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Educational differentials in the prevalence (∆P) of any given condition can be simulated and decomposed as the outcome of differentials on incidence and mortality rates. The exact same methodology also decomposes the role of the chronic condition on the overall mortality (∆OM), but this analysis is not conducted in the literature. Chronic conditions, first cause of death in the US, are studied here using US elderly follow up data about mortality and diagnosed diseases, including Hypertension, Hearth attack, Diabetes, Lung disease, Cancer and Stroke. On each case, all individuals are assumed to experience a baseline mortality, while the presence of a chronic conditions is associated with an “excess mortality” rate; along this lines, ∆P and ∆OM are decomposed as the outcome of educational differences on baseline mortality, incidence and excess mortality. I found that for most chronic conditions a) educational differences on the base line mortality explain most of ∆OM but not much of ∆P , b) differences on incidence are more important than differences on excess mortality, but only with regard to ∆P, not to ∆OM; furthermore, in the case of Hypertension and Hearth attack, excess mortality rates explain most of the ∆OM associated the chronic condition. In the case of Cancer, the lower incidence and higher excess mortality of individuals in the low education group predicts a relatively lower prevalence of Cancer but also a relatively higher overall mortality in this group. In terms of policy, this idea highlights that the relative importance of differentials on incidence and mortality rates depends on the target of interest, prevalence or overall mortality

About the role of chronic conditions onto the US educational differences on mortality