Heterogeneity in schizophrenia; mixture modelling of age-at-first-admission, gender and diagnosis

Objective: Identifying and explaining sources of heterogeneity in schizophr enia would help elucidate its aetiology and course. In this paper we examin e heterogeneity in terms of age-at-first-admission, diagnosis and gender by decomposing a large dataset using mixture modelling. Method: Using the Queensland Mental Health Statistics System, we first extr acted age-at-first-admission data for schizophrenia (ICD8/9 295) to represe nt a 'narrow' definition of schizophrenia (N = 7651); we then added paraphr enia (297) and other non-organic psychoses (298) for a 'broad' definition ( N = 10 199). Mixture models were fitted to these narrowly and broadly defin ed distributions for both males and females. Results: For narrowly defined schizophrenia a three-component model best fi tted both male and female distributions. While the mean ages of these compo nents were very similar for both males and females, the ratios of males to females crossed from an excess of males in the 'youngest' component to an e xcess of females in the 'oldest' component. When using the broad definition , four components best fitted the underlying distributions. While the first three were similar to those found for narrowly defined schizophrenia, the additional fourth component reverted to a male excess; however, the mean ag e for males was 10 years younger than for females. Conclusion: Our findings suggest that subtypes based on age-at-first-admiss ion can be identified, although the number identified depends on how inclus ively schizophrenia is defined. While there appear to be the same number wi th similar mean ages for both genders, there are differences in the proport ions of males to females. Further work to fully characterize their nature i s warranted.