Accelerometer-derived ‘weekend warrior’ physical activity pattern and brain health
Iso-Markku, P. et al. Physical activity as a protective factor for dementia and Alzheimer’s disease: systematic review, meta-analysis and quality assessment of cohort and case-control studies. Br. J. Sports Med. 56, 701–709 (2022).
Google Scholar
Hooker, S. P. et al. Association of accelerometer-measured sedentary time and physical activity with risk of stroke among US adults. JAMA Netw. Open 5, e2215385 (2022).
Google Scholar
Fang, X. et al. Association of levels of physical activity with risk of Parkinson disease: a systematic review and meta-analysis. JAMA Netw. Open 1, e182421 (2018).
Google Scholar
Ho, F. K. et al. Device-measured physical activity and incident affective disorders. BMC Med. 20, 290 (2022).
Google Scholar
Bull, F. C. et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br. J. Sports Med. 54, 1451–1462 (2020).
Google Scholar
Kunutsor, S. K., Jae, S. Y. & Laukkanen, J. A. ‘Weekend warrior’ and regularly active physical activity patterns confer similar cardiovascular and mortality benefits: a systematic meta-analysis. Eur. J. Prev. Cardiol. 30, e7–e10 (2023).
Optimizing Brain Health Across the Life Course: WHO Position Paper (WHO, 2022).
O’Donovan, G., Lee, I. M., Hamer, M. & Stamatakis, E. Association of ‘weekend warrior’ and other leisure time physical activity patterns with risks for all-cause, cardiovascular disease and cancer mortality. JAMA Intern. Med. 177, 335–342 (2017).
Google Scholar
Dos Santos, M. et al. Association of the ‘weekend warrior’ and other leisure-time physical activity patterns with all-cause and cause-specific mortality: a nationwide cohort study. JAMA Intern. Med. 182, 840–848 (2022).
Google Scholar
Hamer, M., Biddle, S. J. H. & Stamatakis, E. Weekend warrior physical activity pattern and common mental disorder: a population wide study of 108,011 British adults. Int. J. Behav. Nutr. Phys. Act. 14, 96 (2017).
Google Scholar
Khurshid, S., Al-Alusi, M. A., Churchill, T. W., Guseh, J. S. & Ellinor, P. T. Accelerometer-derived ‘weekend warrior’ physical activity and incident cardiovascular disease. JAMA 330, 247–252 (2023).
Google Scholar
Chen, R. et al. Weekend warrior physical activity pattern is associated with lower depression risk: findings from NHANES 2007–2018. Gen. Hosp. Psychiatry 84, 165–171 (2023).
Google Scholar
Shiroma, E. J., Lee, I. M., Schepps, M. A., Kamada, M. & Harris, T. B. Physical activity patterns and mortality: the weekend warrior and activity bouts. Med. Sci. Sports Exerc. 51, 35–40 (2019).
Google Scholar
Thompson, D., Batterham, A. M., Peacock, O. J., Western, M. J. & Booso, R. Feedback from physical activity monitors is not compatible with current recommendations: a recalibration study. Prev. Med. 91, 389–394 (2016).
Google Scholar
Öztürk, Ç. Ç. et al. Weekend warrior exercise model for protection from chronic mild stress‑induced depression and ongoing cognitive impairment. Acta Neurobiol. Exp. 83, 10–24 (2023).
Google Scholar
Mee-Inta, O., Zhao, Z.-W. & Kuo, Y.-M. Physical exercise inhibits inflammation and microglial activation. Cells 8, 691 (2019).
Zhang, Y.-R. et al. Personality traits and brain health: a large prospective cohort study. Nat. Mental Health 1, 722–735 (2023).
Google Scholar
Cotman, C. W., Berchtold, N. C. & Christie, L.-A. Exercise builds brain health: key roles of growth factor cascades and inflammation. Trends Neurosci. 30, 464–472 (2007).
Google Scholar
Paillard, T., Rolland, Y. & de Souto Barreto, P. Protective effects of physical exercise in Alzheimer’s disease and Parkinson’s disease: a narrative review. J. Clin. Neurol. 11, 212–219 (2015).
Google Scholar
De la Rosa, A. et al. Physical exercise in the prevention and treatment of Alzheimer’s disease. J. Sport Health Sci. 9, 394–404 (2020).
Google Scholar
Boecker, H. et al. The runner’s high: opioidergic mechanisms in the human brain. Cereb. Cortex 18, 2523–2531 (2008).
Google Scholar
Guthold, R., Stevens, G. A., Riley, L. M. & Bull, F. C. Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1.9 million participants. Lancet Glob. Health 6, e1077–e1086 (2018).
Google Scholar
Santos, A. C., Willumsen, J., Meheus, F., Ilbawi, A. & Bull, F. C. The cost of inaction on physical inactivity to public health-care systems: a population-attributable fraction analysis. Lancet Glob. Health 11, e32–e39 (2023).
Google Scholar
Fry, A., Littlejohns, T. J., Sudlow, C., Doherty, N. & Allen, N. E. OP41 The representativeness of the UK Biobank cohort on a range of sociodemographic, physical, lifestyle and health-related characteristics. J. Epidemiol. Commun. Health 70, A26 (2016).
Fry, A. et al. Comparison of sociodemographic and health-related characteristics of UK biobank participants with those of the general population. Am. J. Epidemiol. 186, 1026–1034 (2017).
Google Scholar
Saint-Maurice, P. F. et al. Reproducibility of accelerometer and posture-derived measures of physical activity. Med. Sci. Sports Exerc. 52, 876–883 (2020).
Google Scholar
Mielke, G. I. et al. Absolute intensity thresholds for tri-axial wrist and waist accelerometer-measured movement behaviors in adults. Scand. J. Med. Sci. Sports 33, 1752–1764 (2023).
Google Scholar
Tedesco, S. et al. Validity evaluation of the Fitbit Charge2 and the Garmin vivosmart HR+ in free-living rnvironments in an older adult cohort. JMIR Mhealth Uhealth 7, e13084 (2019).
Google Scholar
Welch, W. A. et al. Classification accuracy of the wrist-worn gravity estimator of normal everyday activity accelerometer. Med. Sci. Sports Exerc. 45, 2012–2019 (2013).
Google Scholar
Sudlow, C. et al. UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 12, e1001779 (2015).
Google Scholar
Doherty, A. et al. Large scale population assessment of physical activity using wrist worn accelerometers: the UK Biobank Study. PLoS ONE 12, e0169649 (2017).
Google Scholar
Walmsley, R. et al. Reallocation of time between device-measured movement behaviours and risk of incident cardiovascular disease. Br. J. Sports Med. 56, 1008–1017 (2021).
Google Scholar
Bush, K. et al. THUR 121 Identifying participants with Parkinson’s disease in UK Biobank. J. Neurol. Neurosurg. Psychiatry 89, A13 (2018).
Wilkinson, T. et al. Identifying dementia outcomes in UK Biobank: a validation study of primary care, hospital admissions and mortality data. Eur. J. Epidemiol. 34, 557–565 (2019).
Google Scholar
Rannikmäe, K. et al. Accuracy of identifying incident stroke cases from linked health care data in UK Biobank. Neurology 95, e697–e707 (2020).
Google Scholar
Terracciano, A., Luchetti, M., Karakose, S., Stephan, Y. & Sutin, A. R. Loneliness and risk of Parkinson disease. JAMA Neurol. 80, 1138–1144 (2023).
Google Scholar
Townsend, P., Phillimore, P. & Beattie, A. Health and Deprivation: Inequality and the North (Routledge, 1988).
Mozaffarian, D. Dietary and policy priorities for cardiovascular disease, diabetes and obesity: a comprehensive review. Circulation 133, 187–225 (2016).
Google Scholar
Morris, M. C. et al. MIND diet associated with reduced incidence of Alzheimer’s disease. Alzheimers Dement. 11, 1007–1014 (2015).
Google Scholar
Cao, Z. et al. Healthy sleep patterns and common mental disorders among individuals with cardiovascular disease: a prospective cohort study. J. Affect. Disord. 338, 487–494 (2023).
Google Scholar
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