title: Personalized Activity Intelligence (PAI) for Prevention of Cardiovascular Disease and Promotion of Physical Activity.
abstract: OBJECTIVE
  To derive and validate a single metric of activity tracking that associates with lower risk of cardiovascular disease mortality.
  
  
  METHODS
  We derived an algorithm, Personalized Activity Intelligence (PAI), using the HUNT Fitness Study (n = 4631), and validated it in the general HUNT population (n = 39,298) aged 20-74 years. The PAI was divided into three sex-specific groups (≤50, 51-99, and ≥100), and the inactive group (0 PAI) was used as the referent. Hazard ratios for all-cause and cardiovascular disease mortality were estimated using Cox proportional hazard regressions.
  
  
  RESULTS
  After >1 million person-years of observations during a mean follow-up time of 26.2 (SD 5.9) years, there were 10,062 deaths, including 3867 deaths (2207 men and 1660 women) from cardiovascular disease. Men and women with a PAI level ≥100 had 17% (95% confidence interval [CI], 7%-27%) and 23% (95% CI, 4%-38%) reduced risk of cardiovascular disease mortality, respectively, compared with the inactive groups. Obtaining ≥100 PAI was associated with significantly lower risk for cardiovascular disease mortality in all prespecified age groups, and in participants with known cardiovascular disease risk factors (all P-trends <.01). Participants who did not obtain ≥100 PAI had increased risk of dying regardless of meeting the physical activity recommendations.
  
  
  CONCLUSIONS
  PAI may have a huge potential to motivate people to become and stay physically active, as it is an easily understandable and scientifically proven metric that could inform potential users of how much physical activity is needed to reduce the risk of premature cardiovascular disease death.
authors.affiliation: K.G. Jebsen Center of Exercise in Medicine at the Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Faculty of Medicine, Trondheim, Norway.
authors.forename: Bjarne M
authors.initials: BM
authors.lastname: Nes
authors.affiliation: Technology Transfer Office, Norwegian University of Science and Technology, Trondheim, Norway.
authors.forename: Christian R
authors.initials: CR
authors.lastname: Gutvik
authors.affiliation: Department of Cardiovascular Diseases, John Ochsner Heart and Vascular Institute, Ochsner Clinical School-University of Queensland School of Medicine, New Orleans, La.
authors.forename: Carl J
authors.initials: CJ
authors.lastname: Lavie
authors.affiliation: K.G. Jebsen Center of Exercise in Medicine at the Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Faculty of Medicine, Trondheim, Norway. Electronic address: javaid.nauman@ntnu.no.
authors.forename: Javaid
authors.initials: J
authors.lastname: Nauman
authors.affiliation: K.G. Jebsen Center of Exercise in Medicine at the Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Faculty of Medicine, Trondheim, Norway; School of Human Movement & Nutrition Sciences, University of Queensland, St. Lucia, QLD, Australia.
authors.forename: Ulrik
authors.initials: U
authors.lastname: Wisløff
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000465:Algorithms; D002318:Cardiovascular Diseases / Q000401:mortality / Q000517:prevention & control*; D015444:Exercise; D005260:Female; D006293:Health Promotion / Q000379:methods*; D006801:Humans; D008297:Male; D008875:Middle Aged; D016016:Proportional Hazards Models; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D012737:Sex Factors; D055815:Young Adult
keywords: Activity tracking; Cardiovascular disease mortality; Physical activity; Prevention