  The approach of causality based on physical laws and systems is revisited.
The issue of "levels", the relevance to epidemiology and the definition of
effects are particularly developed. Moreover it is argued that this approach
that we call the stochastic system approach is particularly well fitted to
study lifecourse epidemiology. A hierarchy of factors is described that could
be modeled using a suitable multivariate stochastic process. To illustrate this
approach, a conceptual model for coronary heart disease mixing continuous and
discrete state-space processes is proposed.
