Haitham Jahrami1,2, Zahraa Saif1, Mo'ez Al-Islam Faris3, Michael P Levine4. 1. Ministry of Health, Manama, Bahrain. 2. College of Medicine and Medical Sciences, Arabian Gulf University, Manama, Bahrain. 3. Department of Clinical Nutrition and Dietetics, College of Health Sciences/Sharjah Institute for Medical Research (SIMR), University of Sharjah, Sharjah, United Arab Emirates. 4. Emeritus Professor, Department of Psychology, Kenyon College, Gambier, OH, USA. levine@kenyon.edu.
Abstract
PURPOSE: Age, gender and body mass index (BMI) are commonly described risk factors for the development of eating disorders. However, the magnitude of these factors (individually and together) is still not well-defined in some populations. METHODS: A systematic search was performed for studies that reported the prevalence of eating disorder risk among medical students using the Eating Attitudes Test-26 (EAT-26) and age, gender and BMI as risk factors. We included studies published in English peer-reviewed journals between 1982 and 2017. A total of 14 studies were included in the analyses, and the meta-regression analyses were performed using mean age (years), gender (proportion of female subjects), and mean BMI (kg/m2) as moderators with the risk of eating disorders measured using EAT-26 as an outcome variable. Four interaction terms were created (1) age × gender (2) age × BMI (3) gender × BMI and (4) age × gender × BMI to assess if two or more independent variables simultaneously influence the outcome variable. RESULTS: Utilizing the EAT-26, the pooled prevalence of at risk for eating disorders among medical students (k = 14, N = 3520) was 10.5% (95% CI 7.3-13.7%). Meta-regression model of age, gender and BMI alone revealed poor predictive capabilities. Meta-regression model of age × gender × BMI interaction revealed statistically significant results with a covariate coefficient of 0.001 and p value of 0.044. CONCLUSION: Results from this sample of medical students provided evidence for the role of interactions between risk factors (e.g., age × gender × BMI) in predicting individuals at risk for eating disorders, whereas these variables individually failed to predict eating disorders. LEVEL OF EVIDENCE: Level I, systematic review and meta-analysis.
PURPOSE: Age, gender and body mass index (BMI) are commonly described risk factors for the development of eating disorders. However, the magnitude of these factors (individually and together) is still not well-defined in some populations. METHODS: A systematic search was performed for studies that reported the prevalence of eating disorder risk among medical students using the Eating Attitudes Test-26 (EAT-26) and age, gender and BMI as risk factors. We included studies published in English peer-reviewed journals between 1982 and 2017. A total of 14 studies were included in the analyses, and the meta-regression analyses were performed using mean age (years), gender (proportion of female subjects), and mean BMI (kg/m2) as moderators with the risk of eating disorders measured using EAT-26 as an outcome variable. Four interaction terms were created (1) age × gender (2) age × BMI (3) gender × BMI and (4) age × gender × BMI to assess if two or more independent variables simultaneously influence the outcome variable. RESULTS: Utilizing the EAT-26, the pooled prevalence of at risk for eating disorders among medical students (k = 14, N = 3520) was 10.5% (95% CI 7.3-13.7%). Meta-regression model of age, gender and BMI alone revealed poor predictive capabilities. Meta-regression model of age × gender × BMI interaction revealed statistically significant results with a covariate coefficient of 0.001 and p value of 0.044. CONCLUSION: Results from this sample of medical students provided evidence for the role of interactions between risk factors (e.g., age × gender × BMI) in predicting individuals at risk for eating disorders, whereas these variables individually failed to predict eating disorders. LEVEL OF EVIDENCE: Level I, systematic review and meta-analysis.
Entities:
Keywords:
Eating disorders; High risk; Meta-regression; Risk factors; University students
Authors: MoezAlIslam E Faris; Michael V Vitiello; Dana N Abdelrahim; Leila Cheikh Ismail; Haitham A Jahrami; Sharfa Khaleel; Maryam S Khan; Ayman Z Shakir; Ayesha M Yusuf; Alyaa A Masaad; Ahmed S Bahammam Journal: Sleep Breath Date: 2021-10-06 Impact factor: 2.655
Authors: Omar A Alhaj; Feten Fekih-Romdhane; Dima H Sweidan; Zahra Saif; Mina F Khudhair; Hadeel Ghazzawi; Mohammed Sh Nadar; Saad S Alhajeri; Michael P Levine; Haitham Jahrami Journal: Eat Weight Disord Date: 2022-08-04 Impact factor: 3.008
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