Division of Adolescent and Young Adult Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, California, USA.
Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA.
Int J Eat Disord. 2022 Feb;55(2):207-214. doi: 10.1002/eat.23656. Epub 2021 Dec 14.
Digital technology use and muscle-building behaviors reflect a wide range of behaviors with associated health risks. However, links between digital technology use and muscle-building behaviors remain unknown and this study aimed to address this gap.
Data were collected from a diverse sample of 1,483 young adults (mean age 22.2 ± 2.0 years) participating in the population-based Eating and Activity over Time 2018 study. Gender-stratified-modified Poisson regression models were used to determine cross-sectional associations between three types of digital technology use (screen time, social media, weight-related self-monitoring apps) and five types of muscle-building behaviors (changing eating, exercise, protein powders/shakes, pre-workout drinks, steroids/growth hormone/creatine/amino acids) in young adulthood, adjusted for sociodemographic characteristics and body mass index.
Screen time and social media were either not found to be associated with muscle-building behaviors or in a few instances, associated with less use of these behaviors (e.g., screen time and pre-workout drinks in men). In contrast, the use of weight-related self-monitoring apps was positively associated with all muscle-building behaviors, including steroids/growth hormone/creatine/amino acids in men (prevalence ratio [PR] = 1.83; 95% confidence interval [CI]: 1.13-2.97) and women (PR = 4.43; 95% CI: 1.68-11.68).
While most recreational screen time may represent sedentary behaviors not related to muscle-building behaviors, weight-related self-monitoring apps are highly associated with more muscle-building behaviors and could be a future target for interventions to discourage the use of steroids and other harmful muscle-building substances.
数字技术的使用和肌肉锻炼行为反映了一系列与健康风险相关的行为。然而，数字技术的使用与肌肉锻炼行为之间的联系尚不清楚，本研究旨在填补这一空白。
数据来自参加基于人群的“饮食与活动随时间变化 2018 年研究”的 1483 名年轻成年人（平均年龄 22.2±2.0 岁）的多样化样本。使用性别分层修正泊松回归模型，确定三种数字技术使用（屏幕时间、社交媒体、体重相关自我监测应用程序）与五种肌肉锻炼行为（改变饮食、运动、蛋白粉/奶昔、锻炼前饮料、类固醇/生长激素/肌酸/氨基酸）之间的横断面关联，调整了社会人口统计学特征和体重指数。
屏幕时间和社交媒体要么与肌肉锻炼行为无关，要么在某些情况下与这些行为的使用减少有关（例如，男性的屏幕时间和锻炼前饮料）。相比之下，使用体重相关的自我监测应用程序与所有肌肉锻炼行为呈正相关，包括男性的类固醇/生长激素/肌酸/氨基酸（患病率比 [PR] = 1.83；95%置信区间 [CI]：1.13-2.97）和女性（PR = 4.43；95%CI：1.68-11.68）。
虽然大多数娱乐性屏幕时间可能代表与肌肉锻炼行为无关的久坐行为，但体重相关的自我监测应用程序与更多的肌肉锻炼行为高度相关，可能成为未来干预措施的目标，以阻止使用类固醇和其他有害的肌肉锻炼物质。
