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Reallocation of time between device-measured movement behaviours and risk of incident cardiovascular disease.

Rosemary WalmsleyShing ChanKarl Smith ByrneRema RamakrishnanMark WoodwardKazem RahimiTerence DwyerDerrick A BennettAiden Doherty
Published in: British journal of sports medicine (2021)
Machine-learning methods classified movement behaviours accurately in free-living accelerometer data. Reallocating time from other behaviours to MVPA, and from sedentary behaviour to other behaviours, was associated with lower risk of incident CVD, and should be promoted by interventions and guidelines.
Keyphrases
  • cardiovascular disease
  • physical activity
  • machine learning
  • type diabetes
  • artificial intelligence
  • cardiovascular events
  • clinical practice
  • data analysis