Lifestyle patterns and endocrine, metabolic, and immunological biomarkers in European adolescents: The HELENA study

Objective: To evaluate the association of lifestyle patterns related to physical activity (PA), sedentariness, and sleep with endocrine, metabolic, and immunological health biomarkers in European adolescents. Methods: The present cross-sectional study comprised 3528 adolescents (1845 girls) (12.5-17...

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Detalles Bibliográficos
Autores: Agostinis-Sobrinho, C., Gómez-Martínez, S., Nova, E., Hernandez, A., Labayen, I., Kafatos, A., Gottand, F., Molnár, D., Ferrari, M., Moreno, L.A., González-Gross, M., Michels, N., Ruperez, A., Ruiz, J.R., Marcos, A.
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2018
País:España
Institución:Universidad de Zaragoza
Repositorio:Zaguán. Repositorio Digital de la Universidad de Zaragoza
OAI Identifier:oai:zaguan.unizar.es:86196
Acceso en línea:http://zaguan.unizar.es/record/86196
Access Level:acceso abierto
Descripción
Sumario:Objective: To evaluate the association of lifestyle patterns related to physical activity (PA), sedentariness, and sleep with endocrine, metabolic, and immunological health biomarkers in European adolescents. Methods: The present cross-sectional study comprised 3528 adolescents (1845 girls) (12.5-17.5 years) enrolled in the Healthy Lifestyle in Europe by Nutrition in Adolescence Study. Cluster analysis was performed by including body composition, PA by accelerometry, self-reported sedentary behaviors, and sleep duration. We also measured endocrine, metabolic, and immunological biomarkers. Results: Three-cluster solutions were identified: (a) light-PA time, moderate-vigorous-PA time and sedentary time, (b) light-PA time, moderate-vigorous-PA time, sedentary time and sleep time, (c) light-PA time, moderate-vigorous-PA time, sedentary time and body composition. In addition, each cluster solution was defined as: “healthy, ” “medium healthy, ” and “unhealthy” according to the presented rating. Analysis of variance showed that overall the healthiest groups from the three clusters analyzed presented a better metabolic profile. A decision tree analysis showed that leptin had a strong association with cluster 3 in both boys and girls, high-density lipoprotein cholesterol had the strongest association with clusters 1 and 3 in boys. Cortisol had the strongest association with cluster 1. HOMA index (homeostatic model assessment) and C3 showed a strong association with cluster 3 in girls. Conclusions: Our results support the existence of different interactions between metabolic health and lifestyle patterns related to PA, sedentariness, and sleep, with some gender-specific findings. These results highlight the importance to consider multiple lifestyle-related health factors in the assessment of adolescents'' health to plan favorable strategies.