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Editorial
Device-based measurement of physical activity in cardiovascular healthcare: possibilities and challenges
  1. Timothy James Chico1,2,
  2. Emmanuel Stamatakis3,
  3. Fabio Ciravegna4,
  4. Jessilyn Dunn5,
  5. Simon Redwood6,
  6. Rasha Al-lamee7,
  7. Reecha Sofat2,8,
  8. Jason Gill9
  1. 1 Infection, Immunity, and Cardiovascular Disease, University of Sheffield, Sheffield, UK
  2. 2 British Heart Foundation Data Science Centre, Health Data Research UK, London, UK
  3. 3 School of Health Sciences, University of Sydney, Sydney, New South Wales, Australia
  4. 4 Dipartimento di Informatica, Università di Torino, Torino, Italy
  5. 5 Department of Biomedical Engineering and Department of Biostatistics & Bioinformatics, Duke University, Durham, North Carolina, USA
  6. 6 St Thomas' Hospital, King’s College London, London, UK
  7. 7 National Heart and Lung Institute, Imperial College London, London, UK
  8. 8 Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
  9. 9 British Heart Foundation Glasgow Cardiovascular Research Centre (BHF GCRC), Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
  1. Correspondence to Professor Timothy James Chico, Infection, Immunity, and Cardiovascular Disease, University of Sheffield, Sheffield S10 2TN, UK; t.j.chico{at}sheffield.ac.uk

https://doi.org/10.1136/bjsports-2022-106460

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    Low physical activity increases the risk of cardiovascular disease (CVD).1 2 Conversely, once CVD develops, it can reduce the ability to be active. This suggests measurement of physical activity using wearables or smartphones may provide clinically useful ‘digital biomarkers’ for prediction, diagnosis and treatment selection in CVD. For any biomarker to be used in healthcare, its measurement must influence clinical decisions to improve outcomes. Here, we consider the possible benefits and barriers to using activity data in cardiovascular healthcare.

    Activity measurement to predict CVD risk

    Unlike unmodifiable CVD risk factors such as age, physical activity provides a non-pharmacological approach to reduce risk. Although physical activity may help control risk factors such as blood pressure and weight, existing risk prediction tools such as the QRISK3 (derived by the QResearch consortium) and Systematic COronary Risk Evaluation do not directly incorporate physical activity. Inclusion of self-reported activity levels can improve risk prediction. For instance, the American Diabetes Association 60 second risk score for type 2 diabetes includes binary self-reported activity. Evidence also suggests inclusion of self-reported walking pace improves prediction of CVD,3 and self-reported activity improves CVD risk classification.4 Thus, device-based measurement, which is more accurate and comprehensive than self-report, may further improve CVD prediction.

    Activity measurement to diagnose CVD

    Many (but not all) CVDs progressively reduce the ability to be physically active. Diagnosis of CVDs such as heart failure and valvular heart disease that impact activity relies on self-recognised and …

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    Footnotes

    • Twitter @timchico, @M_Stamatakis, @JasonGill74

    • Contributors TJC, ES and JG conceived the work, drafting and revising its content. FC, JD, SR, RA-I and RS made significant contributions to the manuscript, adding content, arguments, appropriate references and influencing the views expressed in the work. TJC submitted the manuscript, which all authors have approved. TJC agreed on behalf of all authors to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

    • Funding ES is funded by an Australian National Health and Medical Research Council (NHMRC) Leadership level 2 Investigator Grant (APP 1194510). TJC is funded by EPSRC project grant EP/X000257/1. His work is supported by the NIHR Sheffield Biomedical Research Centre (No award Number).

    • Disclaimer The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.

    • Competing interests SR has received fees to act as proctor and lecturer from Edwards and from Medtronic to sit on an International Advisory Board.

    • Provenance and peer review Not commissioned; externally peer reviewed.

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