Verónica Cabanas-Sánchez1, David Martínez-Gómez2, Rocío Izquierdo-Gómez3, Víctor Segura-Jiménez4, José Castro-Piñero4, Oscar L Veiga5. 1. Department of Physical Education, Sport and Human Movement, Faculty of Teacher Training and Education, Autonomous University of Madrid, Madrid, Spain. Electronic address: veronica.cabanas84@gmail.com. 2. Department of Physical Education, Sport and Human Movement, Faculty of Teacher Training and Education, Autonomous University of Madrid, Madrid, Spain; IMDEA Food Institute, CEI UAM + CSIC, Madrid, Spain. 3. Research Center, Faculty of Education, Universidad Central de Chile, Santiago, Chile; Department of Physical Education, Faculty of Education Sciences, University of Cádiz, Puerto Real, Spain. 4. Department of Physical Education, Faculty of Education Sciences, University of Cádiz, Puerto Real, Spain. 5. Department of Physical Education, Sport and Human Movement, Faculty of Teacher Training and Education, Autonomous University of Madrid, Madrid, Spain.
Abstract
OBJECTIVES: To examine clustering of lifestyle behaviors in Spanish children and adolescents based on screen time, nonscreen sedentary time, moderate-to-vigorous physical activity, Mediterranean diet quality, and sleep time, and to analyze its association with health-related physical fitness. STUDY DESIGN: The sample consisted of 1197 children and adolescents (597 boys), aged 8-18 years, included in the baseline cohort of the UP&DOWN study. Moderate-to-vigorous physical activity was assessed by accelerometry. Screen time, nonscreen sedentary time, Mediterranean diet quality, and sleep time were self-reported by participants. Health-related physical fitness was measured following the Assessing Levels of Physical Activity battery for youth. A 2-stage cluster analysis was performed based on the 5 lifestyle behaviors. Associations of clusters with fatness and physical fitness were analyzed by 1-way ANCOVA. RESULTS: Five lifestyle clusters were identified: (1) active (n = 171), (2) sedentary nonscreen sedentary time-high diet quality (n = 250), (3) inactive-high sleep time (n = 249 [20.8%]), (4) sedentary nonscreen sedentary time-low diet quality (n = 273), and (5) sedentary screen time-low sleep time (n = 254). Cluster 1 was the healthiest profile in relation to health-related physical fitness in both boys and girls. In boys, cluster 3 had the worst fatness and fitness levels, whereas in girls the worst scores were found in clusters 4 and 5. CONCLUSIONS: Clustering of different lifestyle behaviors was identified and differences in health-related physical fitness were found among clusters, which suggests that special attention should be given to sedentary behaviors in girls and physical activity in boys when developing childhood health prevention strategies focusing on lifestyles patterns.
OBJECTIVES: To examine clustering of lifestyle behaviors in Spanish children and adolescents based on screen time, nonscreen sedentary time, moderate-to-vigorous physical activity, Mediterranean diet quality, and sleep time, and to analyze its association with health-related physical fitness. STUDY DESIGN: The sample consisted of 1197 children and adolescents (597 boys), aged 8-18 years, included in the baseline cohort of the UP&DOWN study. Moderate-to-vigorous physical activity was assessed by accelerometry. Screen time, nonscreen sedentary time, Mediterranean diet quality, and sleep time were self-reported by participants. Health-related physical fitness was measured following the Assessing Levels of Physical Activity battery for youth. A 2-stage cluster analysis was performed based on the 5 lifestyle behaviors. Associations of clusters with fatness and physical fitness were analyzed by 1-way ANCOVA. RESULTS: Five lifestyle clusters were identified: (1) active (n = 171), (2) sedentary nonscreen sedentary time-high diet quality (n = 250), (3) inactive-high sleep time (n = 249 [20.8%]), (4) sedentary nonscreen sedentary time-low diet quality (n = 273), and (5) sedentary screen time-low sleep time (n = 254). Cluster 1 was the healthiest profile in relation to health-related physical fitness in both boys and girls. In boys, cluster 3 had the worst fatness and fitness levels, whereas in girls the worst scores were found in clusters 4 and 5. CONCLUSIONS: Clustering of different lifestyle behaviors was identified and differences in health-related physical fitness were found among clusters, which suggests that special attention should be given to sedentary behaviors in girls and physical activity in boys when developing childhood health prevention strategies focusing on lifestyles patterns.
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