Kg. Manton et al., ANALYSES OF COHORT MORTALITY INCORPORATING OBSERVED AND UNOBSERVED RISK-FACTORS, Mathematical and computer modelling, 25(7), 1997, pp. 89-107
Interventions to prevent disease and increase life expectancy are most
effectively developed from data on pathways to disease and death. Unf
ortunately, most national data sets separate end-state information-i.e
., cause-specific mortality-from pathway data describing how specific
diseases result from environmental and behavioral processes. Thus, a c
oherent empirical picture of routes to death from a diversity of cause
s requires a data combining and modelling strategy that, of necessity,
incorporates theory and prior-knowledge-based assumptions together wi
th sensitivity analyses to assess the stability of conclusions. In thi
s paper, a general data combining statistical strategy is presented an
d illustrated for smoking behavior and lung cancer mortality. Specific
ally, National Health Interview Survey data on smoking is combined wit
h U.S. vital statistics data 1950 to 1987 to analyze the joint distrib
ution of total and lung cancer mortality Parameters were estimated for
mortality, smoking cessation processes, and for individual risk heter
ogeneity for nine U.S. white male and female cohorts aged 30 to 70 in
1950 and followed until 1981.