César Agostinis-Sobrinho1, Sonia Gómez-Martínez2, Esther Nova2, Aurora Hernandez2, Idoia Labayen3, Antonios Kafatos4, Frederic Gottand5, Dénes Molnár6, Marika Ferrari7, Luis A Moreno8, Marcela González-Gross9, Nathalie Michels10, Azahara Ruperez8, Jonatan R Ruiz11, Ascensión Marcos2. 1. Faculty of Health Sciences, Klaipeda University, Klaipėda, Lithuania. 2. Department of Metabolism and Nutrition, Institute of Food Science and Technology and Nutrition (ICTAN), Spanish National Research Council (CSIC), Madrid, Spain. 3. Institute for Innovation & Sustainable Development in Food Chain (IS-FOOD), Public University of Navarra, Pamplona, Spain. 4. Faculty of Medicine, University of Crete, Crete, Greece. 5. Faculty of Medicine, University Lille, Lille, France. 6. Department of Pediatrics, Medical School, University of Pécs, Pecs, Hungary. 7. Council for Agricultural Research and Economics, Research Center for Food and Nutrition, Rome, Italy. 8. Growth, Exercise, Nutrition and Development Research Group, University of Zaragoza, Food and Agriculture Institute of Aragón (IA2), Health Research Institute of Aragón (ISS Aragón), Zaragoza, Spain. 9. ImFINE Research Group, Department of Health and Human Performance, Faculty of Physical Activity and Sport Sciences-INEF, Technical University of Madrid, Madrid, Spain. 10. Department of Public Health, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium. 11. PROFITH "PROmoting FITness and Health through physical activity" Research Group, Department of Physical Education and Sport, Faculty of Sport Sciences, University of Granada, Granada, Spain.
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.
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.
Authors: Andrea Wigna; Jacqueline B Urban; Wésley Torres; Lucas G Moraes-Chagas; Jefferson S Dias; David S Nunes; Veronica A de-Menezes; Rômulo A Fernandes Journal: Matern Child Health J Date: 2022-09-20
Authors: Li He; Xiaoyan Li; Weidong Wang; Youfa Wang; Haiyan Qu; Yang Zhao; Danhua Lin Journal: BMC Public Health Date: 2021-03-19 Impact factor: 3.295