Please use this identifier to cite or link to this item:
Scopus Web of Science® Altmetric
Full metadata record
DC FieldValueLanguage
dc.contributor.authorGreen, M.-
dc.contributor.authorTzoumakis, S.-
dc.contributor.authorLaurens, K.-
dc.contributor.authorDean, K.-
dc.contributor.authorKariuki, M.-
dc.contributor.authorHarris, F.-
dc.contributor.authorO Reilly, N.-
dc.contributor.authorChilvers, M.-
dc.contributor.authorBrinkman, S.-
dc.contributor.authorCarr, V.-
dc.identifier.citationAustralian and New Zealand Journal of Psychiatry, 2018; 52(6):530-541-
dc.description.abstractObjective: Detecting the early emergence of childhood risk for adult mental disorders may lead to interventions for reducing subsequent burden of these disorders. We set out to determine classes of children who may be at risk for later mental disorder on the basis of early patterns of development in a population cohort, and associated exposures gleaned from linked administrative records obtained within the New South Wales Child Development Study. Methods: Intergenerational records from government departments of health, education, justice and child protection were linked with the Australian Early Development Census for a state population cohort of 67,353 children approximately 5 years of age. We used binary data from 16 subdomains of the Australian Early Development Census to determine classes of children with shared patterns of Australian Early Development Census–defined vulnerability using latent class analysis. Covariates, which included demographic features (sex, socioeconomic status) and exposure to child maltreatment, parental mental illness, parental criminal offending and perinatal adversities (i.e. birth complications, smoking during pregnancy, low birth weight), were examined hierarchically within latent class analysis models. Results: Four classes were identified, reflecting putative risk states for mental disorders: (1) disrespectful and aggressive/ hyperactive behaviour, labelled ‘misconduct risk’ (N = 4368; 6.5%); (2) ‘pervasive risk’ (N = 2668; 4.0%); (3) ‘mild generalised risk’ (N = 7822; 11.6%); and (4) ‘no risk’ (N = 52,495; 77.9%). The odds of membership in putative risk groups (relative to the no risk group) were greater among children from backgrounds of child maltreatment, parental history of mental illness, parental history of criminal offending, socioeconomic disadvantage and perinatal adversities, with distinguishable patterns of association for some covariates. Conclusion: Patterns of early childhood developmental vulnerabilities may provide useful indicators for particular mental disorder outcomes in later life, although their predictive utility in this respect remains to be established in longitudinal follow-up of the cohort.-
dc.description.statementofresponsibilityMelissa J Green, Stacy Tzoumakis, Kristin R Laurens, Kimberlie Dean, Maina Kariuki, Felicity Harris, Nicole O, Reilly, Marilyn Chilvers, Sally A Brinkman and Vaughan J Carr-
dc.publisherSAGE Publications-
dc.rights© The Royal Australian and New Zealand College of Psychiatrists 2017-
dc.subjectEarly childhood-
dc.subjectrecord linkage-
dc.subjectrisk profiles-
dc.subjectmental health-
dc.titleLatent profiles of early developmental vulnerabilities in a New South Wales child population at age 5 years-
dc.typeJournal article-
dc.identifier.orcidBrinkman, S. [0000-0001-7538-4844]-
Appears in Collections:Aurora harvest 8
Public Health publications

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.