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Modeling all-cause mortality: Projections of the impact of smoking cessation based on the NHEFS

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Listed:
  • Russell, L.B.
  • Carson, J.L.
  • Taylor, W.C.
  • Milan, E.
  • Dey, A.
  • Jagannathan, R.

Abstract

Objectives. A model that relates clinical risk factors to subsequent mortality was used to simulate the impact of smoking cessation. Methods. Survivor functions derived from multivariate hazard regressions fitted to data from the first National Health and Nutrition Examination Survey (NHANES I) Epidemiologic Follow-up Study, a longitudinal survey of a representative sample of US adults, were used to project deaths from all causes. Results. Validation tests showed that the hazard regressions agreed with the risk relationships reported by others, that reported deaths for baseline risk factors closely matched observed mortality, and that the projections attributed deaths to the appropriate levels of important risk factors. Projections of the impact of smoking cessation showed that the number of cumulative deaths would be 15% lower after 5 years and 11% lower after 20 years. Conclusions. The model produced realistic projections of the effects of risk factor modification of subsequent mortality in adults. Comparison of the projections for smoking cessation with estimates of the risk attributable to smoking published by the Centers for Disease Control and Prevention suggests that cessation could capture most of the benefit possible from eliminating smoking.

Suggested Citation

  • Russell, L.B. & Carson, J.L. & Taylor, W.C. & Milan, E. & Dey, A. & Jagannathan, R., 1998. "Modeling all-cause mortality: Projections of the impact of smoking cessation based on the NHEFS," American Journal of Public Health, American Public Health Association, vol. 88(4), pages 630-636.
  • Handle: RePEc:aph:ajpbhl:1998:88:4:630-636_8
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    Cited by:

    1. Pamela M. McMahon & Alan M. Zaslavsky & Milton C. Weinstein & Karen M. Kuntz & Jane C. Weeks & G. Scott Gazelle, 2006. "Estimation of Mortality Rates for Disease Simulation Models Using Bayesian Evidence Synthesis," Medical Decision Making, , vol. 26(5), pages 497-511, September.
    2. Xufeng Qian & Louise Russell & Elmira Valiyeva & Jane Miller, 2005. "New Evidence on Medicare's Prospective Payment System: A Survival Analysis based on the NHANES I Epidemiologic Followup Study," Departmental Working Papers 200506, Rutgers University, Department of Economics.

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