.1%). For housing, 77.3% of the students lived with family instead of university dormitories (22.7%). Almost all our participants were not currently visiting a mental health care specialist (97.8%), nor were they taking any psychiatric medication (96.4%). Most students also did not report a positive mental health history (94.1%), nor did they have a positive family history of eating disorders (90.6%). Further details, characteristics, and differences among the participants are outlined in Table 2 . Regarding the results of the administered questionnaires, the mean score of the EAT-26 was 9.50 (SD = 9.35); after applying a cutoff point of 20, ninety-four (11.3%) students had a high risk of developing eating disorders. For the SCOFF questionnaire, applying a cutoff point of 2 resulted in one hundred and sixty-eight (20.3%) patients being at high risk of developing eating disorders. Five years of medical school were grouped into two groups: the second and third years were considered preclinical, while the fourth, fifth and sixth years were considered clinical, as students started rotations in hospital wards at the start of the fourth year. Upon comparing these two categories, the highest prevalence was noted in the second year (a preclinical year), representing 15.81% of the total number of students in that year. This group was more strongly associated with a greater risk of disordered eating (p = 0.017). Out of 556 students reporting recent stressors, only 15 students were seeing a healthcare professional (2.69%), while only six students at high risk according to their EAT-26 results were seeing a professional in comparison with 9 (5.35%) according to SCOFF. For section B of the EAT-26, the prevalence of behaviors considered in need of medical attention was as follows: binge eating 29.8% (considered alarming if recurrent 2–3 times a month or more), self-induced vomiting 3.4% (requiring attention at any frequency), use of laxatives and diet pills 5.1% (also requiring attention at any frequency) and finally exercising for ≥ 60 min/day 2.5% (only if practiced once a day or more). Overall, individuals with alarming behaviors toward food were at greater risk of eating disorders (OR = 4.63) (CI 95% 3.23–6.66) ** (p > 0.001). Furthermore, the significance was robust when we conducted binary regression between the risk of EAT and SCOFF and the clinically alarming portion of each question. See Tables 6 and 7 . Gender and a high risk of eating disorders: Table 3 shows the odds ratio between males and females with a high risk of eating disorders depending on the risk calculated by the EAT-26. The table indicates that 8.1% of males and 14.3% of females have a high risk of eating disorders. The odds ratio between males and females was 1.89 (95% CI: 1.21–2.96), as there were significant differences between males and females. Table 4 shows the odds ratio between males and females with a high risk of eating disorders depending on the risk calculated by SCOFF. The table indicates that 16.54% of males and 23.82% of females have a high risk of eating disorders. The odds ratio between males and females was 1.57 (95% CI: 1.11–2.22), as there were significant differences between males and females. BMI and a high risk of eating disorders: A high risk of disordered eating was significantly associated with weight pattern and BMI classification (**p > 0.001), with a 95% CI of 1.08–1.18. Predictors and high risk of eating disorders: Table 5 presents the results of binary regression analysis aimed at determining the adjusted odds ratios for a high risk of eating disorders associated with various factors. The variables considered included sex, age, body mass index (BMI), recent stressors, living arrangements, marital status, visiting a health care professional, taking psychiatric medication, personal positive mental history, and positive family history of eating disorders. The adjusted odds ratios, along with their corresponding 95% confidence intervals, provide insights into the potential associations between these variables and the likelihood of individuals being at a high risk of eating disorders. Notably, all addressed variables demonstrate a positive correlation with the dependent risk. The only factors that, despite showing trends, did not reach significance based on their confidence intervals were current use of psychiatric drugs, living circumstances and marital status. Table 2 : Student Sample Characteristics Variables Frequency (n) Percent (%) Means (SDs) Gender Males 405 48.9% - Females 424 51.1% - Age 18-30 years - - 21.29 (1.76) BMI 14.04-50.26 - - 22.56 (3.79) BMI Ranges Underweight 82 9.8% - Within normal range 561 67.6% - Overweight 153 18.4% - Obese (classes1,2 and 3) 33 3.9% - Marital Status Single 754 91.0% - Married 75 9.0% - Recent Stressors Yes 556 67.1% - No 273 32.9% - Where do you live With family 641 77.3% - Dorms 188 22.7% - Year of Medical School Second 196 23.6% - Third 131 15.8% - Fourth 126 15.2% - Fifth 196 23.6% - Sixth 180 21.7% - Classification of Year Preclinical 328 39.6% - Clinical 501 60.4% - Currently Seeing a Healthcare Specialist No 811 97.8% - Yes 18 2.2% - Currently Taking any Psychiatric Medication No 799 96.4% - Yes 30 3.6% - Personal Mental Health History No 780 94.1% - Yes 49 5.9% - Family History of Eating Disorders No 751 90.6% - Yes 78 9.4% - Recent weight loss of 9 kgs or more in the past six months No 755 91.1% - Yes 74 8.9% - Table 3 demonstrating the odds ratio between males and females with high risk of eating disorders. (EAT-26 risk) Males (Referenced) Females OR (95% CI) High risk of eating disorders 33 (8.1% of total males) 61 (14.3% of total females) 1.89 (1.21-2.96)* * p<0.05, ** p<0.001 Unadjusted odds ratios were used in this table. Table 4 demonstrating the odds ratio between males and females with high risk of eating disorders. (SCOFF risk) Males (Referenced) Females OR (95% CI) High risk of eating disorders 67 (16.5% of total males) 101 (23.8% of total females) 1.57 (1.11-2)* * p<0.05, ** p<0.001 Unadjusted odds ratios were used in this table. Table 5 shows the results of binary regression to determine the adjusted odds ratio for a high risk of eating disorders according to multiple variables. variable high risk of eating disorders (SCOFF) high risk of eating disorders (EAT-26) Year of medical school (preclinical is referenced) 0.66 (0.47-0.92) * 0.68 (0.43-1.04) (p=0.82) Number of positive dieting questions 1.45 (1.36-1.54) ** 2.30 (1.99-2.65)** Age 0.92 (0.83-1.02) (p=0.12) 0.91 (0.8-1.03) (p=0.17) BMI 1.13 (1.08-1.18)** 1.15 (1.09-1.21)** Recent Stressors (not having is referenced) 2.43 (1.60-3.69)** 2.84 (1.6-5.04)** Where do you live (Dorms are referenced) 0.8 (0.55-1.20) (p=0.31) 0.69 (0.43-1.12) (p=0.13) Marital Status (married is referenced) 0.6 (0.39-1.15) (p=0.15) 0.64 (0.33-1.23) (p=0.18) Visiting a Health care professional (not is referenced) 4.10 (1.60-10.49) * 4.1 (1.5-11.21)* Taking Psychiatric Medication (not taking is referenced) 1.72 (0.77-3.89) (p=0.18) 3.01 (1.3-6.98)* Personal positive mental history (no history is referenced) 2.00 (1.07-3.73) * 2.76 (1.38-5.5)* Positive family history of eating disorders (no history is referenced) 1.87 (1.12-3.13) * 2.66 (1.49-4.74)* * p<0.05, ** p<0.001 Table 6: Overall relationship between the behavioral section and SCOFF risk. Variables for SCOFF N=829 High Risk n (%) N=168 Low Risk n (%) N=661 p value Binge Eating Episodes Never ≤ Once per month *2-3 times a month *Once a week *2-6 times a week *≥ Once a day 38 43 28 27 20 12 319 181 76 51 21 13 > 0.001 Vomiting for weight shape or control Never *≤ Once per month *2-3 times a month *Once a week *2-6 times a week *≥ Once a day 154 4 6 2 1 1 647 6 2 1 1 4 > 0.001 Use of laxatives, diet pills or diuretics for weight control or shape Never *≤ Once per month *2-3 times a month *Once a week *2-6 times a week *≥ Once a day 141 14 6 3 1 3 646 6 2 1 1 5 > 0.001 Exercise ≥60 min/day for weight loss or control Never ≤ Once per month 2-3 times a month Once a week 2-6 times a week *≥ Once a day 66 20 22 17 33 10 487 54 27 24 58 11 0.003 Weight loss ≥20 lbs. (9 kg) *Yes 41 33 > 0.001 No 127 628 - Table 7: Overall relationship between the EAT-26 score and behavior Variables for EAT-26 N=829 High Risk n (%) N=94 Low Risk n (%) N=735 p value Binge Eating Episodes Never ≤ Once per month *2-3 times a month *Once a week *2-6 times a week *≥ Once a day 19 25 11 15 14 10 338 199 93 63 27 15 > 0.001 Vomiting for weight shape or control Never *≤ Once per month *2-3 times a month *Once a week *2-6 times a week *≥ Once a day 80 5 4 2 2 1 721 5 4 1 0 4 > 0.001 Use of laxatives, diet pills or diuretics for weight control or shape Never *≤ Once per month *2-3 times a month *Once a week *2-6 times a week *≥ Once a day 75 12 3 1 1 2 712 8 5 3 1 6 > 0.001 Exercise ≥60 min/day for weight loss or control Never ≤ Once per month 2-3 times a month Once a week 2-6 times a week *≥ Once a day 33 7 13 9 24 8 520 67 36 32 67 13 > 0.001 Weight loss ≥20 lbs. (9 kg) Yes 20 74 > 0.001 No 54 681 - *Alarm frequency that requires medical attention Discussion This study inspected a sample of Syrian medical students to provide initial information on the extent of the prevalence of disordered eating behaviors in this group, considering the paucity of related research. Initially, our risk percentage reached 11.3% using the EAT-26 and 20.3% based on SCOFF. Compared with results from other medical schools, the closest 17% of the respondents were at risk of using EAT-26, and 19% were at risk of using SCOFF for medical students in Lebanon, while there was a greater risk in both Morocco (25.09%) and Saudi Arabia (32.1%) in addition to Pakistan (22.75% using EAT-26 and 17% using SCOFF), while a lower percentage of Indian medical students were found (13% distributed equally between both genders) (17-21). In comparison with larger studies, one scoping review showed a pooled prevalence in medical students of 10.5%, while another reported a 17.35% prevalence. Both of these factors, compared to the general population, are strongly increased in medical students (with a lifetime risk of 0.91% and a 12-month risk of 0.43%) (22-24). Ideally, to achieve full case diagnosis and follow-up, these surveys must be followed by clinical expert evaluation with the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria, as this turns simple screening into effective detection and initiation of treatment as needed (25). The first factor to demonstrate a notable connection with increased ED risk is exposure to stressors. In contrast with their peers with whom they share age, medical students are proven to experience a significant load of stress even to the extent where medical education is considered the sole factor of stress. This stress increases with advancing through years of education and is shown to peak at the second year (considered a preclinical year). From their own perspective, stressors for medical students emerge from many aspects, including academic workload, competition with peers and exposure to human suffering (which is more common in fourth-year students who are just starting clinical rotations in hospitals) (7,26). This also solidifies our observation that there is a difference in risk between clinical and preclinical years, as in our study, the risk seemed slightly higher in clinical years in which stressors such as exposure to human suffering and personal responsibility of medical personality increase in effect and therefore (in predisposing individuals) might trigger a new disorder. Many more nascent risk factors are correlated with ED symptomology and exacerbation, and among the most discussed are social media and the SARS-COVID-19 pandemic. Further research on the role that media has implemented suffers from the difficulty in isolating its effects on people who suffer from EDs to determine how it exactly affects them, among others. Pandemics are associated with new risk factors, such as the disruption of routines, social isolation, a lack of access to healthcare and social anxiety, and a new disorder or worsening of a preexisting disorder (27,28). Additionally, sex is one of the most important and prevailing factors contributing to ED etiology. Our study agreed with the abundance of research showing that females in general are more prone to developing EDs. Medically speaking, studies mentioned that female students reported higher stress levels concerning academic workload, poor time-management skills and exposure to human suffering. It was also reported that female physicians are generally more prone to developing emotional exhaustion and burnout (29-33). For dieting behaviors, skipping meals and weight, these factors also demonstrated strong correlations with disordered eating behaviors and can be used as future indicators and predictors of EDs. As noted in the dieting section of the EAT-26, the number of positively answered questions was evidently important as a key moderator. Further solidifying our results, both genders who put themselves through dieting behaviors and strive for the “ideal-thin” figure were at risk for developing disordered eating habits by 3.28 times (34,4). Furthermore, BMI and fluctuations in BMI also play a fundamental role in the development of EDs, as our results also demonstrated. This factor’s effect starts morphing with childhood weight as a starting point, as both lower and higher BMIs are related to different kinds of eating habits (4). Generally, higher BMIs tend to be more strongly correlated with worsening relationships with food, as every one-unit increase in BMI may lead to a 1.26-fold increase in risk. This demands attention for overweight and obese patients, as ED symptoms are not why they usually seek professional healthcare (34,35). Moreover, this should not result in subsiding underweight individuals despite the lower risk, as this perception might lead to masking of the threatening symptoms and simply resigning to naming these individuals merely “underweight” (36). The final set of factors that displayed a notable relationship were personal positive mental health history, meeting with a healthcare specialist and a positive family history of eating disorders. Family history has a reciprocal effect, as children who are born to a parent with an existing eating disorder have a 3-5 times greater chance of developing one in the future. However, despite the hereditary nature that contributes to its etiology, no particular disorder tends to be more transmissible than the other, and thus, if a parent suffers from anorexia nervosa, it is not certain that if their offspring do develop an ED, it would necessarily be an AN. It is also notably worth mentioning that children of affected parents are also at risk for developing other mental illnesses in addition to those in EDs and not exclusively in EDs. Interestingly, a parent of a child suffering from disordered eating is also triggered to develop weight and appearance concerns (37-40). A personal history of mental health also triggers a bad relationship with food as a comorbid condition, with their associated mindsets (perfectionism, guilt, self-judgment, etc.). have been shown to be related to a greater risk of symptom development. The most common psychiatric conditions were depression, anxiety and even bipolar disorder. Although a timeline still needs to be drawn and further disentanglement is needed to determine the preceding cause and the result, studies now offer solid evidence of multiple known factors that interplay this relationship (4). Finally, logically speaking, to justify seeking professional mental health assistance, there needs to be a prior complaint or illness, and the correlation between seeing a healthcare specialist and ED risk will also follow the same trend, while the use of medication is not necessarily an influencing factor. Strengths and limitations : This study included a large number of participants to ensure that the results were as accurate as possible. Additionally, the emphasis on using two screening tools demonstrates further reach for significance. Further studies should include students from public and private universities along with students from different governorates to study the impact of greater diversity. In addition, more elaboration on certain factors deserves to be highlighted, and the addition of more possibly associated predictors should be added to inspect risk factors on a larger scale. Conclusions This study sheds light on disordered eating behaviors among Syrian medical students, revealing initial risk percentages of 11.3% using the EAT-26 and 20.3% based on SCOFF. Stressors, particularly academic workload and exposure to human suffering, emerged as significant contributors to ED risk, with distinctions observed between clinical and preclinical years. Sex, dieting behaviors, BMI fluctuations, personal mental health history, meeting with a healthcare specialist, and positive family history of eating disorders were identified as notable factors influencing ED risk. This study underscores the complex interplay of biological, environmental, and personal elements in the manifestation of disordered eating, emphasizing the need for early detection, clinical evaluation, and holistic approaches in addressing eating disorders among Syrian medical students. Further research and longitudinal studies are recommended for a deeper understanding and informed interventions. Declarations Conflict of interest: None to declare Ethical approval: The ethical board of the Faculty of Medicine and Damascus University approved this study (ID number: 241023-130, session 8 on 24/10/2024). Funding: This project received no specific funding. Data availability: The data that support the findings of this study are available upon request from the corresponding author (L.N.). Author contributions: L.N.: first author; data collection and analysis, writing and reviewing the manuscript. L.M.: second author, data collection and curation, writing. 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A 4pL item response theory examination of perceived stigma in the screening of eating disorders with the SCOFF among college students. Eating and weight disorders : EWD 2023;28(1):79. Morgan JF, Reid F, Lacey JH. The SCOFF questionnaire: assessment of a new screening tool for eating disorders. BMJ. 1999;319(7223):1467–1468. doi:10.1136/bmj.319.7223.1467 Vijayalakshmi P, Thimmaiah R, Nikhil Reddy SS, B VK, Gandhi S, BadaMath S. Gender differences in body mass index, body weight perception, weight satisfaction, disordered eating and weight control strategies among indian medical and nursing undergraduates. Invest Educ Enferm. 2017;35(3):268–278. doi:10.17533/udea.iee.v35n3a04 Aoun A, Azzam J, Jabbour FE, Hlais S, Daham D, Amm CE, Honein K, Déchelotte P. Validation of the Arabic version of the SCOFF questionnaire for the screening of eating disorders. Eastern Mediterranean health journal = La revue de sante de la Mediterranee orientale = al-Majallah al-sihhiyah li-sharq al-mutawassit 2015;21(5):326-31. Bizri M, Geagea L, Kobeissy F, Talih F. Prevalence of Eating Disorders Among Medical Students in a Lebanese Medical School: A Cross-Sectional Study. Neuropsychiatric disease and treatment 2020;16:1879-87. Attouche N, Hafdi S, Somali R, Battas O, Agoub M. [Factors associated with the risk of developing eating disorders among medical students in Casablanca, Morocco]. The Pan African medical journal 2021;39:270. Ghamri RA, Alahmari AM, Alghamdi LS, Alamoudi SF, Barashid MM. Prevalence and predictors of eating disorders: A cross-sectional survey of medical students at King Abdul-Aziz University, Jeddah. Pakistan journal of medical sciences 2022;38(6):1633-8. Memon AA, Adil SE, Siddiqui EU, Naeem SS, Ali SA, Mehmood K. Eating disorders in medical students of Karachi, Pakistan-a cross-sectional study. BMC research notes 2012;5:84. Iyer S, Shriraam V. Prevalence of Eating Disorders and Its Associated Risk Factors in Students of a Medical College Hospital in South India. Cureus 2021;13(1):e12926. Qian J, Wu Y, Liu F, Zhu Y, Jin H, Zhang H, Wan Y, Li C, Yu D. An update on the prevalence of eating disorders in the general population: a systematic review and meta-analysis. Eating and weight disorders : EWD 2022;27(2):415-28. Jahrami H, Saif Z, Faris MA, Levine MP. The relationship between risk of eating disorders, age, gender and body mass index in medical students: a meta-regression. Eating and weight disorders : EWD 2019;24(2):169-77. Fekih-Romdhane F, Daher-Nashif S, Alhuwailah AH, Al Gahtani HMS, Hubail SA, Shuwiekh HAM, Khudhair MF, Alhaj OA, Bragazzi NL, Jahrami H. The prevalence of feeding and eating disorders symptomology in medical students: an updated systematic review, meta-analysis, and meta-regression. Eating and weight disorders : EWD 2022;27(6):1991-2010. Fisher M, Gonzalez M, Malizio J. Eating disorders in adolescents: how does the DSM-5 change the diagnosis. International journal of adolescent medicine and health 2015;27(4):437-41. Dyrbye LN, Thomas MR, Shanafelt TD.. Systematic review of depression, anxiety, and other indicators of psychological distress among U.S. and Canadian medical students. Acad Med. 2006;81:354–373 Peter C, Brosius HB. [The role of the media in the development, course, and management of eating disorders]. Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz 2021;64(1):55-61. Gao Y, Bagheri N, Furuya-Kanamori L. Has the COVID-19 pandemic lockdown worsened eating disorders symptoms among patients with eating disorders? A systematic review. Zeitschrift fur Gesundheitswissenschaften = Journal of Public Health 2022;30(11):2743-52. Sharan P, Sundar AS. Eating disorders in women. Indian journal of psychiatry 2015;57(Suppl 2):S286-95. Rosal MC, Ockene IS, Ockene JK, et al. A longitudinal study of students’ depression at one medical school. Academic Medicine. 1997;72:542–546 Compton MT, Carrera J, Frank E. Stress and depressive symptoms/dysphoria among US medical students: results from a large, nationally representative survey. J Nerv Ment Dis. 2008;196:891–897 Hill MR, Goicochea S, Merlo LJ. In their own words: stressors facing medical students in the millennial generation. Medical education online 2018;23(1):1530558. Houkes I, Winants Y, Twellaar M, et al. Development of burnout over time and the causal order of the three dimensions of burnout among male and female GPs. A Three-Wave Panel Study. BMC Public Health.. 2011;11(1):240. Kabakuş Aykut M, Bilici S. The relationship between the risk of eating disorder and meal patterns in University students. Eating and weight disorders : EWD 2022;27(2):579-87. Melchior V, Fuchs S, Scantamburlo G. [Obesity and eating disorders]. Revue medicale de Liege 2021;76(2):134-9. Flament MF, Henderson K, Buchholz A, Obeid N, Nguyen HN, Birmingham M, Goldfield G. Weight Status and DSM-5 Diagnoses of Eating Disorders in Adolescents From the Community. Journal of the American Academy of Child and Adolescent Psychiatry 2015;54(5):403-411.e2. Bould H, Sovio U, Koupil I, Dalman C, Micali N, Lewis G, Magnusson C. Do eating disorders in parents predict eating disorders in children? Evidence from a Swedish cohort. Acta psychiatrica Scandinavica 2015;132(1):51-9. Alghanami BH, El Keshky MES. The Relationship between the Family Environment and Eating Disorder Symptoms in a Saudi Nonclinical Sample of Students: A Moderated Mediated Model of Automatic Thoughts and Gender. Behavioral sciences (Basel, Switzerland) 2023;13(10):818. Strober M, Freeman R, Lampert C, Diamond J, Kaye W. Controlled family study of anorexia nervosa and bulimia nervosa: evidence of shared liability and transmission of partial syndromes. The American journal of psychiatry 2000;157(3):393-401. Kendler KS, Ohlsson H, Sundquist J, Sundquist K. The patterns of family genetic risk scores for eleven major psychiatric and substance use disorders in a Swedish national sample. Translational psychiatry 2021;11(1):326. Additional Declarations No competing interests reported. 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-4232158","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":288875801,"identity":"788afd21-ee8d-45d0-b13c-b18d44174686","order_by":0,"name":"Lujain Nahas","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYBACAwaGBCAEMxgffKgAspiZG4jWwmw44wxICyNBLXAGmzRvG4hJSItEwsMPD3fckTdnP/5Acua82mj+dqCWHxXb8GlJlkg888xwZ0+OgcHHbcdzZxxmbGDsOXMbn5YEicS2w4wbDuQwJM7cdiy3AaiFmbENr5bkH0At9hvOP39wmHfOsdz5RGhJA9mSuOFGgmEzb0NN7gaCWngepFkAtSRvuPHGmHHGsQO5G4FaDuLzi317TvLNn22HbTecT3/+40NNXe6884cPPvhRgVsLAwNPAjLvMJg8gEc9ELCjyNfhVzwKRsEoGAUjEgAAwPJmH2I7g4AAAAAASUVORK5CYII=","orcid":"","institution":"Faculty of Medicine, University of Damascus, Damascus","correspondingAuthor":true,"prefix":"","firstName":"Lujain","middleName":"","lastName":"Nahas","suffix":""},{"id":288875803,"identity":"d698a469-5bea-4951-beae-30c116a2898e","order_by":1,"name":"Lama Mohamad","email":"","orcid":"","institution":"Faculty of Medicine, University of Damascus, Damascus","correspondingAuthor":false,"prefix":"","firstName":"Lama","middleName":"","lastName":"Mohamad","suffix":""},{"id":288875805,"identity":"4956c2c4-25ed-40c8-b7b5-2d539a25d34d","order_by":2,"name":"Jameel Soqia","email":"","orcid":"","institution":"Faculty of Medicine, University of Damascus, Damascus","correspondingAuthor":false,"prefix":"","firstName":"Jameel","middleName":"","lastName":"Soqia","suffix":""},{"id":288875807,"identity":"084bee02-129e-49a9-87f1-cc45c2f046ca","order_by":3,"name":"Laila Yakoub Agha","email":"","orcid":"","institution":"Faculty of Medicine, University of Damascus, Damascus","correspondingAuthor":false,"prefix":"","firstName":"Laila","middleName":"Yakoub","lastName":"Agha","suffix":""},{"id":288875810,"identity":"d1c7e5aa-e5bb-47b5-807e-f12be2fae8d0","order_by":4,"name":"Mehdy Nahas","email":"","orcid":"","institution":"Faculty of Medicine, University of Damascus, Damascus","correspondingAuthor":false,"prefix":"","firstName":"Mehdy","middleName":"","lastName":"Nahas","suffix":""},{"id":288875812,"identity":"48ae593e-07f3-431e-aedc-608c8068482b","order_by":5,"name":"Bayan Alsaid","email":"","orcid":"","institution":"Laboratory of Anatomy, Faculty of Medicine, University of Damascus, Damascus","correspondingAuthor":false,"prefix":"","firstName":"Bayan","middleName":"","lastName":"Alsaid","suffix":""}],"badges":[],"createdAt":"2024-04-07 15:59:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4232158/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4232158/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55876150,"identity":"8aa00fb2-9e15-4cec-93ba-721e42bb7519","added_by":"auto","created_at":"2024-05-05 14:52:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":834794,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4232158/v1/93dee355-0876-4d96-b101-ecc577b9318e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prevalence and predictors of Eating Disorders’ risk in medical students at Damascus University: a cross-sectional study","fulltext":[{"header":"What is already known about the subject","content":"\u003cp\u003eEating disorders are serious mental health conditions that can have a significant impact on a person's physical and emotional well-being. We were interested in understanding the prevalence of these disorders in medical students because they are known to be at\u0026nbsp;greater\u0026nbsp;risk due to the stress and pressure of their studies,\u0026nbsp;among other factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat this study adds:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBy understanding how common eating disorders are among medical students, healthcare professionals can better identify and support those who may be struggling. Additionally, addressing eating disorders in medical students can help prevent future healthcare providers from experiencing these challenges themselves, ultimately improving the overall well-being of the healthcare workforce. Ultimately, this research has the potential to improve the mental health and overall well-being of medical students, leading to better patient care and outcomes in the long run.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eEating disorders (EDs) consist of a spectrum of presentations for which a number of factors, such as genetic and environmental factors, are combined to create a predisposition (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). This may be a subthreshold risk or a full-on disorder that disrupts life and threatens high levels of mortality, psychological distress and impairment. However, there are relatively fewer studies in this field than in the field of other mental disorders (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). A large study identified a number of possible triggers and participating factors and grouped them into nine categories: genetics, gastrointestinal microbiota and autoimmune reactions, childhood and early adolescent exposures, personality traits and comorbid health conditions, gender, socioeconomic status, ethnic minority, body image and social influence and elite sports. This implies a vast variety of related factors that require testing for possible and degree of influence in different populations (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCompared to a global general population prevalence of 5.7% and 2.2% in females and males, respectively, a 10.4% prevalence was found among medical students who are generally more predisposed to disordered eating behaviors, and this is attributable to various factors and coexisting or preceding elements (5,6). This observation highlights multiple added predisposing factors that medical students are subjected to in addition to generally noted factors, as they are generally recognized to be more susceptible to psychological distress (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e7\u003c/span\u003e). In Syria, there is a shortage of research in terms of providing a recent estimate of prevalence, with gross meta-analyses finding a (22.3%) prevalence percentage in 2022 depending on only one study (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e8\u003c/span\u003e). This paucity of research and delay of recognition is also met with minimal recognition of the mental health sector in Syrian society, as it is generally stigmatized and marginalized, which makes this study necessary. Furthermore, to our knowledge, no similar studies concerning Syrian medical students have been conducted, which makes ours the first to study the prevalence of risk and associated predisposing factors and to compare our findings with international literature to determine how our results align.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design:\u003c/h2\u003e \u003cp\u003eThis cross-sectional study took place in the Faculty of Medicine of Damascus University in Syria to inspect the prevalence and predictors of the risk of disordered eating behaviors using online surveys over a three-month period (October to December 2023). Test scores were used to classify high-risk and low-risk groups and to understand the differences between them and how both groups correlate wit\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\)\u003c/span\u003e\u003c/span\u003eh the studied risk factors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSample size and participants:\u003c/h2\u003e \u003cp\u003eThe sample size was calculated using Robert Mason\u0026rsquo;s formula (M\u0026thinsp;=\u0026thinsp;5991, s\u003csup\u003e2\u003c/sup\u003e\u003csub\u003e=\u003c/sub\u003e0.00065, p\u0026thinsp;=\u0026thinsp;q\u0026thinsp;=\u0026thinsp;0.50), and a minimum size of n\u0026thinsp;=\u0026thinsp;374 was recommended (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e9\u003c/span\u003e). The number of participants from each year and the overall number used in the formula can be seen in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\)\u003c/span\u003e \u003c/span\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(n=\\frac{M}{\\left[({S}^{2 }\\times \\left(M-1\\right))\u0026divide;pq\\right]+1 }\\)\u003c/span\u003e \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\u003eSample size and overall population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eyear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal number of students\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRequired number for the sample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOur sample\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e196\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e196\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5991\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e829\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\u003eAll male and female students from the second to sixth years at Damascus University were eligible to participate, and students were chosen randomly from private study groups for each year. They were asked to complete an online survey sent to each of them with a personally customized message between 6:00 and 9:00 PM over a period of three months spanning from October to December 2023. The first year was excluded because it encompasses a large number of students who will eventually be sorted into three medical faculties (Faculty of Pharmacy, Dentistry and Medicine). The response rate was estimated at 87.81%, as 829 students completed the survey from a total of 944 messages sent.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMeasurements\u003c/h2\u003e \u003cp\u003eThe survey included two eating disorder risk assessment questionnaires: the Eating Attitude Test-26 (EAT-26) and Sick, Control, One, Fat, Food (SCOFF). At the beginning of the survey, participants were asked to answer demographic questions concerning exposure to recent stressors, past or current use of mental health services and medications, current school year, living circumstances, and medical and family histories of mental and eating disorders. Body mass index (BMI) was subsequently calculated using the required height and weight.\u003c/p\u003e \u003cp\u003eThe EAT-26 is a shorter version of the 40-item questionnaire and is self-administered. It is used for the determination of individuals with high ED risk. It starts with 26 questions. Each item is scored on a six-point scale ranging from always to never. It can be divided into three subgroups: dieting questions, bulimia and food preoccupation and oral control. The total sum of the Eat-26 scores ranges from 0 to 78. With a cutoff point of 20, a score of 20 or higher is classified as high risk (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The second part investigated behaviors related to weight-control patterns, including binge eating episodes, self-induced vomiting, the use of laxatives or diuretics and excessive exercise to control shape and weight, in addition to drastic weight loss of more than 9 kilograms over the past 6 months. The EAT-26 is considered a psychometrically reliable instrument (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.90) (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e11\u003c/span\u003e). The validated Arabic version of the EAT-10 was used in this study (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe SCOFF questionnaire is another widely used self-administered screening questionnaire and is among the most sensitive (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe results of these five questions were added, and a score of 2 or more was considered high risk (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e14\u003c/span\u003e). This tool is credible and has reliable psychometric properties (kappa statistic\u0026thinsp;=\u0026thinsp;0.73 to 0.82) (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA validated Arabic version was also used in our study (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eEthical considerations\u003c/h2\u003e \u003cp\u003eStudents who agreed to participate were asked to complete an online questionnaire administered personally to each participant. Informed consent was obtained, and participants were reminded that their responses would not be shared or used outside the scope of this research. The study was approved by the ethical committee of Damascus University (ID number: 241023-130, session 8 on 24/10/2024) and was conducted in accordance with the ethical standards of the Helsinki II Declaration about informed consent, voluntariness and anonymity. Surveys and questionnaires containing no information were used to identify participants; henceforth, their responses remained anonymous. Participants understood that their contribution was purely voluntary.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis:\u003c/h2\u003e \u003cp\u003eAll analyses were performed using IBM SPSS Statistics for Windows, version 25 (IBM Corp., Armonk, N.Y., USA). Google Forms were used to collect the data online. Prevalence rates were calculated based on the recommended cut-offs for Eat-26 and SCOFF. Separate logistic regressions were conducted to identify predictors of high ED risk according to the Eat-26 and SCOFF scores. In each regression, sex, age, year of medical school, BMI, recent stressors, place of residence, marital status, visiting a health care professional, taking psychiatric medication, personal positive mental history and positive family history of eating disorders were entered as predictors in step 1.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003eDemographic characteristics\u003c/h2\u003e\n \u003cp\u003e\u003cstrong\u003eOverall, of the 829 participating students\u003c/strong\u003e, 48.9% were males and 51.1% were females. The ages ranged from 18 to 30 years, with a mean of 21.29 years (SD\u0026thinsp;=\u0026thinsp;1.76). The BMI of the participants ranged from 14.04 to 50.26, with a mean of 22.56 (SD\u0026thinsp;=\u0026thinsp;3.79). The majority of the participants were single (91.0%) and had been subjected to recent stressors in the past six months (67.1%). For housing, 77.3% of the students lived with family instead of university dormitories (22.7%). Almost all our participants were not currently visiting a mental health care specialist (97.8%), nor were they taking any psychiatric medication (96.4%). Most students also did not report a positive mental health history (94.1%), nor did they have a positive family history of eating disorders (90.6%). Further details, characteristics, and differences among the participants are outlined in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eRegarding the results of the administered questionnaires, the mean score of the EAT-26 was 9.50 (SD\u0026thinsp;=\u0026thinsp;9.35); after applying a cutoff point of 20, ninety-four (11.3%) students had a high risk of developing eating disorders. For the SCOFF questionnaire, applying a cutoff point of 2 resulted in one hundred and sixty-eight (20.3%) patients being at high risk of developing eating disorders.\u003c/p\u003e\n \u003cp\u003eFive years of medical school were grouped into two groups: the second and third years were considered preclinical, while the fourth, fifth and sixth years were considered clinical, as students started rotations in hospital wards at the start of the fourth year. Upon comparing these two categories, the highest prevalence was noted in the second year (a preclinical year), representing 15.81% of the total number of students in that year. This group was more strongly associated with a greater risk of disordered eating (p\u0026thinsp;=\u0026thinsp;0.017).\u003c/p\u003e\n \u003cp\u003eOut of 556 students reporting recent stressors, only 15 students were seeing a healthcare professional (2.69%), while only six students at high risk according to their EAT-26 results were seeing a professional in comparison with 9 (5.35%) according to SCOFF.\u003c/p\u003e\n \u003cp\u003eFor section B of the EAT-26, the prevalence of behaviors considered in need of medical attention was as follows: binge eating 29.8% (considered alarming if recurrent 2\u0026ndash;3 times a month or more), self-induced vomiting 3.4% (requiring attention at any frequency), use of laxatives and diet pills 5.1% (also requiring attention at any frequency) and finally exercising for \u0026ge;\u0026thinsp;60 min/day 2.5% (only if practiced once a day or more).\u003c/p\u003e\n \u003cp\u003eOverall, individuals with alarming behaviors toward food were at greater risk of eating disorders (OR\u0026thinsp;=\u0026thinsp;4.63) (CI 95% 3.23\u0026ndash;6.66) ** (p\u0026thinsp;\u0026gt;\u0026thinsp;0.001).\u003c/p\u003e\n \u003cp\u003eFurthermore, the significance was robust when we conducted binary regression between the risk of EAT and SCOFF and the clinically alarming portion of each question. See Tables \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003eGender and a high risk of eating disorders:\u003c/h2\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e shows the odds ratio between males and females with a high risk of eating disorders depending on the risk calculated by the EAT-26. The table indicates that 8.1% of males and 14.3% of females have a high risk of eating disorders. The odds ratio between males and females was 1.89 (95% CI: 1.21\u0026ndash;2.96), as there were significant differences between males and females.\u003c/p\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e shows the odds ratio between males and females with a high risk of eating disorders depending on the risk calculated by SCOFF. The table indicates that 16.54% of males and 23.82% of females have a high risk of eating disorders. The odds ratio between males and females was 1.57 (95% CI: 1.11\u0026ndash;2.22), as there were significant differences between males and females.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eBMI and a high risk of eating disorders:\u003c/h2\u003e\n \u003cp\u003eA high risk of disordered eating was significantly associated with weight pattern and BMI classification (**p\u0026thinsp;\u0026gt;\u0026thinsp;0.001), with a 95% CI of 1.08\u0026ndash;1.18.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003ePredictors and high risk of eating disorders:\u003c/h2\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e presents the results of binary regression analysis aimed at determining the adjusted odds ratios for a high risk of eating disorders associated with various factors. The variables considered included sex, age, body mass index (BMI), recent stressors, living arrangements, marital status, visiting a health care professional, taking psychiatric medication, personal positive mental history, and positive family history of eating disorders. The adjusted odds ratios, along with their corresponding 95% confidence intervals, provide insights into the potential associations between these variables and the likelihood of individuals being at a high risk of eating disorders. Notably, all addressed variables demonstrate a positive correlation with the dependent risk. The only factors that, despite showing trends, did not reach significance based on their confidence intervals were current use of psychiatric drugs, living circumstances and marital status.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e: Student\u0026nbsp;Sample Characteristics\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"54.967948717948715%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercent (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeans (SDs)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eMales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e48.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e51.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003e18-30 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e21.29\u003c/p\u003e\n \u003cp\u003e(1.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003e14.04-50.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e22.56\u003c/p\u003e\n \u003cp\u003e(3.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eBMI Ranges\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eUnderweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e9.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eWithin normal range\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e561\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e67.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e18.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eObese (classes1,2 and 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e3.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eMarital Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e754\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e91.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e9.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eRecent Stressors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e556\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e67.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e32.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eWhere do you live\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eWith family\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e77.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eDorms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e22.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eYear of Medical School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eSecond\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e23.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eThird\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e15.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eFourth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e15.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eFifth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e23.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eSixth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e21.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eClassification of Year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003ePreclinical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e39.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eClinical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e60.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eCurrently Seeing a Healthcare Specialist\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e97.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e2.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eCurrently Taking any Psychiatric Medication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e799\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e96.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e3.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003ePersonal Mental Health History\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e780\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e94.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e5.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eFamily History of Eating Disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e751\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e90.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e9.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eRecent weight loss of 9 kgs or more in the past six months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e755\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e91.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e8.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cdiv class=\"gridtable\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3 demonstrating the odds ratio between males and females with high risk of eating disorders. (EAT-26 risk)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eMales (Referenced)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eHigh risk of eating disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e33 (8.1% of total males)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e61 (14.3% of total females)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e1.89 (1.21-2.96)*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e* p\u0026lt;0.05, ** p\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003eUnadjusted odds ratios were used in this table.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 4 demonstrating the odds ratio between males and females with high risk of eating disorders. (SCOFF risk)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eMales (Referenced)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eHigh risk of eating disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e67 (16.5% of total males)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e101 (23.8% of total females)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e1.57 (1.11-2)*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e* p\u0026lt;0.05, ** p\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003eUnadjusted odds ratios were used in this table.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cstrong\u003eTable 5\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eshows the results of\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;binary regression to determine the adjusted odds ratio\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003efor a\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ehigh risk of eating disorders\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eaccording to\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;multiple variables.\u003c/strong\u003e\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"425\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.1764705882353%\" valign=\"top\"\u003e\n \u003cp\u003evariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003ehigh risk of eating disorders (SCOFF)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003ehigh risk of eating disorders (EAT-26)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.1764705882353%\" valign=\"top\"\u003e\n \u003cp\u003eYear of medical school (preclinical is referenced)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e0.66 (0.47-0.92) *\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e0.68 (0.43-1.04)\u003c/p\u003e\n \u003cp\u003e(p=0.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.1764705882353%\" valign=\"top\"\u003e\n \u003cp\u003eNumber of positive dieting questions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e1.45 (1.36-1.54) **\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e2.30 (1.99-2.65)**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.1764705882353%\" valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e0.92 (0.83-1.02)\u003c/p\u003e\n \u003cp\u003e(p=0.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e0.91 (0.8-1.03)\u003c/p\u003e\n \u003cp\u003e(p=0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.1764705882353%\" valign=\"top\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e1.13 (1.08-1.18)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e1.15 (1.09-1.21)**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.1764705882353%\" valign=\"top\"\u003e\n \u003cp\u003eRecent Stressors (not having is referenced)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e2.43 (1.60-3.69)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e2.84 (1.6-5.04)**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.1764705882353%\" valign=\"top\"\u003e\n \u003cp\u003eWhere do you live (Dorms are referenced)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e0.8 (0.55-1.20)\u003c/p\u003e\n \u003cp\u003e(p=0.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e0.69 (0.43-1.12)\u003c/p\u003e\n \u003cp\u003e(p=0.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.1764705882353%\" valign=\"top\"\u003e\n \u003cp\u003eMarital Status (married is referenced)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e0.6 (0.39-1.15)\u003c/p\u003e\n \u003cp\u003e(p=0.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e0.64 (0.33-1.23)\u003c/p\u003e\n \u003cp\u003e(p=0.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.1764705882353%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Visiting a Health care professional (not is referenced)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e4.10 (1.60-10.49) *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e4.1 (1.5-11.21)*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.1764705882353%\" valign=\"top\"\u003e\n \u003cp\u003eTaking Psychiatric Medication (not taking is referenced)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e1.72 (0.77-3.89)\u003c/p\u003e\n \u003cp\u003e(p=0.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e3.01 (1.3-6.98)*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.1764705882353%\" valign=\"top\"\u003e\n \u003cp\u003ePersonal positive mental history (no history is referenced)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e2.00 (1.07-3.73) *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e2.76 (1.38-5.5)*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.1764705882353%\" valign=\"top\"\u003e\n \u003cp\u003ePositive family history of eating disorders (no history is referenced)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e1.87 (1.12-3.13) *\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e2.66 (1.49-4.74)*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e* p\u0026lt;0.05, ** p\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 6:\u0026nbsp;\u003c/strong\u003eOverall\u0026nbsp;relationship between\u0026nbsp;the\u0026nbsp;behavioral section and SCOFF risk.\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"623\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"54.967948717948715%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables for SCOFF N=829\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh Risk\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=168\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow Risk\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=661\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eBinge Eating Episodes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003cp\u003e\u0026le; Once per month\u003c/p\u003e\n \u003cp\u003e*2-3 times a month\u003c/p\u003e\n \u003cp\u003e*Once a week\u003c/p\u003e\n \u003cp\u003e*2-6 times a week\u003c/p\u003e\n \u003cp\u003e*\u0026ge; Once a day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e319\u003c/p\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026gt;\u003c/span\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eVomiting for weight shape or control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003cp\u003e*\u0026le; Once per month\u003c/p\u003e\n \u003cp\u003e*2-3 times a month\u003c/p\u003e\n \u003cp\u003e*Once a week\u003c/p\u003e\n \u003cp\u003e*2-6 times a week\u003c/p\u003e\n \u003cp\u003e*\u0026ge; Once a day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e647\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026gt;\u003c/span\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eUse of laxatives, diet pills or diuretics for weight control or shape\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003cp\u003e*\u0026le; Once per month\u003c/p\u003e\n \u003cp\u003e*2-3 times a month\u003c/p\u003e\n \u003cp\u003e*Once a week\u003c/p\u003e\n \u003cp\u003e*2-6 times a week\u003c/p\u003e\n \u003cp\u003e*\u0026ge; Once a day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e141\u003c/p\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e646\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026gt;\u003c/span\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eExercise \u0026ge;60 min/day for weight loss or control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003cp\u003e\u0026le; Once per month\u003c/p\u003e\n \u003cp\u003e2-3 times a month\u003c/p\u003e\n \u003cp\u003eOnce a week\u003c/p\u003e\n \u003cp\u003e2-6 times a week\u003c/p\u003e\n \u003cp\u003e*\u0026ge; Once a day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e487\u003c/p\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eWeight loss \u0026ge;20 lbs. (9 kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003e*Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026gt;\u003c/span\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cstrong\u003eTable 7:\u0026nbsp;\u003c/strong\u003eOverall\u0026nbsp;relationship between\u0026nbsp;the\u0026nbsp;EAT-26\u0026nbsp;score\u0026nbsp;and\u0026nbsp;behavior\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"623\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"54.967948717948715%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables for EAT-26 N=829\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh Risk\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=94\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow Risk\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=735\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"54.967948717948715%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eBinge Eating Episodes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003cp\u003e\u0026le; Once per month\u003c/p\u003e\n \u003cp\u003e*2-3 times a month\u003c/p\u003e\n \u003cp\u003e*Once a week\u003c/p\u003e\n \u003cp\u003e*2-6 times a week\u003c/p\u003e\n \u003cp\u003e*\u0026ge; Once a day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e338\u003c/p\u003e\n \u003cp\u003e199\u003c/p\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026gt;\u003c/span\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eVomiting for weight shape or control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003cp\u003e*\u0026le; Once per month\u003c/p\u003e\n \u003cp\u003e*2-3 times a month\u003c/p\u003e\n \u003cp\u003e*Once a week\u003c/p\u003e\n \u003cp\u003e*2-6 times a week\u003c/p\u003e\n \u003cp\u003e*\u0026ge; Once a day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e721\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026gt;\u003c/span\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eUse of laxatives, diet pills or diuretics for weight control or shape\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003cp\u003e*\u0026le; Once per month\u003c/p\u003e\n \u003cp\u003e*2-3 times a month\u003c/p\u003e\n \u003cp\u003e*Once a week\u003c/p\u003e\n \u003cp\u003e*2-6 times a week\u003c/p\u003e\n \u003cp\u003e*\u0026ge; Once a day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e712\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026gt;\u003c/span\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eExercise \u0026ge;60 min/day for weight loss or control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003cp\u003e\u0026le; Once per month\u003c/p\u003e\n \u003cp\u003e2-3 times a month\u003c/p\u003e\n \u003cp\u003eOnce a week\u003c/p\u003e\n \u003cp\u003e2-6 times a week\u003c/p\u003e\n \u003cp\u003e*\u0026ge; Once a day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e520\u003c/p\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026gt;\u003c/span\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003eWeight loss \u0026ge;20 lbs. (9 kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026gt;\u003c/span\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.442307692307693%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.525641025641026%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.628205128205128%\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.942307692307692%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 681\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cstrong\u003e*Alarm frequency that requires medical attention\u003c/strong\u003e\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study inspected a sample of Syrian medical students to\u0026nbsp;provide\u0026nbsp;initial\u0026nbsp;information\u0026nbsp;on the extent of the prevalence of disordered eating behaviors in this group,\u0026nbsp;considering the paucity of\u0026nbsp;related research.\u003c/p\u003e\n\u003cp\u003eInitially, our risk percentage reached 11.3% using the EAT-26 and 20.3% based on SCOFF.\u0026nbsp;Compared\u0026nbsp;with results from other medical schools, the closest\u0026nbsp;17% of the respondents were at risk of using EAT-26, and 19% were at risk of using SCOFF for medical students in Lebanon, while there was a greater risk in both Morocco (25.09%) and Saudi Arabia (32.1%) in addition to Pakistan (22.75% using EAT-26 and 17% using SCOFF), while a lower percentage of Indian medical students were found (13% distributed equally between both genders) (17-21).\u003c/p\u003e\n\u003cp\u003eIn comparison with larger studies, one scoping review showed a pooled prevalence in medical students of 10.5%, while another reported a 17.35% prevalence. Both of these factors, compared to the general population, are strongly increased in medical students (with a lifetime risk of 0.91% and a 12-month risk of 0.43%) (22-24). Ideally, to achieve full case diagnosis and follow-up, these surveys must be followed by clinical expert evaluation with the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria, as this turns simple screening into effective detection and initiation of treatment as needed (25).\u003c/p\u003e\n\u003cp\u003eThe first factor to demonstrate a notable connection with increased ED risk is exposure to stressors. In contrast with their peers with whom they share age, medical students are proven to experience a significant load of stress even to the extent where medical education is considered the sole factor of stress. This stress increases with advancing through years of education and is shown to peak at the second year (considered a preclinical year). From their own perspective, stressors for medical students emerge from many aspects, including academic workload, competition with peers and exposure to human suffering (which is more common in fourth-year students who are just starting clinical rotations in hospitals) (7,26). This also solidifies our observation that there is a difference in risk between clinical and preclinical years, as in our study, the risk seemed slightly higher in clinical years in which stressors such as exposure to human suffering and personal responsibility of medical personality increase in effect and therefore (in predisposing individuals) might trigger a new disorder. Many more nascent risk factors are correlated with ED symptomology and exacerbation, and among the most discussed are social media and the SARS-COVID-19 pandemic. Further research on the role that media has implemented suffers from the difficulty in isolating its effects on people who suffer from EDs to determine how it exactly affects them, among others. Pandemics are associated with new risk factors, such as the disruption of routines, social isolation, a lack of access to healthcare and social anxiety, and a new disorder or worsening of a preexisting disorder (27,28).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; Additionally, sex is one of the most important and prevailing factors contributing to ED etiology. Our study agreed with the abundance of research showing that females in general are more prone to developing EDs. Medically speaking, studies mentioned that female students reported higher stress levels concerning academic workload, poor time-management skills and exposure to human suffering. It was also reported that female physicians are generally more prone to developing emotional exhaustion and burnout (29-33).\u003c/p\u003e\n\u003cp\u003eFor\u0026nbsp;dieting behaviors, skipping meals and weight, these factors also demonstrated strong\u0026nbsp;correlations\u0026nbsp;with disordered eating behaviors and can be used as future indicators and predictors of EDs. As\u0026nbsp;noted\u0026nbsp;in the dieting section of the EAT-26, the number of positively answered questions was evidently important as a key moderator. Further solidifying our results, both genders who put themselves through dieting behaviors and strive for the \u0026ldquo;ideal-thin\u0026rdquo; figure were at\u0026nbsp;risk\u0026nbsp;for developing disordered eating habits by 3.28 times (34,4).\u003c/p\u003e\n\u003cp\u003eFurthermore, BMI and\u0026nbsp;fluctuations in BMI\u0026nbsp;also play a fundamental role in\u0026nbsp;the\u0026nbsp;development of EDs,\u0026nbsp;as our results also demonstrated. This factor\u0026rsquo;s effect starts morphing with childhood weight as a starting point, as both lower\u0026nbsp;and\u0026nbsp;higher BMIs are related to different kinds of eating habits (4). Generally, higher BMIs tend to\u0026nbsp;be\u0026nbsp;more\u0026nbsp;strongly correlated\u0026nbsp;with worsening relationships with food,\u0026nbsp;as every\u0026nbsp;one-unit\u0026nbsp;increase in BMI may lead to\u0026nbsp;a\u0026nbsp;1.26-fold increase in risk. This demands attention for overweight and obese patients,\u0026nbsp;as ED symptoms are not why they usually seek professional healthcare (34,35). Moreover, this should not result in subsiding underweight individuals despite the lower risk,\u0026nbsp;as this perception might lead\u0026nbsp;to\u0026nbsp;masking of the threatening symptoms and simply resigning to naming these individuals merely \u0026ldquo;underweight\u0026rdquo; (36). The final set of factors that displayed a notable relationship were personal positive mental health history, meeting with a healthcare specialist and a positive family history of eating disorders. Family history\u0026nbsp;has a\u0026nbsp;reciprocal\u0026nbsp;effect, as children who are born to a parent with an existing eating disorder have a\u0026nbsp;3-5 times greater\u0026nbsp;chance of developing one in the future. However,\u0026nbsp;despite the hereditary nature that contributes\u0026nbsp;to its\u0026nbsp;etiology, no particular disorder tends to be more transmissible than the other,\u0026nbsp;and\u0026nbsp;thus,\u0026nbsp;if a parent\u0026nbsp;suffers\u0026nbsp;from anorexia nervosa,\u0026nbsp;it is not\u0026nbsp;certain\u0026nbsp;that if their offspring\u0026nbsp;do\u0026nbsp;develop an ED,\u0026nbsp;it would\u0026nbsp;necessarily\u0026nbsp;be\u0026nbsp;an AN. It is also notably worth mentioning that children of affected parents are also at risk for developing other mental illnesses in addition to\u0026nbsp;those in\u0026nbsp;EDs and not exclusively\u0026nbsp;in EDs. Interestingly, a parent of a child suffering from disordered eating\u0026nbsp;is\u0026nbsp;also triggered to develop weight and appearance concerns (37-40).\u003c/p\u003e\n\u003cp\u003eA personal\u0026nbsp;history of mental health also triggers a bad relationship with food as\u0026nbsp;a\u0026nbsp;comorbid\u0026nbsp;condition,\u0026nbsp;with their associated mindsets (perfectionism, guilt, self-judgment, etc.).\u0026nbsp;have been shown to be related to\u0026nbsp;a greater\u0026nbsp;risk of symptom development.\u0026nbsp;The\u0026nbsp;most common psychiatric conditions were depression, anxiety and even bipolar disorder.\u0026nbsp;Although\u0026nbsp;a timeline still needs to be drawn and further disentanglement is needed to determine the preceding cause and the result, studies now offer solid evidence of multiple known factors that interplay this relationship (4). Finally, logically speaking, to justify seeking professional mental\u0026nbsp;health assistance,\u0026nbsp;there needs to be a prior complaint or illness,\u0026nbsp;and\u0026nbsp;the correlation between seeing a healthcare specialist and ED risk will also follow the same trend,\u0026nbsp;while the use of medication\u0026nbsp;is not\u0026nbsp;necessarily an influencing factor.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengths and\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003elimitations\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study\u0026nbsp;included\u0026nbsp;a large number of participants to ensure that the results were as accurate as\u0026nbsp;possible. Additionally, the emphasis on using two screening tools demonstrates further reach for significance. Further studies should include students from public and private universities along with students from different governorates to study the impact of\u0026nbsp;greater diversity.\u003c/p\u003e\n\u003cp\u003eIn addition, more elaboration on certain factors deserves to be highlighted, and the addition of more possibly associated predictors should be added to inspect risk factors on a larger scale.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study sheds light on disordered eating behaviors among Syrian medical students, revealing initial risk percentages of 11.3% using the EAT-26 and 20.3% based on SCOFF. Stressors, particularly academic workload and exposure to human suffering, emerged as significant contributors to ED risk, with distinctions observed between clinical and preclinical years. Sex, dieting behaviors, BMI fluctuations, personal mental health history, meeting with a healthcare specialist, and positive family history of eating disorders were identified as notable factors influencing ED risk. This study underscores the complex interplay of biological, environmental, and personal elements in the manifestation of disordered eating, emphasizing the need for early detection, clinical evaluation, and holistic approaches in addressing eating disorders among Syrian medical students. Further research and longitudinal studies are recommended for a deeper understanding and informed interventions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of interest:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone to declare\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ethical board of the Faculty of Medicine and Damascus\u0026nbsp;University approved\u0026nbsp;this study (ID number: 241023-130, session 8 on 24/10/2024).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project received no specific funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data\u0026nbsp;that support the findings of this study are available\u0026nbsp;upon\u0026nbsp;request from the corresponding author (L.N.).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eL.N.: first author; data collection and analysis, writing and reviewing the manuscript. L.M.: second author, data collection and curation, writing. J.S.: second author; data analysis; writing (reviewing and editing). L.YA. : data collection, curation and final analysis; writing (reviewing and editing) M.N.: data collection and curation, writing (reviewing and editing). B.A.: senior author; conceptualization; methodology; resources; writing (reviewing and editing); supervision.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eFairburn CG, Harrison PJ. Eating disorders. Lancet. 2003;361(9355):407\u0026ndash;416. doi: 10.1016/s0140-6736(03)12378-1\u003c/li\u003e\n \u003cli\u003eStern SA, Bulik CM. Alternative Frameworks for Advancing the Study of Eating Disorders. Trends in neurosciences 2020;43(12):951-9.\u003c/li\u003e\n \u003cli\u003eJenkins PE, Hoste RR, Meyer C, Blissett JM. Eating disorders and quality of life: A review of the literature. 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Eating and weight disorders : EWD 2022;27(2):415-28.\u003c/li\u003e\n \u003cli\u003eJahrami H, Saif Z, Faris MA, Levine MP. The relationship between risk of eating disorders, age, gender and body mass index in medical students: a meta-regression. Eating and weight disorders : EWD 2019;24(2):169-77.\u003c/li\u003e\n \u003cli\u003eFekih-Romdhane F, Daher-Nashif S, Alhuwailah AH, Al Gahtani HMS, Hubail SA, Shuwiekh HAM, Khudhair MF, Alhaj OA, Bragazzi NL, Jahrami H. The prevalence of feeding and eating disorders symptomology in medical students: an updated systematic review, meta-analysis, and meta-regression. Eating and weight disorders : EWD 2022;27(6):1991-2010.\u003c/li\u003e\n \u003cli\u003eFisher M, Gonzalez M, Malizio J. Eating disorders in adolescents: how does the DSM-5 change the diagnosis. International journal of adolescent medicine and health 2015;27(4):437-41.\u003c/li\u003e\n \u003cli\u003eDyrbye LN, Thomas MR, Shanafelt TD.. Systematic review of depression, anxiety, and other indicators of psychological distress among U.S. and Canadian medical students. Acad Med. 2006;81:354\u0026ndash;373\u003c/li\u003e\n \u003cli\u003ePeter C, Brosius HB. [The role of the media in the development, course, and management of eating disorders]. Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz 2021;64(1):55-61.\u003c/li\u003e\n \u003cli\u003eGao Y, Bagheri N, Furuya-Kanamori L. Has the COVID-19 pandemic lockdown worsened eating disorders symptoms among patients with eating disorders? A systematic review. Zeitschrift fur Gesundheitswissenschaften = Journal of Public Health 2022;30(11):2743-52.\u003c/li\u003e\n \u003cli\u003eSharan P, Sundar AS. Eating disorders in women. Indian journal of psychiatry 2015;57(Suppl 2):S286-95.\u003c/li\u003e\n \u003cli\u003eRosal MC, Ockene IS, Ockene JK, et al. A longitudinal study of students\u0026rsquo; depression at one medical school. Academic Medicine. 1997;72:542\u0026ndash;546\u003c/li\u003e\n \u003cli\u003eCompton MT, Carrera J, Frank E. Stress and depressive symptoms/dysphoria among US medical students: results from a large, nationally representative survey. J Nerv Ment Dis. 2008;196:891\u0026ndash;897\u003c/li\u003e\n \u003cli\u003eHill MR, Goicochea S, Merlo LJ. In their own words: stressors facing medical students in the millennial generation. Medical education online 2018;23(1):1530558.\u003c/li\u003e\n \u003cli\u003eHoukes I, Winants Y, Twellaar M, et al. Development of burnout over time and the causal order of the three dimensions of burnout among male and female GPs. A Three-Wave Panel Study. BMC Public Health.. 2011;11(1):240.\u003c/li\u003e\n \u003cli\u003eKabakuş Aykut M, Bilici S. The relationship between the risk of eating disorder and meal patterns in University students. Eating and weight disorders : EWD 2022;27(2):579-87.\u003c/li\u003e\n \u003cli\u003eMelchior V, Fuchs S, Scantamburlo G. [Obesity and eating disorders]. Revue medicale de Liege 2021;76(2):134-9.\u003c/li\u003e\n \u003cli\u003eFlament MF, Henderson K, Buchholz A, Obeid N, Nguyen HN, Birmingham M, Goldfield G. Weight Status and DSM-5 Diagnoses of Eating Disorders in Adolescents From the Community. Journal of the American Academy of Child and Adolescent Psychiatry 2015;54(5):403-411.e2.\u003c/li\u003e\n \u003cli\u003eBould H, Sovio U, Koupil I, Dalman C, Micali N, Lewis G, Magnusson C. Do eating disorders in parents predict eating disorders in children? Evidence from a Swedish cohort. Acta psychiatrica Scandinavica 2015;132(1):51-9.\u003c/li\u003e\n \u003cli\u003eAlghanami BH, El Keshky MES. The Relationship between the Family Environment and Eating Disorder Symptoms in a Saudi Nonclinical Sample of Students: A Moderated Mediated Model of Automatic Thoughts and Gender. Behavioral sciences (Basel, Switzerland) 2023;13(10):818.\u003c/li\u003e\n \u003cli\u003eStrober M, Freeman R, Lampert C, Diamond J, Kaye W. Controlled family study of anorexia nervosa and bulimia nervosa: evidence of shared liability and transmission of partial syndromes. The American journal of psychiatry 2000;157(3):393-401.\u003c/li\u003e\n \u003cli\u003eKendler KS, Ohlsson H, Sundquist J, Sundquist K. The patterns of family genetic risk scores for eleven major psychiatric and substance use disorders in a Swedish national sample. Translational psychiatry 2021;11(1):326.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"eating disorders, medical students, BMI, eating behaviors, risk factors","lastPublishedDoi":"10.21203/rs.3.rs-4232158/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4232158/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eEating disorders are among the most important psychiatric problems, and they are triggered by a complex network of factors. These disorders also seem to affect medical field students far more than others.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eTo determine the point prevalence of the risk of disordered eating behaviors in medical students at Damascus University and to study the possible reasons for this risk.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A cross-sectional study at Damascus University, Faculty of Medicine, was carried out between October and December of 2023. Data were collected from randomly sampled students from the second to sixth years via online surveys using the Eating Attitudes Test-26 (EAT-26) and the Sick, Control, One, Fat, Food (SCOFF) questionnaires as primary screening tools\u003cstrong\u003e. \u003c/strong\u003eBinary logistic regression was used to determine possible influencing factors on eating disorders.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eAmong the 829 participants, 11.3% had a greater risk of disordered eating behavior according to the EAT-26, and 20.3% had a greater risk according to the SCOFF. The average age was 21.29 years (1.76), and 67.6% of the participants’ body mass index (BMI) was within the normal range. Preclinical-aged female students (OR=1.89, p=0.009 for SCOFF and OR=0.66, p=0.017 for SCOFF) were at greater risk. Another important correlation was found between BMI and exposure to recent stressors (p\u0026lt;0.001 in both comparisons). However, age did not demonstrate any traceable importance (p=0.17) in addition to living or marital status (p=0.13 and p=0.18, respectively).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: There is a \u003c/strong\u003erisk of developing eating disorders among medical students, which might go unrecognized due to a lack of awareness of the importance of their detection. This risk also seems to stem from multiple risk factors that still require further research. Improving the relationship with psychological disorders and working on changing their rooted stigmatization will most likely prevent the escalation of these disorders in the future.\u003c/p\u003e","manuscriptTitle":"Prevalence and predictors of Eating Disorders’ risk in medical students at Damascus University: a cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-12 08:48:52","doi":"10.21203/rs.3.rs-4232158/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":"2ca62797-1586-430b-92aa-dc15e32a20db","owner":[],"postedDate":"April 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-05T14:44:37+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-12 08:48:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4232158","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4232158","identity":"rs-4232158","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}