The Camden Schizophrenia Surveys

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Abstract
BACKGROUND Investigation of the geographical distribution of schizophrenia and its relationship to socio-demographic factors is useful for planning services. METHOD Individuals 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. RESULTS A 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. CONCLUSIONS Unemployment 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.