Clustering of Physical Activity, Sleep, Diet, and Screen-Based Device Use Associated with Self-Rated Health in Adolescents.

Background: Little is known about how the interplay among health-related behaviors impacts self-rated health (SRH). We examined the clustering of physical activity (PA), sleep, diet, and specific screen-based device use, and the associations between the emergent clusters and SRH among Brazilian adol...

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Detalles Bibliográficos
Publicado en:International Journal of Behavioral Medicine Vol. 29; no. 5; pp. 587 - 597
Autores principales: Knebel, Margarethe Thaisi Garro, Matias, Thiago Sousa, Lopes, Marcus Vinicius Veber, dos Santos, Priscila Cristina, da Silva Bandeira, Alexsandra, da Silva, Kelly Samara
Formato: research tables/charts Journal Article
Publicado: Springer Nature Oct2022
Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario:Background: Little is known about how the interplay among health-related behaviors impacts self-rated health (SRH). We examined the clustering of physical activity (PA), sleep, diet, and specific screen-based device use, and the associations between the emergent clusters and SRH among Brazilian adolescents. Method: The data used in this cross-sectional study were from the baseline of the Movimente Program. Self-reported data were analyzed. SRH was recorded as a 5-point scale (from poor to excellent). Daily duration of exposure to the computer, the television, the cell phone, and games; PA; sleep; and weekly consumption of fruits and vegetables and ultra-processed foods were included in a Two-Step cluster analysis. Multilevel ordered logistic regressions assessed the associations between the clusters and SRH. Results: The data of 750 students (girls: 52.8%, 13.1 ± 1.0 years) were analyzed. Good SRH was more prevalent (52.8%). Three clusters were identified: the Phubbers (50.53%; characterized by the longest cell phone use duration, shortest gaming and computer use, lowest PA levels, and low consumption of fruits and vegetables), the Gamers (22.80%; longest gaming and computer use duration, PA < sample average, highest intake of ultra-processed foods), and a Healthier cluster (26.67%; physically active, use of all screen-based devices < sample average, and healthier dietary patterns). For both Gamers (−0.85; 95% CI −1.24, −0.46) and Phubbers (−0.71; 95% CI −1.04, −0.38), it was found a decrease in the log-odds of being in a higher SRH category compared with the Healthier cluster. Conclusion: Specific clusters represent increased health-related risk. Assuming the interdependence of health-related behaviors is indispensable for accurately managing health promotion actions for distinguishable groups.