Cargando…

Alzheimer's disease: Estimating its prevalence rate in a French geographical unit using the National Alzheimer Data Bank and national health insurance information systems

BACKGROUND: Reliable epidemiological data on Alzheimer's disease are scarce. However, these are necessary to adapt healthcare policy in terms of prevention, care and social needs related to this condition. To estimate the prevalence rate in the Alpes-Maritimes on the French Riviera, with a popu...

Descripción completa

Detalles Bibliográficos
Autores principales: Bailly, Laurent, David, Renaud, Chevrier, Roland, Grebet, Jean, Moncada, Mario, Fuch, Alain, Sciortino, Vincent, Robert, Philippe, Pradier, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6502320/
https://www.ncbi.nlm.nih.gov/pubmed/31059547
http://dx.doi.org/10.1371/journal.pone.0216221
_version_ 1783416242035490816
author Bailly, Laurent
David, Renaud
Chevrier, Roland
Grebet, Jean
Moncada, Mario
Fuch, Alain
Sciortino, Vincent
Robert, Philippe
Pradier, Christian
author_facet Bailly, Laurent
David, Renaud
Chevrier, Roland
Grebet, Jean
Moncada, Mario
Fuch, Alain
Sciortino, Vincent
Robert, Philippe
Pradier, Christian
author_sort Bailly, Laurent
collection PubMed
description BACKGROUND: Reliable epidemiological data on Alzheimer's disease are scarce. However, these are necessary to adapt healthcare policy in terms of prevention, care and social needs related to this condition. To estimate the prevalence rate in the Alpes-Maritimes on the French Riviera, with a population of one million, we present a capture-recapture procedure applied to cases of Alzheimer’s disease, based on two epidemiological surveillance systems. METHODS: To estimate the total number of patients affected by Alzheimer's disease, a capture-recapture study included a cohort of patients with Alzheimer's disease or receiving medications only eligible for use for this condition, recorded by a specific health insurance information system (Health Insurance Cohort, HIC), and those registered in the French National Alzheimer’s Data Bank (“Banque Nationale Alzheimer”, BNA) in 2010 and 2011. We applied Bayesian estimation of the M(t) ecological model, taking into account age and gender as covariates, i.e. factors of inhomogeneous catchability. RESULTS: Overall, 5,562 patients with Alzheimer's disease were recorded, of whom only 856 were common to both information systems. Mean age and F/M sex ratio differed between BNA and HIC surveillance systems, 81 vs 84 years and 2.7 vs 3.2, respectively. A Bayesian estimation, with age and gender as covariates, yields an estimate of 15,060 cases of Alzheimer's disease [95%HPDI: 14,490–15,630] in the Alpes-Maritimes. The completeness of the HIC and BNA databases were respectively of 25.4% and 17.2%. The estimated prevalence rate among the population over 65 years old was 6.3% in 2010–2011. CONCLUSIONS: This study demonstrates that it is possible to determine the number of subjects affected by Alzheimer's disease in a geographical unit, using available data from two existing surveillance systems in France, i.e. 15,060 cases in the Alpes-Maritimes. This is the first stage of a population-based approach in view of adapting available resources to the population’s needs.
format Online
Article
Text
id pubmed-6502320
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-65023202019-05-23 Alzheimer's disease: Estimating its prevalence rate in a French geographical unit using the National Alzheimer Data Bank and national health insurance information systems Bailly, Laurent David, Renaud Chevrier, Roland Grebet, Jean Moncada, Mario Fuch, Alain Sciortino, Vincent Robert, Philippe Pradier, Christian PLoS One Research Article BACKGROUND: Reliable epidemiological data on Alzheimer's disease are scarce. However, these are necessary to adapt healthcare policy in terms of prevention, care and social needs related to this condition. To estimate the prevalence rate in the Alpes-Maritimes on the French Riviera, with a population of one million, we present a capture-recapture procedure applied to cases of Alzheimer’s disease, based on two epidemiological surveillance systems. METHODS: To estimate the total number of patients affected by Alzheimer's disease, a capture-recapture study included a cohort of patients with Alzheimer's disease or receiving medications only eligible for use for this condition, recorded by a specific health insurance information system (Health Insurance Cohort, HIC), and those registered in the French National Alzheimer’s Data Bank (“Banque Nationale Alzheimer”, BNA) in 2010 and 2011. We applied Bayesian estimation of the M(t) ecological model, taking into account age and gender as covariates, i.e. factors of inhomogeneous catchability. RESULTS: Overall, 5,562 patients with Alzheimer's disease were recorded, of whom only 856 were common to both information systems. Mean age and F/M sex ratio differed between BNA and HIC surveillance systems, 81 vs 84 years and 2.7 vs 3.2, respectively. A Bayesian estimation, with age and gender as covariates, yields an estimate of 15,060 cases of Alzheimer's disease [95%HPDI: 14,490–15,630] in the Alpes-Maritimes. The completeness of the HIC and BNA databases were respectively of 25.4% and 17.2%. The estimated prevalence rate among the population over 65 years old was 6.3% in 2010–2011. CONCLUSIONS: This study demonstrates that it is possible to determine the number of subjects affected by Alzheimer's disease in a geographical unit, using available data from two existing surveillance systems in France, i.e. 15,060 cases in the Alpes-Maritimes. This is the first stage of a population-based approach in view of adapting available resources to the population’s needs. Public Library of Science 2019-05-06 /pmc/articles/PMC6502320/ /pubmed/31059547 http://dx.doi.org/10.1371/journal.pone.0216221 Text en © 2019 Bailly et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Bailly, Laurent
David, Renaud
Chevrier, Roland
Grebet, Jean
Moncada, Mario
Fuch, Alain
Sciortino, Vincent
Robert, Philippe
Pradier, Christian
Alzheimer's disease: Estimating its prevalence rate in a French geographical unit using the National Alzheimer Data Bank and national health insurance information systems
title Alzheimer's disease: Estimating its prevalence rate in a French geographical unit using the National Alzheimer Data Bank and national health insurance information systems
title_full Alzheimer's disease: Estimating its prevalence rate in a French geographical unit using the National Alzheimer Data Bank and national health insurance information systems
title_fullStr Alzheimer's disease: Estimating its prevalence rate in a French geographical unit using the National Alzheimer Data Bank and national health insurance information systems
title_full_unstemmed Alzheimer's disease: Estimating its prevalence rate in a French geographical unit using the National Alzheimer Data Bank and national health insurance information systems
title_short Alzheimer's disease: Estimating its prevalence rate in a French geographical unit using the National Alzheimer Data Bank and national health insurance information systems
title_sort alzheimer's disease: estimating its prevalence rate in a french geographical unit using the national alzheimer data bank and national health insurance information systems
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6502320/
https://www.ncbi.nlm.nih.gov/pubmed/31059547
http://dx.doi.org/10.1371/journal.pone.0216221
work_keys_str_mv AT baillylaurent alzheimersdiseaseestimatingitsprevalencerateinafrenchgeographicalunitusingthenationalalzheimerdatabankandnationalhealthinsuranceinformationsystems
AT davidrenaud alzheimersdiseaseestimatingitsprevalencerateinafrenchgeographicalunitusingthenationalalzheimerdatabankandnationalhealthinsuranceinformationsystems
AT chevrierroland alzheimersdiseaseestimatingitsprevalencerateinafrenchgeographicalunitusingthenationalalzheimerdatabankandnationalhealthinsuranceinformationsystems
AT grebetjean alzheimersdiseaseestimatingitsprevalencerateinafrenchgeographicalunitusingthenationalalzheimerdatabankandnationalhealthinsuranceinformationsystems
AT moncadamario alzheimersdiseaseestimatingitsprevalencerateinafrenchgeographicalunitusingthenationalalzheimerdatabankandnationalhealthinsuranceinformationsystems
AT fuchalain alzheimersdiseaseestimatingitsprevalencerateinafrenchgeographicalunitusingthenationalalzheimerdatabankandnationalhealthinsuranceinformationsystems
AT sciortinovincent alzheimersdiseaseestimatingitsprevalencerateinafrenchgeographicalunitusingthenationalalzheimerdatabankandnationalhealthinsuranceinformationsystems
AT robertphilippe alzheimersdiseaseestimatingitsprevalencerateinafrenchgeographicalunitusingthenationalalzheimerdatabankandnationalhealthinsuranceinformationsystems
AT pradierchristian alzheimersdiseaseestimatingitsprevalencerateinafrenchgeographicalunitusingthenationalalzheimerdatabankandnationalhealthinsuranceinformationsystems