Literature DB >> 16002319

Estimating population prevalence of psychiatric conditions by small area with applications to analysing outcome and referral variations.

Peter Congdon1.   

Abstract

This paper considers the development of estimates of mental illness prevalence for small areas and applications in explaining psychiatric outcomes and in assessing service provision. Estimates of prevalence are based on a logistic regression analysis of two national studies that provides model based estimates of relative morbidity risk by demographic, socio-economic and ethnic group for major psychiatric conditions; household/marital and area status also figure in the regression. Relative risk estimates are used, along with suitably disaggregated census populations, to make prevalence estimates for 354 English local authorities (LAs). Two applications are considered: the first involves analysis of variations in schizophrenia referrals and suicide mortality over English LAs that takes account of prevalence differences, and the second involves assessing hospital referral and bed use in relation to prevalence (for ages 16-74) for a case study area, Waltham Forest in NE London.

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Year:  2005        PMID: 16002319     DOI: 10.1016/j.healthplace.2005.05.001

Source DB:  PubMed          Journal:  Health Place        ISSN: 1353-8292            Impact factor:   4.078


  3 in total

1.  Generating small-area prevalence of psychological distress and alcohol consumption: validation of a spatial microsimulation method.

Authors:  Mylène Riva; Dianna M Smith
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2011-05-31       Impact factor: 4.328

2.  Self-rated health: small area large area comparisons amongst older adults at the state, district and sub-district level in India.

Authors:  Siddhivinayak Hirve; Penelope Vounatsou; Sanjay Juvekar; Yulia Blomstedt; Stig Wall; Somnath Chatterji; Nawi Ng
Journal:  Health Place       Date:  2013-12-10       Impact factor: 4.078

3.  Estimating prevalence of overweight or obese children and adolescents in small geographic areas using publicly available data.

Authors:  Carlo Davila-Payan; Michael DeGuzman; Kevin Johnson; Nicoleta Serban; Julie Swann
Journal:  Prev Chronic Dis       Date:  2015-03-12       Impact factor: 2.830

  3 in total

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