Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Accelerometer-derived ‘weekend warrior’ physical activity pattern and brain health

Abstract

Extensive evidence shows the beneficial effect of adhering to a regular physical activity (PA) pattern on brain health. However, whether the ‘weekend warrior’ pattern, characterized by concentrated moderate-to-vigorous PA (MVPA) over 1–2 days, is associated with brain health is unclear. Here, we perform a prospective cohort study including 75,629 participants from the UK Biobank with validated accelerometry data. Individuals were classified into three PA patterns using current guideline thresholds: inactive (<150 min week−1 of MVPA), weekend warrior (≥150 min week−1 with ≥50% of total MVPA occurring within 1–2 days) and regularly active (≥150 min week−1 but not meeting weekend warrior criteria). We find that the weekend warrior pattern is associated with similarly lower risks of dementia, stroke, Parkinson’s disease, depressive disorders and anxiety compared to a regularly active pattern. Our findings highlight the weekend warrior pattern as a potential alternative in preventive intervention strategies, particularly for those unable to maintain daily activity routines.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: The cumulative risk of incident brain disorders stratified by activity pattern using an activity threshold of ≥150 min of MVPA per week (guideline-based).
Fig. 2: Association between PA pattern and incident brain disorders in models with different sets of covariates and the fully adjusted model.
Fig. 3: Association between PA pattern and incident brain disorders using different thresholds of total MVPA volume per week.
Fig. 4: Association between PA pattern and incident brain disorders stratified by age and sex.

Similar content being viewed by others

Data availability

The main data used in this study were accessed from the publicly available UK Biobank Resource (https://www.ukbiobank.ac.uk) under application no. 79095, which cannot be shared with other investigators because of data privacy laws. The UK Biobank data can be accessed by researchers on the application. Source data are provided with this paper.

Code availability

Scripts used to perform the analyses are available at https://github.com/Chen-jie-Xu/UKB_weekend_warrior_brain_health.git.

References

  1. 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).

    Article  PubMed  Google Scholar 

  2. 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).

    Article  PubMed  PubMed Central  Google Scholar 

  3. 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).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Ho, F. K. et al. Device-measured physical activity and incident affective disorders. BMC Med. 20, 290 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Bull, F. C. et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br. J. Sports Med. 54, 1451–1462 (2020).

    Article  PubMed  Google Scholar 

  6. 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).

  7. Optimizing Brain Health Across the Life Course: WHO Position Paper (WHO, 2022).

  8. 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).

    Article  PubMed  Google Scholar 

  9. 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).

    Article  PubMed  PubMed Central  Google Scholar 

  10. 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).

    Article  PubMed  PubMed Central  Google Scholar 

  11. 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).

    Article  PubMed  PubMed Central  Google Scholar 

  12. 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).

    Article  PubMed  Google Scholar 

  13. 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).

    Article  PubMed  PubMed Central  Google Scholar 

  14. 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).

    Article  PubMed  PubMed Central  Google Scholar 

  15. 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).

    Article  Google Scholar 

  16. Mee-Inta, O., Zhao, Z.-W. & Kuo, Y.-M. Physical exercise inhibits inflammation and microglial activation. Cells 8, 691 (2019).

  17. Zhang, Y.-R. et al. Personality traits and brain health: a large prospective cohort study. Nat. Mental Health 1, 722–735 (2023).

    Article  Google Scholar 

  18. 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).

    Article  CAS  PubMed  Google Scholar 

  19. 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).

    Article  PubMed  PubMed Central  Google Scholar 

  20. 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).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Boecker, H. et al. The runner’s high: opioidergic mechanisms in the human brain. Cereb. Cortex 18, 2523–2531 (2008).

    Article  PubMed  Google Scholar 

  22. 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).

    Article  PubMed  Google Scholar 

  23. 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).

    Article  CAS  PubMed  Google Scholar 

  24. 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).

    Google Scholar 

  25. 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).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Saint-Maurice, P. F. et al. Reproducibility of accelerometer and posture-derived measures of physical activity. Med. Sci. Sports Exerc. 52, 876–883 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. 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).

    Article  PubMed  Google Scholar 

  28. 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).

    Article  PubMed  PubMed Central  Google Scholar 

  29. 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).

    Article  PubMed  PubMed Central  Google Scholar 

  30. 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).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Doherty, A. et al. Large scale population assessment of physical activity using wrist worn accelerometers: the UK Biobank Study. PLoS ONE 12, e0169649 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  32. 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).

    Article  PubMed  Google Scholar 

  33. Bush, K. et al. THUR 121 Identifying participants with Parkinson’s disease in UK Biobank. J. Neurol. Neurosurg. Psychiatry 89, A13 (2018).

    Google Scholar 

  34. 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).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Rannikmäe, K. et al. Accuracy of identifying incident stroke cases from linked health care data in UK Biobank. Neurology 95, e697–e707 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Terracciano, A., Luchetti, M., Karakose, S., Stephan, Y. & Sutin, A. R. Loneliness and risk of Parkinson disease. JAMA Neurol. 80, 1138–1144 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Townsend, P., Phillimore, P. & Beattie, A. Health and Deprivation: Inequality and the North (Routledge, 1988).

  38. Mozaffarian, D. Dietary and policy priorities for cardiovascular disease, diabetes and obesity: a comprehensive review. Circulation 133, 187–225 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Morris, M. C. et al. MIND diet associated with reduced incidence of Alzheimer’s disease. Alzheimers Dement. 11, 1007–1014 (2015).

    Article  PubMed  Google Scholar 

  40. 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).

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

This study was conducted using the UK Biobank resource (application no. 79095). We want to express our sincere thanks to the participants of the UK Biobank and the members of the survey, development and management teams of this project. This work was supported by the National Natural Science Foundation of China (grant no. 72204071 to C.X. and no. 72342017 to Y.W.); Zhejiang Provincial Natural Science Foundation of China (grant no. LY23G030005 to C.X.); Major Science and Technology Project of Public Health in Tianjin (grant no. 21ZXGWSY00090 to Y.W.); and Scientific Research Foundation for Scholars of HZNU (grant no. 4265C50221204119 to C.X.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. The person icons in the left panel of Supplementary Fig. 1 were designed by Chagu from Iconfont (https://www.iconfont.cn). The icons for dementia and depressive disorder in Supplementary Fig. 1 were created by Ziyuejunkui and Lisefei from Iconfont. The PD icon in Supplementary Fig. 1 was designed by Freepik from Flaticon (https://www.flaticon.com). We sincerely thank the designers at Iconfont and Flaticon.

Author information

Authors and Affiliations

Authors

Contributions

J.M., Z.C., Y.W. and C.X. contributed to the conception, study design and ideas. J.M. and Z.C. collected, assembled the data and performed the statistical analysis. J.M., Z.C., T.D, Y.W. and C.X. conducted results interpretation. J.M. and Z.C. wrote the first and successive drafts of the manuscript. T.D, Y.W. and C.X. revised the manuscript for important intellectual content. C.X. and Y.W. obtained fundings. C.X. and Y.W. provided administrative, technical and logistic support. All authors reviewed the manuscript and approved the final version.

Corresponding authors

Correspondence to Yaogang Wang or Chenjie Xu.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Aging thanks Kaarin Anstey and Severine Sabia for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Tables

Supplementary Tables 1–15 and Figs. 1–4.

Reporting Summary

Source data

Source Data Fig. 2 Data

Used to plot Fig. 2.

Source Data Fig. 3 Data

Used to plot Fig. 3.

Source Data Fig. 4 Data

Used to plot Fig. 4.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Min, J., Cao, Z., Duan, T. et al. Accelerometer-derived ‘weekend warrior’ physical activity pattern and brain health. Nat Aging 4, 1394–1402 (2024). https://doi.org/10.1038/s43587-024-00688-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s43587-024-00688-y

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing