BackgroundIdentifying the unique and shared premorbid indicators of risk for the schizophrenia spectrum disorders (SSD) and affective psychoses (AP) may refine aetiological hypotheses and inform the delivery of universal versus targeted preventive interventions. This systematic review synthesises the available evidence concerning developmental risk factors and antecedents of SSD and AP to identify those with the most robust support, and to highlight remaining evidence gaps.MethodsA systematic search of prospective birth, population, high-risk, and case-control cohorts was conducted in Medline and supplemented by hand searching, incorporating published studies in English with full text available. Inclusion/exclusion decisions and data extraction were completed in duplicate. Exposures included three categories of risk factors and four categories of antecedents, with case and comparison groups defined by adult psychiatric diagnosis. Effect sizes and prevalence rates were extracted, where available, and the strength of evidence synthesised and evaluated qualitatively across the study designs.ResultsOf 1775 studies identified by the search, 127 provided data to the review. Individuals who develop SSD experience a diversity of subtle premorbid developmental deficits and risk exposures, spanning the prenatal period through early adolescence. Those of greatest magnitude (or observed most consistently) included obstetric complications, maternal illness during pregnancy (especially infections), other maternal physical factors, negative family emotional environment, psychopathology and psychotic symptoms, and cognitive and motor dysfunctions. Relatively less evidence has accumulated to implicate this diversity of exposures in AP, and many yet remain unexamined, with the most consistent or strongest evidence to date being for obstetric complications, psychopathology, cognitive indicators and motor dysfunction. Among the few investigations affording direct comparison between SSD and AP, larger effect sizes and a greater number of significant associations are commonly reported for SSD relative to AP.ConclusionsShared risk factors for SSD and AP may include obstetric complications, childhood psychopathology, cognitive markers and motor dysfunction, but the capacity to distinguish common versus distinct risk factors/antecedents for SSD and AP is limited by the scant availability of prospective data for AP, and inconsistency in replication. Further studies considering both diagnoses concurrently are needed. Nonetheless, the prevalence of the risk factors/antecedents observed in cases and controls helps demarcate potential targets for preventative interventions for these disorders.Electronic supplementary materialThe online version of this article (doi:10.1186/s12888-015-0562-2) contains supplementary material, which is available to authorized users.

PurposeThe initial aim of this multiagency, multigenerational record linkage study is to identify childhood profiles of developmental vulnerability and resilience, and to identify the determinants of these profiles. The eventual aim is to identify risk and protective factors for later childhood-onset and adolescent-onset mental health problems, and other adverse social outcomes, using subsequent waves of record linkage. The research will assist in informing the development of public policy and intervention guidelines to help prevent or mitigate adverse long-term health and social outcomes.ParticipantsThe study comprises a population cohort of 87 026 children in the Australian State of New South Wales (NSW). The cohort was defined by entry into the first year of full-time schooling in NSW in 2009, at which time class teachers completed the Australian Early Development Census (AEDC) on each child (with 99.7% coverage in NSW). The AEDC data have been linked to the children's birth, health, school and child protection records for the period from birth to school entry, and to the health and criminal records of their parents, as well as mortality databases.Findings to dateDescriptive data summarising sex, geographic and socioeconomic distributions, and linkage rates for the various administrative databases are presented. Child data are summarised, and the mental health and criminal records data of the children's parents are provided.Future plansIn 2015, at age 11 years, a self-report mental health survey was administered to the cohort in collaboration with government, independent and Catholic primary school sectors. A second record linkage, spanning birth to age 11 years, will be undertaken to link this survey data with the aforementioned administrative databases. This will enable a further identification of putative risk and protective factors for adverse mental health and other outcomes in adolescence, which can then be tested in subsequent record linkages.

The choice of algorithm for extracting a psychosis diagnosis from administrative datasets may have a substantial impact on the accuracy of the diagnoses derived. An 'Any diagnosis' algorithm provides a sensitive measure for the presence of any psychosis, while 'Last diagnosis' is more accurate for specific diagnosis of schizophrenia and a hierarchical diagnosis is more accurate for affective psychosis.