Department of Physical Education, Federal University of Viçosa, Viçosa, Minas Gerais, Brazil.
School of Applied Health Sciences and Wellness, Ohio University, Athens, Ohio, United States of America.
PLoS One. 2020 Jun 22;15(6):e0234374. doi: 10.1371/journal.pone.0234374. eCollection 2020.
Latent Class Analysis can assist researchers interested in a better understanding of behavioral patterns and their association with health outcomes. This study aimed to identify lifestyle latent classes related to distinct domains of physical activity (PA) and sedentary behavior (SB) among adolescents and their association with health outcomes. This cross-sectional study included 217 Brazilian adolescents (15 to 18 years old, 49.3% female). The classes were based on moderate-to-vigorous physical activity (MVPA), light physical activity (LPA), number of steps, sedentary behavior (SB), and screen time (ST). To assess these behaviors, participants wore an accelerometer for one week. ST, demographic characteristics, socioeconomic status, and signs of common mental disorders (CMD) were evaluated through questionnaires. Latent Class Analysis was used to identify lifestyle classes. Three classes were recognized: "Active-Non-sedentary" (class 1) with 28.1% of adolescents; "Inactive-Non-sedentary" (class 2), 48.85%; and "Inactive-Sedentary" (class 3), 23.04%. Sex and signs of CMD were associated with the prevalence of the classes. Female adolescents presented 4.48 (95% CI 2.04-9.77) times more chance of belonging to the "Inactive-Sedentary" (class 3). Adolescents who presented CMD had 11.35 (95% CI 3.45-101.1) times more chance of belonging to the "Inactive-Non-sedentary" (class 2). The interaction between sex and signs of CMD showed that girls with signs of CMD were 9.20 (95% CI 1.17-71.52) more likely to belong to the Inactive-Sedentary class than the "Active-Non-sedentary". Results indicate that sex and signs of CMD can affect the prevalence of the classes. Our findings highlight that physical inactivity and SB can be associated with signs of CMD, especially in female adolescents.
潜类分析可以帮助研究者更好地了解行为模式及其与健康结果的关系。本研究旨在确定与青少年身体活动(PA)和久坐行为(SB)不同领域相关的生活方式潜类,并研究它们与健康结果的关系。这项横断面研究纳入了 217 名巴西青少年(年龄 15 至 18 岁,女性占 49.3%)。这些类别是基于中等到剧烈的体力活动(MVPA)、轻度体力活动(LPA)、步数、久坐行为(SB)和屏幕时间(ST)来划分的。为了评估这些行为,参与者佩戴加速度计一周。通过问卷评估 ST、人口统计学特征、社会经济地位和常见精神障碍(CMD)的迹象。使用潜类分析来识别生活方式类别。识别出三个类别:“活跃-非久坐”(第 1 类)占 28.1%的青少年;“不活跃-非久坐”(第 2 类)占 48.85%;“不活跃-久坐”(第 3 类)占 23.04%。性别和 CMD 的迹象与类别的流行程度有关。女性青少年属于“不活跃-久坐”(第 3 类)的可能性是男性的 4.48 倍(95%CI 2.04-9.77)。患有 CMD 的青少年属于“不活跃-非久坐”(第 2 类)的可能性是不患有 CMD 的青少年的 11.35 倍(95%CI 3.45-101.1)。性别和 CMD 迹象之间的相互作用表明,患有 CMD 的女孩属于“不活跃-久坐”类别的可能性比“活跃-非久坐”类别的可能性高 9.20 倍(95%CI 1.17-71.52)。结果表明,性别和 CMD 的迹象可能会影响类别的流行程度。我们的研究结果表明,身体活动不足和 SB 可能与 CMD 的迹象有关,尤其是在女性青少年中。