title: A new set of risk equations for predicting long term risk of all-cause mortality using cardiovascular risk factors.
abstract: OBJECTIVE
  As population ages and treatment for cardiovascular disease improves the risk of all-cause mortality has become a more meaningful outcome. We develop all-cause mortality equations for predicting long term risk using cardiovascular risk factors.
  
  
  METHODS
  The 24-year risk of all-cause mortality was evaluated using Cox model for participants aged 40-81 years at the 10th or 11th examination of the Framingham original cohort and the first examination of the offspring cohort-all of whom were free of major chronic diseases.
  
  
  RESULTS
  The predictors of all-cause mortality were age, sex, systolic blood pressure, total cholesterol/HDL ratio and smoking status. Risk prediction improved significantly when intensity of smoking and time since quitting were included into smoking status. A reduced model based on non-laboratory risk factors also demonstrated good predictive performance.
  
  
  CONCLUSIONS
  All-cause mortality risk equations incorporating cardiovascular risk factors provide an improved tool to quantify risk and guide prevention of mortality. There are great potentials for prevention of the CVD epidemic and for increased longevity with health, through improved life-styles and consequent lower levels of blood pressure, cholesterol and smoking.
authors.affiliation: Department of Epidemiology and Preventive Medicine, Alfred Centre, Monash University, Melbourne, Victoria 3004, Australia. haider.mannan@monash.edu
authors.forename: Haider R
authors.initials: HR
authors.lastname: Mannan
authors.forename: Christopher E
authors.initials: CE
authors.lastname: Stevenson
authors.forename: Anna
authors.initials: A
authors.lastname: Peeters
authors.forename: John J
authors.initials: JJ
authors.lastname: McNeil
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002318:Cardiovascular Diseases / Q000209:etiology*; D002423:Cause of Death / Q000639:trends*; D005260:Female; D006801:Humans; D008297:Male; D008404:Massachusetts / Q000453:epidemiology; D008875:Middle Aged; D015233:Models, Statistical; D016016:Proportional Hazards Models; D018570:Risk Assessment / Q000379:methods* / Q000706:statistics & numerical data; D012307:Risk Factors