||Models of the Interaction of Mortality and the Evolution of Risk Factor Distribution: A General Stochastic Process Formulation (Journal Version).
Manton, K. G. ;
Woodbury, M. A. ;
Stallard, E. ;
||Duke Univ., Durham, NC.;Health Effects Research Lab., Research Triangle Park, NC.;National Science Foundation, Washington, DC.
Mathematical models ;
Risk assessment ;
||Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy.
Generally, analyses of longitudinal studies of chronic disease risks do not directly model the change with time of risk factor values and the interactions of those changes with risk levels. Failure to account for such process characteristics can lead to incorrect inferences about the specific effects of risk factors on mortality, the inability to accurately forecast the future risk of the cohort, and inaccurate statements about the effects of specific risk factor interventions on morality. A model is presented which does describe such a process model, and shows how it can be estimated from longitudinal studies. The effects of certain risk factor process features on the evolution of disease risk are illustrated, using data from males in the Framingham, Massachusetts study. (Copyright (c) John Wiley & Sons Ltd. 1988.)