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Abstract: Aims: To investigate pathways to ecstasy use disorders from pre-birth to early adulthood with particular attention to the relationship between early depressive and anxiety symptoms and later ecstasy use disorders. Design: Prospective, longitudinal, population-based study started in Brisbane, South East Queensland (Australia) in 1981. Participants were 2143 young adults, followed up from pre-birth to young adulthood. Measurements: Ecstasy use disorders were assessed with the composite international diagnostic interview (CIDI-Auto). Maternal socio-economic position and mental health status were assessed at baseline (antenatal visit); maternal substance use was measured at the 5-year follow-up, adolescents’ behaviour at the 5- and 14-year follow-up and tobacco and alcohol use were assessed at the 14-year follow-up. Findings: Eight syndrome scales of childhood behaviour were examined. After adjustment for important confounders, delinquent and aggressive behaviour in early adolescence remained significantly associated with ecstasy use disorders in early adulthood. The associations became statistically non-significant when adolescent tobacco and alcohol use were included in the model [OR=1.50 (95%CI=0.75, 3.01) for delinquency and OR=1.69 (95%CI=0.92, 3.12) for aggression]. Formal mediation tests were statistically significant (p =0.001 for delinquent behaviour and p =0.05 for aggressive behaviour). Conclusions: Our findings suggest a pathway from early deviant behaviour to ecstasy use disorders, possibly mediated through licit drug experimentation in early adolescence. [Copyright &y& Elsevier]

While static microsimulation models of the tax-transfer system are now available throughout the developed world, health microsimulation models are much rarer. This is, at least in part, due to the difficulties in creating adequate base micro-datasets upon which the microsimulation models can be constructed. In sharp contrast to tax-transfer modelling, no readily available microdata set typically contains all the health status, health service usage and socio-demographic information required for a sophisticated health microsimulation model. This paper describes three new techniques developed to overcome survey data limitations when constructing 'MediSim', a microsimulation model of the Australian Pharmaceutical Benefits Scheme. Comparable statistical matching and data imputation techniques may be of relevance to other modellers, as they attempt to overcome similar data deficiencies. The 2001 national health survey (NHS) was the main data source for MediSim. However, the NHS has a number of limitations for use in a microsimulation model. To compensate for this, we statistically matched the NHS with another national survey to create synthetic families and get a complete record for every individual within each family. Further, we used complementary datasets to impute short term health conditions and prescribed drug usage for both short- and long-term health conditions. The application of statistical matching methods and use of complementary data sets significantly improved the usefulness of the NHS as a base dataset for MediSim. [ABSTRACT FROM AUTHOR]