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.
Department of Nutritional Sciences, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI 48109, United States of America.
Eat Behav. 2021 Aug;42:101520. doi: 10.1016/j.eatbeh.2021.101520. Epub 2021 May 8.
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.
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.
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.
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.
确定基于技术的体重相关自我监测（WRSM）模式，并评估在一年级大学生中发现的模式与饮食障碍行为之间的关联。
一年级大学生（n=647）完成了一项基于网络的调查，以评估他们对基于技术的 WRSM 和饮食障碍行为的使用情况。使用性别分层潜在类别分析对跨性别数据进行分析，以确定 WRSM 模式，然后使用逻辑回归计算每个 WRSM 模式下饮食障碍行为的预测概率。
基于技术的 WRSM 在一年级大学生中很常见，WRSM 模式因学生性别而异。此外，WRSM 的独特模式与不同的饮食障碍行为发生概率有关。例如，与不使用基于技术的 WRSM 的女性相比，女性中使用大量基于技术的 WRSM（33.0%）的更有可能报告禁食、不吃饭、过度运动和使用补充剂。在男性中，报告所有形式的 WRSM（9.5%）的人更有可能报告禁食、不吃饭、催吐和使用补充剂，但只报告运动自我监测（11.9%）的人则没有增加饮食障碍行为的可能性。
使用多种形式的基于技术的 WRSM 与女性和男性一年级大学生饮食障碍行为的发生概率增加有关。评估基于技术的 WRSM 可能是筛查一年级学生饮食障碍风险的一种简单方法。
