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Assessing Psychiatric Morbidity from Community Registers: Methods for Bayesian Adjustment

Author

Listed:
  • Peter Congdon

    (Department of Geography, Queen Mary and Westfield College, London, E1 4NS, England, UK, p.congdon@qmw.ac.uk)

  • Alan Smith

    (Department of Psychology, Barking, Havering and Brentwood Community NHS Trust, Warley Hospital, Brentwood, Essex, England, UK,)

  • Christine Dean

    (Department of Psychiatroy, Brooklands Mental Health Centre, Wolverhampton, WV1 2ND, England, UK, CDChesters@aol.com)

Abstract

This paper considers Bayesian approaches to adjusting small area prevalence estimates derived from a community register of the seriously mentally ill, by taking account of underlying variability in latent prevalence between areas. Adjustment of individual prevalence rates to take account of the entire spatial distribution has implications both for epidemiological inference and resource rankings for localities. The more commonly adopted empirical Bayes approaches are here compared with fully Bayes approaches. Fully Bayes methods allow for uncertainty in the prevalence parameters and also permit the inclusion of information from other sources (for example, hospital admissions for mental illness) or from previous studies. The impact of socioeconomic indices on morbidity and its relevance for adjusted prevalence estimates is also considered. A case study is applied to an East London Health Authority, Barking and Havering.

Suggested Citation

  • Peter Congdon & Alan Smith & Christine Dean, 1998. "Assessing Psychiatric Morbidity from Community Registers: Methods for Bayesian Adjustment," Urban Studies, Urban Studies Journal Limited, vol. 35(12), pages 2323-2352, December.
    • Handle: RePEc:sae:urbstu:v:35:y:1998:i:12:p:2323-2352
    DOI: 10.1080/0042098983908
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    References listed on IDEAS

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    1. Roger J. Marshall, 1991. "A Review of Methods for the Statistical Analysis of Spatial Patterns of Disease," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 154(3), pages 421-441, May.
    2. Robert Haining, 1991. "Estimation With Heteroscedastic And Correlated Errors: A Spatial Analysis Of Intra‐Urban Mortality Data," Papers in Regional Science, Wiley Blackwell, vol. 70(3), pages 223-241, July.
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