Analyses of cohort mortality incorporating observed and unobserved risk factors

Interventions to prevent disease and increase life expectancy are most effectively developed from data on pathways to disease and death. Unfortunately, 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 coherent empirical picture of routes to death from a diversity of causes requires a data combining and modelling strategy that, of necessity, incorporates theory and prior-knowledge-based assumptions together with sensitivity analyses to assess the stability of conclusions. In this paper, a general data combining statistical strategy is presented and illustrated for smoking behavior and lung cancer mortality. Specifically, National Health Interview Survey data on smoking is combined with U.S. vital statistics data 1950 to 1987 to analyze the joint distribution of total and lung cancer mortality. Parameters were estimated for mortality, smoking cessation processes, and for individual risk heterogeneity for nine U.S. white male and female cohorts aged 30 to 70 in 1950 and followed until 1987.