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Article Dans Une Revue International Journal of Environmental Research and Public Health Année : 2019

Associations of Sensor-Derived Physical Behavior with Metabolic Health: A Compositional Analysis in the Record Multisensor Study

Résumé

Previous studies about the effects of physical activity and sedentary behaviors on health rarely recorded the exact body postures and movements, although they might be of metabolic relevance. Moreover, few studies treated the time budget of behaviors as compositions and little was done to characterize the distribution of durations of behavior sequences in relation with health. Data from the RECORD (Residential Environment and CORonary heart Disease) study of two combined VitaMove accelerometers worn at the trunk and upper leg for a week by 154 male and female adults (age = 50.6 ± 9.6 years, BMI = 25.8 ± 3.9 kg/m2) were analyzed. Using both iso-temporal substitution and compositional analysis, we examined associations between five physical behaviors (lying, sitting, standing, low physical activity, moderate-to-vigorous activity) and seven health outcomes (fasting serum glucose, low- and high-density lipoprotein, and triglycerides levels, body mass index, and waist circumference). After adjustment for confounding variables, total standing time was positively associated with better lipid profile, and lying during the day with adiposity. No significant association was observed between breaking up moderate-to-vigorous physical activity and health. This study highlights the importance of refined categories of postures in research on physical activity and health, as well as the necessity for new tools to characterize the distribution of behavior sequence durations, considering both bouts and micro-sequences. View Full-Text
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Dates et versions

hal-02095511 , version 1 (10-04-2019)

Identifiants

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Isaac Debache, Audrey Bergouignan, Basile Chaix, Emiel M Sneekes, Frédérique Thomas, et al.. Associations of Sensor-Derived Physical Behavior with Metabolic Health: A Compositional Analysis in the Record Multisensor Study. International Journal of Environmental Research and Public Health, 2019, 16 (5), pp.741. ⟨10.3390/ijerph16050741⟩. ⟨hal-02095511⟩
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