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Spatial distribution of psychotic disorders in an urban area of France: an ecological study
Previous analyses of neighbourhood variations of non-affective psychotic disorders (NAPD) have focused mainly on incidence. However, prevalence studies provide important insights on factors associated with disease evolution as well as for healthcare resource allocation. This study aimed to investiga...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4870636/ https://www.ncbi.nlm.nih.gov/pubmed/27189529 http://dx.doi.org/10.1038/srep26190 |
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author | Pignon, Baptiste Schürhoff, Franck Baudin, Grégoire Ferchiou, Aziz Richard, Jean-Romain Saba, Ghassen Leboyer, Marion Kirkbride, James B. Szöke, Andrei |
author_facet | Pignon, Baptiste Schürhoff, Franck Baudin, Grégoire Ferchiou, Aziz Richard, Jean-Romain Saba, Ghassen Leboyer, Marion Kirkbride, James B. Szöke, Andrei |
author_sort | Pignon, Baptiste |
collection | PubMed |
description | Previous analyses of neighbourhood variations of non-affective psychotic disorders (NAPD) have focused mainly on incidence. However, prevalence studies provide important insights on factors associated with disease evolution as well as for healthcare resource allocation. This study aimed to investigate the distribution of prevalent NAPD cases in an urban area in France. The number of cases in each neighbourhood was modelled as a function of potential confounders and ecological variables, namely: migrant density, economic deprivation and social fragmentation. This was modelled using statistical models of increasing complexity: frequentist models (using Poisson and negative binomial regressions), and several Bayesian models. For each model, assumptions validity were checked and compared as to how this fitted to the data, in order to test for possible spatial variation in prevalence. Data showed significant overdispersion (invalidating the Poisson regression model) and residual autocorrelation (suggesting the need to use Bayesian models). The best Bayesian model was Leroux’s model (i.e. a model with both strong correlation between neighbouring areas and weaker correlation between areas further apart), with economic deprivation as an explanatory variable (OR = 1.13, 95% CI [1.02–1.25]). In comparison with frequentist methods, the Bayesian model showed a better fit. The number of cases showed non-random spatial distribution and was linked to economic deprivation. |
format | Online Article Text |
id | pubmed-4870636 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-48706362016-06-01 Spatial distribution of psychotic disorders in an urban area of France: an ecological study Pignon, Baptiste Schürhoff, Franck Baudin, Grégoire Ferchiou, Aziz Richard, Jean-Romain Saba, Ghassen Leboyer, Marion Kirkbride, James B. Szöke, Andrei Sci Rep Article Previous analyses of neighbourhood variations of non-affective psychotic disorders (NAPD) have focused mainly on incidence. However, prevalence studies provide important insights on factors associated with disease evolution as well as for healthcare resource allocation. This study aimed to investigate the distribution of prevalent NAPD cases in an urban area in France. The number of cases in each neighbourhood was modelled as a function of potential confounders and ecological variables, namely: migrant density, economic deprivation and social fragmentation. This was modelled using statistical models of increasing complexity: frequentist models (using Poisson and negative binomial regressions), and several Bayesian models. For each model, assumptions validity were checked and compared as to how this fitted to the data, in order to test for possible spatial variation in prevalence. Data showed significant overdispersion (invalidating the Poisson regression model) and residual autocorrelation (suggesting the need to use Bayesian models). The best Bayesian model was Leroux’s model (i.e. a model with both strong correlation between neighbouring areas and weaker correlation between areas further apart), with economic deprivation as an explanatory variable (OR = 1.13, 95% CI [1.02–1.25]). In comparison with frequentist methods, the Bayesian model showed a better fit. The number of cases showed non-random spatial distribution and was linked to economic deprivation. Nature Publishing Group 2016-05-18 /pmc/articles/PMC4870636/ /pubmed/27189529 http://dx.doi.org/10.1038/srep26190 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Pignon, Baptiste Schürhoff, Franck Baudin, Grégoire Ferchiou, Aziz Richard, Jean-Romain Saba, Ghassen Leboyer, Marion Kirkbride, James B. Szöke, Andrei Spatial distribution of psychotic disorders in an urban area of France: an ecological study |
title | Spatial distribution of psychotic disorders in an urban area of France: an ecological study |
title_full | Spatial distribution of psychotic disorders in an urban area of France: an ecological study |
title_fullStr | Spatial distribution of psychotic disorders in an urban area of France: an ecological study |
title_full_unstemmed | Spatial distribution of psychotic disorders in an urban area of France: an ecological study |
title_short | Spatial distribution of psychotic disorders in an urban area of France: an ecological study |
title_sort | spatial distribution of psychotic disorders in an urban area of france: an ecological study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4870636/ https://www.ncbi.nlm.nih.gov/pubmed/27189529 http://dx.doi.org/10.1038/srep26190 |
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