Association between Clustering of Lifestyle Behaviors and Health-Related Physical Fitness in Youth: The UP&DOWN Study.

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.

Socioeconomic indicators, obesity, and physical fitness in south Brazilian adolescents with Down syndrome.

Objectives: The aim was to examine the association of potential socioeconomic indicators with obesity and physical fitness components in south Brazilian adolescents with Down syndrome. Methods: This study comprised a total of 1249 (669 boys) adolescents with Down syndrome aged 10 to 20 with complete baseline data. Socioeconomic indicators were assessed by a proxy-report questionnaire. Body mass index and physical fitness were assessed using a PROES-BR health-related fitness test battery. Results: Socioeconomic status is not associated with body mass index in adolescents with Down syndrome. In addition, two of five physical fitness variables were associated with groups of family income and paternal education level in boys, while one of five physical fitness variables were associated with groups of paternal and maternal education level in girls. Conclusion: Our results suggest that socioeconomic indicators are associated with some components of physical fitness in Brazilian adolescents with Down syndrome. These associations depend on the socioeconomic status and physical fitness components in boys and girls.