The Camden Schizophrenia Surveys

Abstract

BackgroundInvestigation of the geographical distribution of schizophrenia and its relationship to socio-demographic factors is useful for planning services.MethodIndividuals with schizophrenia (n=980) were identified by key informants within an inner London borough and point prevalence calculated for broad, Feighner and DSM–III–R schizophrenia. The distribution of cases was tested for significant variation using the Poisson process model. Regression models using the Jarman-8 score and its component variables were tested for their ability to predict the prevalence of schizophrenia.ResultsA high point prevalence of schizophrenia (5.3 per 1000 resident population) was demonstrated. Case distribution showed a marked and significant variation associated with socio-demographic factors. The prediction of prevalence was more accurate for broad than for narrower definitions of schizophrenia; unemployment rate performed best.ConclusionsUnemployment rates and Jarman-8 scores may provide crude estimates for resource allocation in planning mental health services, highlighting the need for additional services in deprived inner city areas.