A new set of risk equations for predicting long term risk of all-cause mortality using cardiovascular risk factors

Mannan, Haider R., Stevenson, Christopher E., Peeters, Anna, and McNeil, John J. (2013) A new set of risk equations for predicting long term risk of all-cause mortality using cardiovascular risk factors. Preventive Medicine, 56 (1). pp. 41-45.

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Objectives: 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.

Item ID: 35531
Item Type: Article (Research - C1)
ISSN: 1096-0260
Keywords: all-cause mortality; predictive equation; detailed smoking measures; other modifiable risk factors; reduced equations
Funders: National Health and Medical Research Council (NHMRC), VicHealth
Projects and Grants: NHMRC grant no. 465130
Date Deposited: 16 Oct 2014 23:15
FoR Codes: 01 MATHEMATICAL SCIENCES > 0104 Statistics > 010402 Biostatistics @ 50%
11 MEDICAL AND HEALTH SCIENCES > 1117 Public Health and Health Services > 111706 Epidemiology @ 50%
SEO Codes: 92 HEALTH > 9204 Public Health (excl. Specific Population Health) > 920499 Public Health (excl. Specific Population Health) not elsewhere classified @ 100%
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