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

Authors
  • Agostinis‐Sobrinho, César
  • Gómez‐Martínez, Sonia
  • Nova, Esther
  • Hernandez, Aurora
  • Labayen, Idoia
  • Kafatos, Antonios
  • Gottand, Frederic
  • Molnár, Dénes
  • Ferrari, Marika
  • Moreno, Luis A
  • González‐Gross, Marcela
  • Michels, Nathalie
  • Ruperez, Azahara
  • Ruiz, Jonatan R
  • Marcos, Ascensión
Publication Date
Jan 01, 2019
Source
Ghent University Institutional Archive
Keywords
Language
English
License
Unknown
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Abstract

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.

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