Psychiatric epidemiology has made significant contributions to the identification of risk factors for mental disorders. Available evidence underscores the complexity of the interactions between risk and disease and highlights conceptual and methodological challenges particularly in examining risk and disease relations beyond the level of simple associations. We propose that a life course approach in the study of risk factors for mental disorders, combined with fast developing analytical statistical tools, is the most promising avenue towards shifting the focus of the field from associations to generating and testing aetiological hypotheses. This review presents the basic tenants of life course risk modelling, highlighting key examples in the available literature that demonstrate the potential of this approach to advance our understanding of the trajectories from risk to disease and discusses priorities for future research.
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