Samantha L Hahn1, Kendrin R Sonneville2, Niko Kaciroti3, Daniel Eisenberg4, Katherine W Bauer2. 1. Division of Epidemiology & Community Health, University of Minnesota School of Public Health, 1300 S 2nd St Unit 300, Minneapolis, MN 55454, United States of America; Department of Psychiatry & Behavioral Sciences, University of Minnesota Medical School, 2312 S. 6th St. Floor 2, Minneapolis, MN 55454, United States of America; Department of Nutritional Sciences, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI 48109, United States of America. Electronic address: hahn0203@umn.edu. 2. Department of Nutritional Sciences, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI 48109, United States of America. 3. Department of Biostatistics, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI 48109, United States of America. 4. Department of Health Policy and Management, University of California Los Angeles School of Public Health, 650 Charles Young Dr, Los Angeles, CA 90095, United States of America.
Abstract
OBJECTIVE: To identify patterns of technology-based weight-related self-monitoring (WRSM) and assess associations between identified patterns and eating disorder behaviors among first year university students. METHODS: First year university students (n = 647) completed a web-based survey to assess their use of technology-based WRSM and eating disorder behaviors. The cross-sectional data were analyzed using gender-stratified latent class analysis to identify patterns of WRSM, followed by logistic regression to calculate the predicted probability of eating disorder behaviors for each pattern of WRSM. RESULTS: Technology-based WRSM is common among first year university students, with patterns of WRSM differing by student gender. Further, unique patterns of WRSM were associated with differing probability of engaging in eating disorder behaviors. For example, compared to the 67.0% of females who did not use technology-based WRSM, females engaging in high amounts of technology-based WRSM (33.0%) were more likely to report fasting, skipping meals, excessively exercising, and using supplements. Among males, those who reported all forms of WRSM (9.5%) were more likely to report fasting, skipping meals, purging, and using supplements but those who only used exercise self-monitoring (11.9%) did not have increased likelihood of eating disorder behaviors. CONCLUSIONS: Using multiple forms of technology-based WRSM is associated with increased likelihood of engaging in eating disorder behaviors among both female and male, first year university students. Assessing technology-based WRSM may be a simple method to screen for elevated eating disorder risk among first year students.
OBJECTIVE: To identify patterns of technology-based weight-related self-monitoring (WRSM) and assess associations between identified patterns and eating disorder behaviors among first year university students. METHODS: First year university students (n = 647) completed a web-based survey to assess their use of technology-based WRSM and eating disorder behaviors. The cross-sectional data were analyzed using gender-stratified latent class analysis to identify patterns of WRSM, followed by logistic regression to calculate the predicted probability of eating disorder behaviors for each pattern of WRSM. RESULTS: Technology-based WRSM is common among first year university students, with patterns of WRSM differing by student gender. Further, unique patterns of WRSM were associated with differing probability of engaging in eating disorder behaviors. For example, compared to the 67.0% of females who did not use technology-based WRSM, females engaging in high amounts of technology-based WRSM (33.0%) were more likely to report fasting, skipping meals, excessively exercising, and using supplements. Among males, those who reported all forms of WRSM (9.5%) were more likely to report fasting, skipping meals, purging, and using supplements but those who only used exercise self-monitoring (11.9%) did not have increased likelihood of eating disorder behaviors. CONCLUSIONS: Using multiple forms of technology-based WRSM is associated with increased likelihood of engaging in eating disorder behaviors among both female and male, first year university students. Assessing technology-based WRSM may be a simple method to screen for elevated eating disorder risk among first year students.
Authors: Samantha L Hahn; Katherine W Bauer; Niko Kaciroti; Daniel Eisenberg; Sarah K Lipson; Kendrin R Sonneville Journal: Int J Eat Disord Date: 2021-01-05 Impact factor: 4.861
Authors: Jason M Nagata; Vivienne M Hazzard; Kyle T Ganson; Samantha L Hahn; Dianne Neumark-Sztainer; Marla E Eisenberg Journal: Int J Eat Disord Date: 2021-12-14 Impact factor: 5.791
Authors: Samantha L Hahn; Vivienne M Hazzard; Katie A Loth; Nicole Larson; Laura Klein; Dianne Neumark-Sztainer Journal: Prev Med Date: 2022-01-21 Impact factor: 4.018
Authors: Samantha L Hahn; Niko Kaciroti; Daniel Eisenberg; Heidi M Weeks; Katherine W Bauer; Kendrin R Sonneville Journal: J Acad Nutr Diet Date: 2021-08-20 Impact factor: 5.234