Gali Albalak1, Marjon Stijntjes2,3, Carolien A Wijsman4, P Eline Slagboom5,6, Frans J van der Ouderaa5, Simon P Mooijaart4, Diana van Heemst4, Raymond Noordam4. 1. Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands. g.albalak@lumc.nl. 2. Department of Rehabilitation Medicine, Leiden University Medical Center, Leiden, the Netherlands. 3. BioMechanical Engineering, Delft University of Technology, Delft, the Netherlands. 4. Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands. 5. Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands. 6. Max Planck Institute for Biology and Ageing, Cologne, Germany.
Abstract
BACKGROUND: Little is known about the impact of timing as opposed to frequency and intensity of daily physical activity on metabolic health. Therefore, we assessed the association between accelerometery-based daily timing of physical activity and measures of metabolic health in sedentary older people. METHODS: Hourly mean physical activity derived from wrist-worn accelerometers over a 6-day period was collected at baseline and after 3 months in sedentary participants from the Active and Healthy Ageing study. A principal component analysis (PCA) was performed to reduce the number of dimensions (e.g. define periods instead of separate hours) of hourly physical activity at baseline and change during follow-up. Cross-sectionally, a multivariable-adjusted linear regression analysis was used to associate the principal components, particularly correlated with increased physical activity in data-driven periods during the day, with body mass index (BMI), fasting glucose and insulin, HbA1c and the homeostatic model assessment for insulin resistance (HOMA-IR). For the longitudinal analyses, we calculated the hourly changes in physical activity and change in metabolic health after follow-up. RESULTS: We included 207 individuals (61.4% male, mean age: 64.8 [SD 2.9], mean BMI: 28.9 [4.7]). Higher physical activity in the early morning was associated with lower fasting glucose (-2.22%, 95% CI: -4.19, -0.40), fasting insulin (-13.54%, 95%CI: -23.49, -4.39), and HOMA-IR (-16.07%, 95%CI: -27.63, -5.65). Higher physical activity in the late afternoon to evening was associated with lower BMI (-2.84%, 95% CI: -4.92, -0.70). Higher physical activity at night was associated with higher BMI (2.86%, 95% CI: 0.90, 4.78), fasting glucose (2.57%, 95% CI: 0.70, 4.30), and HbA1c (2.37%, 95% CI: 1.00, 3.82). Similar results were present in the prospective analysis. CONCLUSION: Specific physical activity timing patterns were associated with more beneficial metabolic health, suggesting particular time-dependent physical activity interventions might maximise health benefits.
BACKGROUND: Little is known about the impact of timing as opposed to frequency and intensity of daily physical activity on metabolic health. Therefore, we assessed the association between accelerometery-based daily timing of physical activity and measures of metabolic health in sedentary older people. METHODS: Hourly mean physical activity derived from wrist-worn accelerometers over a 6-day period was collected at baseline and after 3 months in sedentary participants from the Active and Healthy Ageing study. A principal component analysis (PCA) was performed to reduce the number of dimensions (e.g. define periods instead of separate hours) of hourly physical activity at baseline and change during follow-up. Cross-sectionally, a multivariable-adjusted linear regression analysis was used to associate the principal components, particularly correlated with increased physical activity in data-driven periods during the day, with body mass index (BMI), fasting glucose and insulin, HbA1c and the homeostatic model assessment for insulin resistance (HOMA-IR). For the longitudinal analyses, we calculated the hourly changes in physical activity and change in metabolic health after follow-up. RESULTS: We included 207 individuals (61.4% male, mean age: 64.8 [SD 2.9], mean BMI: 28.9 [4.7]). Higher physical activity in the early morning was associated with lower fasting glucose (-2.22%, 95% CI: -4.19, -0.40), fasting insulin (-13.54%, 95%CI: -23.49, -4.39), and HOMA-IR (-16.07%, 95%CI: -27.63, -5.65). Higher physical activity in the late afternoon to evening was associated with lower BMI (-2.84%, 95% CI: -4.92, -0.70). Higher physical activity at night was associated with higher BMI (2.86%, 95% CI: 0.90, 4.78), fasting glucose (2.57%, 95% CI: 0.70, 4.30), and HbA1c (2.37%, 95% CI: 1.00, 3.82). Similar results were present in the prospective analysis. CONCLUSION: Specific physical activity timing patterns were associated with more beneficial metabolic health, suggesting particular time-dependent physical activity interventions might maximise health benefits.
Authors: A Di Blasio; F Di Donato; M Mastrodicasa; N Fabrizio; D Di Renzo; G Napolitano; V Petrella; S Gallina; P Ripari Journal: J Sports Med Phys Fitness Date: 2010-06 Impact factor: 1.637