Predictors of Disordered Eating Behaviors Among Nutrition and Dietetics Professionals and Athletes in Jordan: A Cross-Sectional Study

Predictors of Disordered Eating Behaviors Among Nutrition and Dietetics Professionals and Athletes in Jordan: 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 Predictors of Disordered Eating Behaviors Among Nutrition and Dietetics Professionals and Athletes in Jordan: A Cross-Sectional Study Feda Abu Al-Khair, Numan Al-Natsheh, Omar Ali, Ammar Al Maharmah, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8562775/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 - Disordered eating behaviors are influenced by a variety of personal and professional factors. Professions that emphasize body image, such as nutrition and athletics, may be particularly vulnerable to these behaviors. This study aimed to examine disordered eating behaviors and investigate potential predictors, including professional specialization, BMI, educational attainment, and age, among nutritionists and athletes in Jordan. Methods - A cross-sectional design was used with self-report questionnaires administered to 190 participants (138 nutritionists, 51 athletes) aged 18 to 50 years (M = 28.8, SD = 7.8). Disordered eating behaviors were assessed using the Arabic version of the Eating Attitudes Test (EAT-26). Demographic variables, BMI categories, educational levels, and age were analyzed as potential predictors. Descriptive statistics and logistic regression analyses were conducted. Results - Logistic regression analysis revealed that athletes had significantly higher odds of disordered eating risk compared to nutritionists (OR = 7.75, 95% CI [3.35, 17.91], p < .001). Participants with secondary education or lower were at increased risk compared to those with postgraduate degrees (OR = 0.27, 95% CI [0.07, 0.93], p = .013). BMI was also associated with risk, with individuals in the underweight and normal weight categories showing higher odds of disordered eating compared to those classified as overweight. Conclusions - The findings suggest that professional specialization, educational attainment, and BMI are significant predictors of disordered eating risk among nutritionists and athletes in Jordan. These results underscore the importance of early identification and targeted interventions for individuals in professions where food, body image, and performance are closely linked. Eating disorders EAT-26 nutritionists athletes BMI orthorexia nervosa diet culture predictive factors Introduction Disordered eating behaviors inhibit a broad spectrum of maladaptive attitudes and practices related to food intake, weight control, and body image. These can range from unhealthy dieting and weight-management approaches to subclinical indicators of eating disorders [ 1 ]. Extensive research in the general population has thoroughly investigated the prevalence of disordered eating and clinical eating disorders. for example, global estimates suggest that roughly 8–9% of women and 4% of men will experience an eating disorder in their lifetime [ 2 ]. This suggests that much attention has been focused towards measuring how common these behaviors are in the general population. While several reviews have explored disordered eating in athletes, fewer studies have examined the underlying predictors of these behaviors within professional subgroups, especially those in the Middle East., where body image and nutrition are a key aspect to one’s role or identity. Researchers have pointed out that, despite the high rates of disordered eating observed in groups like athletes, it remains unclear whether the contributing risk factors emulate those in the general population or if unique, context-specific factors are at play [ 3 ]. In other words, while prevalence data in these groups exist, the predictors of such behaviors are not as well investigated or understood. Recent literature within the realm of psychological disorders highlights an increased risk of eating pathology within professions that emphasize physical appearance or body weight as either an advantage or a core requirement. Dancers, models, and military personnel have been found to exhibit elevated rates of EDs, often due to occupational pressures associated with their performance, varying fitness standards, and body image [ 4 , 5 ]. Over the years, athletes have been increasingly labelled as a high-risk group for eating disorders, particularly when excessive physical activity is used for weight control or when sports stress leanness or appearance [ 6 ]. Similarly, dietitians and nutrition students may face unique challenges that place them at heightened risk. A prime example of such challenges include constant engagement with dietary content, societal pressures to embody an ideal body type, and constant exposure to weight stigma and diet culture within professional training and practice [ 7 , 8 ]. While dietitians are trained to promote health and nutritional well-being, their role often involves self-monitoring and evaluation of dietary practices, potentially developing cognitive rigidity around food choices. Such behavior may predispose them to orthorexic tendencies, wherein the pursuit of healthful eating becomes abnormal, maladaptive and obsessive [ 9 ]. Several studies suggest that individuals may be drawn to the field of dietetics and nutrition due to pre-existing negative beliefs related to food and body image, while others indicate that training in dietetics itself may increase the risk for disordered eating, particularly in academic environments where slimness and health are glorified [ 10 , 11 ]. Despite this emerging evidence, few studies have examined the prevalence of eating disorders among nutritionists within the Middle East, particularly in Jordan. Moreover, comparative investigations between dietitians and other body-focused professional groups, such as athletes, remain insufficiently studied. Athletes, especially in aesthetic or weight-reliant sports, are also known to experience high levels of disordered eating behaviors, driven by high performance demands and unrealistic body composition goals [ 12 ]. Understanding how these two professions deviate, or align, in terms of different eating behaviors pathology can provide necessary insights for prevention and intervention plans. This study investigates associations between disordered eating risk and various sociodemographic and professional factors in a sample of Jordanian nutrition professionals and athletes.. By using the Arabic version of the Eating Attitudes Test (EAT-26), this study aims to explore potential risk factors in culturally and professionally distinct populations who may share similar challenges related to body image and food consumption. Methods Participants The study included a total of 190 participants: 138 participants within the professional field of nutrition and dietetics, in addition to 51 athletes from multiple sport specializations. Participants age ranged from 18 to 50 years, with a mean age of 28.8 ± 7.8 years. The mean age of nutritionists was 27.4 ± 7.5 years, and for athletes, it was 32.2 ± 7.4 years. The average BMI for the overall sample was 26.6 ± 4.2 kg/m², with subgroup means of 24.4 ± 4.1 for nutritionists and 25.1 ± 4.2 for athletes. Participants were recruited through convenience sampling from January 2024 to March 2024. Nutritionists and nutrition students were primarily recruited via WhatsApp groups dedicated to professional and academic nutrition communities. Athletes were recruited through sport centers across Jordan, including private gyms and training clubs, where staff and facility networks assisted in participant outreach. The use of these targeted platforms aimed to reach individuals actively involved in each respective field. Recruitment targeted individuals actively working or studying within nutrition-related fields (dietitians, nutrition students) and athletes involved in various sports disciplines within Jordan. Inclusion criteria were between 18–50 years of age, currently studying or working in nutrition/dietetics or actively engaged in professional or competitive athletics. Individuals were excluded if they had no direct involvement in these fields. It is important to note that due to the voluntary nature of participation and the use of convenience sampling, the study is subject to potential self-selection bias, particularly if individuals with greater interest or concern regarding eating behaviors were more likely to respond. Demographic data, including education level and BMI, were collected. The sample included individuals with secondary education or lower (18.9%), bachelor's degrees (64.7%), and postgraduate education (15.8%). Participation was voluntary. Informed consent was acquired from all participants after being informed of the study’s objective. Ethical approval for the study was granted by the Research Ethics Committee at Al-Ahliyya Amman University. Instruments The Arabic translated version of the Eating Attitudes Test (EAT-26) was utilized to assess disordered eating tendencies and behaviors. The EAT-26 is a widely validated self-report questionnaire consisting of 26 items that assess attitudes, thoughts, and behaviors relating to food, weight, and eating. Responses are then rated on a 6-point Likert scale ranging from “Never” to “Always.” Higher scores demonstrate a heightened risk of disordered eating behaviors, with a score of 21 or higher, suggesting possible clinical concern and justifying further evaluation by a mental health professional [ 13 ]. The Arabic translated scale of the EAT-26 utilized in this study has demonstrated strong psychometric properties in previous research conducted within Arabic-speaking populations, including high internal consistency reliability (Cronbach’s alpha = .89; calculated from the study’s current sample). Statistical Analysis Participants scoring 21 or higher on the EAT-26 were classified as being at increased risk for disordered eating, and logistic regression was used to examine potential predictors of this risk. Based on these scores, participants were appropriately placed into two groups: low-risk (EAT-26 < 21) and high-risk (EAT-26 ≥ 21). To determine the predictors of disordered eating risk, a binary logistic regression was conducted with the EAT-26 classification as the dependent variable. Independent variables included the participants specialization (nutritionist vs. athlete), age group (18–25, 26–30, 31–40, 41–50), educational level (high school or less, undergraduate, postgraduate), and their BMI category (underweight, normal weight, overweight). Each categorical variables were assigned a numerical code value to enable its inclusion in our analysis, with athletes, participants aged 41–50, those holding postgraduate degrees, and overweight individuals used as reference categories. Odds ratios (OR) and 95% confidence intervals (CI) were calculated for each predictor. Descriptive statistical data including means, standard deviations, and frequencies were used to summarize demographic and clinical variables. All analyses were conducted using IBM Statistical Package for the Social Sciences (SPSS, v.23). A significance threshold of p < .05 was applied. Participants with missing values in any of the key variables were excluded listwise from the regression model. No imputation was performed. Results The final sample consisted of 190 participants (138 nutritionists and 51 athletes) that had completed the assessment. The participants ages have ranged from 18 to 50 years, with a mean age being 28.8 ± 7.8 years. The mean BMI was 26.6 ± 4.2 kg/m². Table 1 summarizes the demographic and anthropometric characteristics of the sample. Table 1 Demographic and Anthropometric Characteristics of Participants by Group (General Group, Nutritionists, and Athletes) All (n = 190) Nutritionist (n = 190) Athletes (n = 190) mean SD mean SD mean SD Age (years) 28.8 7.8 27.4 7.5 32.2 7.4 Weight (kg) Current 64.7 11.6 63.5 11.3 68.1 11.8 Highest 72.1 14.9 70.6 14.6 76.4 15.3 Lowest 56.6 9.8 56.3 9.7 57.5 10.3 Ideal 58.3 6.4 57.54 5.8 60.4 7.6 Height (cm) 162.2 6.3 161.1 5.5 164.6 7.6 BMI (kg/m²) 26.6 4.2 24.4 4.1 25.1 4.2 Education level n % n % n % Diploma or Less 36 18.9 23 16.7 13 25.5 Bachelor's degree 123 64.7 91 65.9 32 62.7 Postgraduate studies 30 15.8 24 17.4 6 11.8 Based on the Eating Attitudes Test (EAT-26), 60.5% (n = 115) scored at or above the clinical cutoff, indicating a high risk for disordered eating behaviors. A higher percentage of athletes (70.6%) were classified to being at a higher risk compared to the nutritionists (28.3%). The magnitude of high EAT-26 scores fluctuated across education levels, with 61.1% of participants with high school education or less falling into the high-risk group, compared to 35.8% of undergraduates and 30.0% of postgraduates. Disordered eating behaviors were most prevalent among participants classified as overweight (50.6%), followed closely by those with normal weight (32.7%) and then underweight (22.2%). To identify factors associated with increased risk for disordered eating behaviors, binary logistic regression was used with EAT-26 risk classification as the dependent variable and specialization, age, education, and BMI as predictors. Specialization has been indicated as a significant predictor of disordered eating risk, with nutritionists being significantly less likely to be classified as high risk compared to the athletes (OR = 7.75, 95% CI [3.35, 17.91], p < .001). The participants’ educational level was also associated with EAT-26 classification, as individuals with high school education or lower were at a significantly greater risk compared to postgraduates (OR = 0.27, 95% CI [0.07, 0.93], p = .038). BMI category was not statistically significant: participants in normal weight category were at a higher risk compared to those who are in the overweight category (OR = 2.03, 95% CI [1.00, 4.12], p = .050), while those in the underweight category showed an inclination toward elevated risk (OR = 6.00, 95% CI [1.01, 36.27], p = .052). Age group was not a significant predictor across any of the categories included in the model ( p > .05). Model fit statistics indicated an acceptable model (Pseudo R² = 0.18; LLR p < .001), supporting the role of these factors in predicting disordered eating risk. Full regression results are presented in Table 2 . Table 2 Prevalence of Eating Disorders Risk and Its Association with Specialization, Age, Educational Level, and Body Mass Index (BMI) Dependent variable EAT 26 ≤ 20 EAT 26 > 20 OR (95%CI) P Specialization Nutritionist 99 (71.7%) 39 (28.3%) 0.146 (.081-.333) .000 Athletes (Ref) 15 (29.4%) 36 (70.6%) 1 Age 18–25 52 (62.7%) 31 (37.3%) 2.388 (.612-9.327) .210 26–30 26 (68.4%) 12 (31.6%) .786 (.179-3.462) .750 31–40 26(51%) 25 (49%) 1.906 (.479-7.581) .360 41–50 (Ref) 11 (61.1%) 7 (38.9%) 1 52 (62.7%) 31 (37.3%) Educational Level High School 14 (38.9%) 22 (61.1%) 3.667 (.321 − 4.350) .013 Undergraduate 79 (64.2%) 44 (35.8%) 1.300 (.0584-3.082) .552 Postgraduate (Ref) 21 70.0%) 9 (30.0%) 1 BMI underweight 7 (77.8%) 2 (22.2%) .167 (.028 − .1.012 ) .052 Normal Weight 66 (67.3%) 32 (32.7%) .493 (.243- 1.001) .050 Overweight (Ref) 38 (49.4%) 39 (50.6%) 1 Discussion Overall, the findings of this study revealed a particularly high prevalence of disordered eating behaviors among both the nutrition professionals and athletes in Jordan, with the athletes in particular showing significantly higher risk levels. These findings align well with the earlier literature suggesting that individuals and professionals involved in weight-sensitive or performance-reliant disciplines are often faced with increased levels of vulnerability to eating-related disturbances [ 6 , 13 ]. The present study contributes to that body of evidence, further emphasizing the necessity for targeted screening and intervention plans within athletic communities, predominantly those under intense physical or aesthetic pressure. As demonstrated in the study’s findings, individuals with lower educational levels were more prone to disordered eating compared to those with postgraduate degrees. An interpretation for that can be due to the differences in nutrition literacy, critical thinking, or access to supportive communities that promote healthier relationships with food. A similar pattern can be seen to be highlighted in other studies, suggesting that education may play a protective role by equipping individuals with tools to resist cultural and professional pressures related to body image [ 7 , 8 ]. BMI also emerged as an insignificant predictor. While overweight participants showed the highest prevalence of disordered eating behaviors, those classified as underweight have also demonstrated elevated risk, it is worth noting that the sample size in this group was relatively small. These findings support the recent literature on that disordered eating is not limited to one end of the weight spectrum, however, it can affect individuals across a range of body sizes, an argument that emphasizes the idea that weight alone should not be used as a sole indicator for identifying at-risk individuals [ 9 ]. Similarly, age is shown to be an insignificant predictor for risks associated with disordered eating, which might be due to the relatively limited age range and overlapping life stages among the study’s participants. Since most individuals in both groups consisted of young adults or early professionals, age-related variation may have been limited. Another particularly noteworthy finding is the heightened risk among nutrition professionals group. While one would usually assume that academic and formal training in nutrition supposedly acts as a protective factor, previous literature, alongside this study’s findings suggest otherwise; it’s been shown that continuous exposure to various diet cultures, nutritional monitoring, and weight-focused lifestyle are in fact exacerbating factors for disordered attitudes; a dynamic sometimes referred to as "professional vulnerability" [ 11 , 12 ]. This sheds light on a clear contradiction within the field of dietetics: those tasked with promoting health may be silently struggling with the same disordered behaviors they aim to prevent in others. This study has a number of limitations that should be acknowledged. The use of convenience sampling and recruitment via WhatsApp groups and sport centers introduces a risk of self-selection bias, as individuals who are more concerned about food, weight, or body image may have been more likely to participate. This limits the generalizability of the findings and should be considered when interpreting the results. Additionally, it’s important to clarify that although the EAT-26 is a validated tool, it does not provide clinical diagnoses, and further psychological assessment by a mental health professional would be needed to confirm eating disorder cases. Despite these limitations, the study provides important insights into various factors that may contribute to disordered eating behaviors in professional groups that are often overlooked in Middle Eastern research. Future studies should aim for larger, more diverse samples and consider including qualitative methods to better understand the lived experiences behind the numerical data. Conclusions This study highlights that disordered eating behaviors were common in this sample, particularly among athletes. Lower educational attainment and certain BMI categories emerged as predictive factors, underscoring the need for targeted interventions in these groups. Future research with broader, more representative samples is recommended to confirm and expand these findings. Abbreviations EDs Eating Disorders ON Orthorexia Nervosa BMI Body Mass Index EAT-26 Eating Attitudes Test – 26 SPSS Statistical Package for the Social Sciences OR Odds Ratio CI Confidence Interval Declarations Ethics approval and consent to participate Ethical approval was obtained from the Research Ethics Committee at Al-Ahliyya Amman University. Written informed consent was obtained from all participants. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Funding No funding was received for this research. Author Contribution FA conceptualized and supervised the study. NA and DH conducted the statistical analysis. OA performed manuscript writing, formatting, and reviewing. AM contributed to data collection and reviewed the manuscript. DK provided expert insight into nutrition and eating disorders. HS assisted with data management and manuscript review. All authors read and approved of the final manuscript. Acknowledgements The authors would like to thank all the participants for their contributions. Data Availability The datasets generated and/or analyzed during the current study are not publicly available due to including patient information that was not consented to be publicly available, but they are available from the corresponding author at reasonable request. References Bonci CM, Bonci LJ, Granger LR, Johnson CL, Malina RM, Milne LW, Ryan RR, Vanderbunt EM. National athletic trainers' association position statement: preventing, detecting, and managing disordered eating in athletes. Journal of Athletic Training. 2008;43(1):80–108. https://doi.org/10.4085/1062-6050-43.1.80 Barakat S, McLean SA, Bryant E, Le A, Marks P, Touyz S, Maguire S. Risk factors for eating disorders: findings from a rapid review. Journal of Eating Disorders. 2023;11(1):8. https://doi.org/10.1186/s40337-022-00717-4 Fatt SJ, George E, Hay P, Jeacocke N, Mitchison D. 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Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDisordered eating behaviors inhibit a broad spectrum of maladaptive attitudes and practices related to food intake, weight control, and body image. These can range from unhealthy dieting and weight-management approaches to subclinical indicators of eating disorders [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Extensive research in the general population has thoroughly investigated the prevalence of disordered eating and clinical eating disorders. for example, global estimates suggest that roughly 8\u0026ndash;9% of women and 4% of men will experience an eating disorder in their lifetime [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This suggests that much attention has been focused towards measuring how common these behaviors are in the general population. While several reviews have explored disordered eating in athletes, fewer studies have examined the underlying predictors of these behaviors within professional subgroups, especially those in the Middle East., where body image and nutrition are a key aspect to one\u0026rsquo;s role or identity. Researchers have pointed out that, despite the high rates of disordered eating observed in groups like athletes, it remains unclear whether the contributing risk factors emulate those in the general population or if unique, context-specific factors are at play [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In other words, while prevalence data in these groups exist, the predictors of such behaviors are not as well investigated or understood.\u003c/p\u003e \u003cp\u003eRecent literature within the realm of psychological disorders highlights an increased risk of eating pathology within professions that emphasize physical appearance or body weight as either an advantage or a core requirement. Dancers, models, and military personnel have been found to exhibit elevated rates of EDs, often due to occupational pressures associated with their performance, varying fitness standards, and body image [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Over the years, athletes have been increasingly labelled as a high-risk group for eating disorders, particularly when excessive physical activity is used for weight control or when sports stress leanness or appearance [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Similarly, dietitians and nutrition students may face unique challenges that place them at heightened risk. A prime example of such challenges include constant engagement with dietary content, societal pressures to embody an ideal body type, and constant exposure to weight stigma and diet culture within professional training and practice [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhile dietitians are trained to promote health and nutritional well-being, their role often involves self-monitoring and evaluation of dietary practices, potentially developing cognitive rigidity around food choices. Such behavior may predispose them to orthorexic tendencies, wherein the pursuit of healthful eating becomes abnormal, maladaptive and obsessive [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Several studies suggest that individuals may be drawn to the field of dietetics and nutrition due to pre-existing negative beliefs related to food and body image, while others indicate that training in dietetics itself may increase the risk for disordered eating, particularly in academic environments where slimness and health are glorified [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite this emerging evidence, few studies have examined the prevalence of eating disorders among nutritionists within the Middle East, particularly in Jordan. Moreover, comparative investigations between dietitians and other body-focused professional groups, such as athletes, remain insufficiently studied. Athletes, especially in aesthetic or weight-reliant sports, are also known to experience high levels of disordered eating behaviors, driven by high performance demands and unrealistic body composition goals [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Understanding how these two professions deviate, or align, in terms of different eating behaviors pathology can provide necessary insights for prevention and intervention plans.\u003c/p\u003e \u003cp\u003eThis study investigates associations between disordered eating risk and various sociodemographic and professional factors in a sample of Jordanian nutrition professionals and athletes.. By using the Arabic version of the Eating Attitudes Test (EAT-26), this study aims to explore potential risk factors in culturally and professionally distinct populations who may share similar challenges related to body image and food consumption.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eThe study included a total of 190 participants: 138 participants within the professional field of nutrition and dietetics, in addition to 51 athletes from multiple sport specializations. Participants age ranged from 18 to 50 years, with a mean age of 28.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8 years. The mean age of nutritionists was 27.4\u0026thinsp;\u0026plusmn;\u0026thinsp;7.5 years, and for athletes, it was 32.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.4 years. The average BMI for the overall sample was 26.6\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2 kg/m\u0026sup2;, with subgroup means of 24.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1 for nutritionists and 25.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2 for athletes.\u003c/p\u003e \u003cp\u003eParticipants were recruited through convenience sampling from January 2024 to March 2024. Nutritionists and nutrition students were primarily recruited via WhatsApp groups dedicated to professional and academic nutrition communities. Athletes were recruited through sport centers across Jordan, including private gyms and training clubs, where staff and facility networks assisted in participant outreach. The use of these targeted platforms aimed to reach individuals actively involved in each respective field. Recruitment targeted individuals actively working or studying within nutrition-related fields (dietitians, nutrition students) and athletes involved in various sports disciplines within Jordan. Inclusion criteria were between 18\u0026ndash;50 years of age, currently studying or working in nutrition/dietetics or actively engaged in professional or competitive athletics. Individuals were excluded if they had no direct involvement in these fields. It is important to note that due to the voluntary nature of participation and the use of convenience sampling, the study is subject to potential self-selection bias, particularly if individuals with greater interest or concern regarding eating behaviors were more likely to respond.\u003c/p\u003e \u003cp\u003eDemographic data, including education level and BMI, were collected. The sample included individuals with secondary education or lower (18.9%), bachelor's degrees (64.7%), and postgraduate education (15.8%).\u003c/p\u003e \u003cp\u003eParticipation was voluntary. Informed consent was acquired from all participants after being informed of the study\u0026rsquo;s objective. Ethical approval for the study was granted by the Research Ethics Committee at Al-Ahliyya Amman University.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eInstruments\u003c/h3\u003e\n\u003cp\u003eThe Arabic translated version of the Eating Attitudes Test (EAT-26) was utilized to assess disordered eating tendencies and behaviors. The EAT-26 is a widely validated self-report questionnaire consisting of 26 items that assess attitudes, thoughts, and behaviors relating to food, weight, and eating. Responses are then rated on a 6-point Likert scale ranging from \u0026ldquo;Never\u0026rdquo; to \u0026ldquo;Always.\u0026rdquo; Higher scores demonstrate a heightened risk of disordered eating behaviors, with a score of 21 or higher, suggesting possible clinical concern and justifying further evaluation by a mental health professional [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Arabic translated scale of the EAT-26 utilized in this study has demonstrated strong psychometric properties in previous research conducted within Arabic-speaking populations, including high internal consistency reliability (Cronbach\u0026rsquo;s alpha\u0026thinsp;=\u0026thinsp;.89; calculated from the study\u0026rsquo;s current sample).\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eParticipants scoring 21 or higher on the EAT-26 were classified as being at increased risk for disordered eating, and logistic regression was used to examine potential predictors of this risk. Based on these scores, participants were appropriately placed into two groups: low-risk (EAT-26\u0026thinsp;\u0026lt;\u0026thinsp;21) and high-risk (EAT-26\u0026thinsp;\u0026ge;\u0026thinsp;21).\u003c/p\u003e \u003cp\u003eTo determine the predictors of disordered eating risk, a binary logistic regression was conducted with the EAT-26 classification as the dependent variable. Independent variables included the participants specialization (nutritionist vs. athlete), age group (18\u0026ndash;25, 26\u0026ndash;30, 31\u0026ndash;40, 41\u0026ndash;50), educational level (high school or less, undergraduate, postgraduate), and their BMI category (underweight, normal weight, overweight).\u003c/p\u003e \u003cp\u003eEach categorical variables were assigned a numerical code value to enable its inclusion in our analysis, with athletes, participants aged 41\u0026ndash;50, those holding postgraduate degrees, and overweight individuals used as reference categories. Odds ratios (OR) and 95% confidence intervals (CI) were calculated for each predictor.\u003c/p\u003e \u003cp\u003eDescriptive statistical data including means, standard deviations, and frequencies were used to summarize demographic and clinical variables. All analyses were conducted using IBM Statistical Package for the Social Sciences (SPSS, v.23). A significance threshold of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05 was applied. Participants with missing values in any of the key variables were excluded listwise from the regression model. No imputation was performed.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe final sample consisted of 190 participants (138 nutritionists and 51 athletes) that had completed the assessment. The participants ages have ranged from 18 to 50 years, with a mean age being 28.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8 years. The mean BMI was 26.6\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2 kg/m\u0026sup2;. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the demographic and anthropometric characteristics of the sample.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic and Anthropometric Characteristics of Participants by Group (General Group, Nutritionists, and Athletes)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;190)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eNutritionist\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;190)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eAthletes\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;190)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003emean\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003emean\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003emean\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWeight (kg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e68.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHighest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e76.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLowest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIdeal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e162.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e161.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e164.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiploma or Less\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor's degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e62.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostgraduate studies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.8\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\u003eBased on the Eating Attitudes Test (EAT-26), 60.5% (n\u0026thinsp;=\u0026thinsp;115) scored at or above the clinical cutoff, indicating a high risk for disordered eating behaviors. A higher percentage of athletes (70.6%) were classified to being at a higher risk compared to the nutritionists (28.3%). The magnitude of high EAT-26 scores fluctuated across education levels, with 61.1% of participants with high school education or less falling into the high-risk group, compared to 35.8% of undergraduates and 30.0% of postgraduates. Disordered eating behaviors were most prevalent among participants classified as overweight (50.6%), followed closely by those with normal weight (32.7%) and then underweight (22.2%).\u003c/p\u003e \u003cp\u003eTo identify factors associated with increased risk for disordered eating behaviors, binary logistic regression was used with EAT-26 risk classification as the dependent variable and specialization, age, education, and BMI as predictors. Specialization has been indicated as a significant predictor of disordered eating risk, with nutritionists being significantly less likely to be classified as high risk compared to the athletes (OR\u0026thinsp;=\u0026thinsp;7.75, 95% CI [3.35, 17.91], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). The participants\u0026rsquo; educational level was also associated with EAT-26 classification, as individuals with high school education or lower were at a significantly greater risk compared to postgraduates (OR\u0026thinsp;=\u0026thinsp;0.27, 95% CI [0.07, 0.93], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.038). BMI category was not statistically significant: participants in normal weight category were at a higher risk compared to those who are in the overweight category (OR\u0026thinsp;=\u0026thinsp;2.03, 95% CI [1.00, 4.12], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.050), while those in the underweight category showed an inclination toward elevated risk (OR\u0026thinsp;=\u0026thinsp;6.00, 95% CI [1.01, 36.27], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.052). Age group was not a significant predictor across any of the categories included in the model (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;.05). Model fit statistics indicated an acceptable model (Pseudo R\u0026sup2; = 0.18; LLR \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), supporting the role of these factors in predicting disordered eating risk. Full regression results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of Eating Disorders Risk and Its Association with Specialization, Age, Educational Level, and Body Mass Index (BMI)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eDependent variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEAT 26\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;20\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEAT 26\u0026thinsp;\u0026gt;\u0026thinsp;20\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecialization\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNutritionist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99 (71.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 (28.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.146 (.081-.333)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAthletes (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (29.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (70.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (62.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31 (37.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.388 (.612-9.327)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.210\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (68.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (31.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.786 (.179-3.462)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.750\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26(51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.906 (.479-7.581)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.360\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e41\u0026ndash;50 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (61.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (38.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (62.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31 (37.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational Level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (38.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (61.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.667 (.321\u0026thinsp;\u0026minus;\u0026thinsp;4.350)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUndergraduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79 (64.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44 (35.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.300 (.0584-3.082)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.552\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostgraduate (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 70.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (30.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eunderweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (77.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (22.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.167 (.028 \u0026minus;\u0026thinsp;.1.012 )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.052\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal Weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66 (67.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32 (32.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.493 (.243- 1.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.050\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (49.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 (50.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOverall, the findings of this study revealed a particularly high prevalence of disordered eating behaviors among both the nutrition professionals and athletes in Jordan, with the athletes in particular showing significantly higher risk levels. These findings align well with the earlier literature suggesting that individuals and professionals involved in weight-sensitive or performance-reliant disciplines are often faced with increased levels of vulnerability to eating-related disturbances [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The present study contributes to that body of evidence, further emphasizing the necessity for targeted screening and intervention plans within athletic communities, predominantly those under intense physical or aesthetic pressure.\u003c/p\u003e \u003cp\u003eAs demonstrated in the study\u0026rsquo;s findings, individuals with lower educational levels were more prone to disordered eating compared to those with postgraduate degrees. An interpretation for that can be due to the differences in nutrition literacy, critical thinking, or access to supportive communities that promote healthier relationships with food. A similar pattern can be seen to be highlighted in other studies, suggesting that education may play a protective role by equipping individuals with tools to resist cultural and professional pressures related to body image [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBMI also emerged as an insignificant predictor. While overweight participants showed the highest prevalence of disordered eating behaviors, those classified as underweight have also demonstrated elevated risk, it is worth noting that the sample size in this group was relatively small. These findings support the recent literature on that disordered eating is not limited to one end of the weight spectrum, however, it can affect individuals across a range of body sizes, an argument that emphasizes the idea that weight alone should not be used as a sole indicator for identifying at-risk individuals [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSimilarly, age is shown to be an insignificant predictor for risks associated with disordered eating, which might be due to the relatively limited age range and overlapping life stages among the study\u0026rsquo;s participants. Since most individuals in both groups consisted of young adults or early professionals, age-related variation may have been limited.\u003c/p\u003e \u003cp\u003eAnother particularly noteworthy finding is the heightened risk among nutrition professionals group. While one would usually assume that academic and formal training in nutrition supposedly acts as a protective factor, previous literature, alongside this study\u0026rsquo;s findings suggest otherwise; it\u0026rsquo;s been shown that continuous exposure to various diet cultures, nutritional monitoring, and weight-focused lifestyle are in fact exacerbating factors for disordered attitudes; a dynamic sometimes referred to as \"professional vulnerability\" [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This sheds light on a clear contradiction within the field of dietetics: those tasked with promoting health may be silently struggling with the same disordered behaviors they aim to prevent in others.\u003c/p\u003e \u003cp\u003eThis study has a number of limitations that should be acknowledged. The use of convenience sampling and recruitment via WhatsApp groups and sport centers introduces a risk of self-selection bias, as individuals who are more concerned about food, weight, or body image may have been more likely to participate. This limits the generalizability of the findings and should be considered when interpreting the results. Additionally, it\u0026rsquo;s important to clarify that although the EAT-26 is a validated tool, it does not provide clinical diagnoses, and further psychological assessment by a mental health professional would be needed to confirm eating disorder cases.\u003c/p\u003e \u003cp\u003eDespite these limitations, the study provides important insights into various factors that may contribute to disordered eating behaviors in professional groups that are often overlooked in Middle Eastern research. Future studies should aim for larger, more diverse samples and consider including qualitative methods to better understand the lived experiences behind the numerical data.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study highlights that disordered eating behaviors were common in this sample, particularly among athletes. Lower educational attainment and certain BMI categories emerged as predictive factors, underscoring the need for targeted interventions in these groups. Future research with broader, more representative samples is recommended to confirm and expand these findings.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eEDs\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEating Disorders\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eON\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOrthorexia Nervosa\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBody Mass Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eEAT-26\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEating Attitudes Test \u0026ndash; 26\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSPSS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStatistical Package for the Social Sciences\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eOR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOdds Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence Interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e Ethical approval was obtained from the Research Ethics Committee at Al-Ahliyya Amman University. Written informed consent was obtained from all participants.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eNo funding was received for this research.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eFA conceptualized and supervised the study. NA and DH conducted the statistical analysis. OA performed manuscript writing, formatting, and reviewing. AM contributed to data collection and reviewed the manuscript. DK provided expert insight into nutrition and eating disorders. HS assisted with data management and manuscript review. All authors read and approved of the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThe authors would like to thank all the participants for their contributions.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available due to including patient information that was not consented to be publicly available, but they are available from the corresponding author at reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBonci CM, Bonci LJ, Granger LR, Johnson CL, Malina RM, Milne LW, Ryan RR, Vanderbunt EM. National athletic trainers' association position statement: preventing, detecting, and managing disordered eating in athletes. 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Body Image. 2022;40:340\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.bodyim.2022.01.014\u003c/span\u003e\u003cspan address=\"10.1016/j.bodyim.2022.01.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Subaie A, Al‐Shammari S, Bamgboye E, Al‐Sabhan K, Al‐Shehri S, Bannah AR. Validity of the Arabic version of the eating attitude test. International Journal of Eating Disorders. 1996;20(3):321\u0026ndash;4. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/(SICI)1098-108X(199611)20:3%3C321::AID-EAT12%3E3.0.CO;2-2\u003c/span\u003e\u003cspan address=\"10.1002/(SICI)1098-108X(199611)20:3%3C321::AID-EAT12%3E3.0.CO;2-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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, EAT-26, nutritionists, athletes, BMI, orthorexia nervosa, diet culture, predictive factors","lastPublishedDoi":"10.21203/rs.3.rs-8562775/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8562775/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground -\u003c/h2\u003e \u003cp\u003eDisordered eating behaviors are influenced by a variety of personal and professional factors. Professions that emphasize body image, such as nutrition and athletics, may be particularly vulnerable to these behaviors. This study aimed to examine disordered eating behaviors and investigate potential predictors, including professional specialization, BMI, educational attainment, and age, among nutritionists and athletes in Jordan.\u003c/p\u003e\u003ch2\u003eMethods -\u003c/h2\u003e \u003cp\u003eA cross-sectional design was used with self-report questionnaires administered to 190 participants (138 nutritionists, 51 athletes) aged 18 to 50 years (M\u0026thinsp;=\u0026thinsp;28.8, SD\u0026thinsp;=\u0026thinsp;7.8). Disordered eating behaviors were assessed using the Arabic version of the Eating Attitudes Test (EAT-26). Demographic variables, BMI categories, educational levels, and age were analyzed as potential predictors. Descriptive statistics and logistic regression analyses were conducted.\u003c/p\u003e\u003ch2\u003eResults -\u003c/h2\u003e \u003cp\u003eLogistic regression analysis revealed that athletes had significantly higher odds of disordered eating risk compared to nutritionists (OR\u0026thinsp;=\u0026thinsp;7.75, 95% CI [3.35, 17.91], p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Participants with secondary education or lower were at increased risk compared to those with postgraduate degrees (OR\u0026thinsp;=\u0026thinsp;0.27, 95% CI [0.07, 0.93], p\u0026thinsp;=\u0026thinsp;.013). BMI was also associated with risk, with individuals in the underweight and normal weight categories showing higher odds of disordered eating compared to those classified as overweight.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003e- The findings suggest that professional specialization, educational attainment, and BMI are significant predictors of disordered eating risk among nutritionists and athletes in Jordan. These results underscore the importance of early identification and targeted interventions for individuals in professions where food, body image, and performance are closely linked.\u003c/p\u003e","manuscriptTitle":"Predictors of Disordered Eating Behaviors Among Nutrition and Dietetics Professionals and Athletes in Jordan: A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-13 08:49:38","doi":"10.21203/rs.3.rs-8562775/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":"53793802-6272-4a83-9e99-642b8d3a0e71","owner":[],"postedDate":"January 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-23T04:24:46+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-13 08:49:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8562775","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8562775","identity":"rs-8562775","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}