Behavioral classes related to physical activity and sedentary behavior on the evaluation of health and mental outcomes among Brazilian adolescents

• Published in: PloS one Vol. 15; no. 6; p. e0234374
• Main Authors: Faria, Fernanda Rocha de, Neves Miranda, Valter Paulo, Howe, Cheryl A, Sasaki, Jeffer Eidi, dos Santos Amorim, Paulo Roberto
• Format: Journal Article
• Language: English
• Published: San Francisco Public Library of Science 22.06.2020; Public Library of Science (PLoS)
• Subjects: Accelerometers; Adolescents; Behavior; Biology and Life Sciences; Blood pressure; Cardiovascular disease; Cluster analysis; Demographic aspects; Engineering and Technology; Evaluation; Exercise; Health aspects; Lifestyles; Medicine and Health Sciences; Mental disorders; People and Places; Physical activity; Physical education; Psychological aspects; Questionnaires; Risk factors; Secondary schools; Sedentary behavior; Sex; Sleep; Social Sciences; Socio-economic aspects; Socioeconomics; Studies; Teenagers; Youth; Brazil; United States > US; Ohio
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0234374

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.