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Overcoming cut-off restrictions in multimorbidity prevalence estimates
BACKGROUND: Presently, there is no consensus on how to define multimorbidity. In this paper we investigate the connection between prevalence estimates for two or more and three or more chronic conditions to improve comparability of multimorbidity studies with different cut-offs. METHODS: In a system...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4133617/ https://www.ncbi.nlm.nih.gov/pubmed/25084825 http://dx.doi.org/10.1186/1471-2458-14-780 |
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author | Holzer, Barbara M Siebenhuener, Klarissa Bopp, Matthias Minder, Christoph E |
author_facet | Holzer, Barbara M Siebenhuener, Klarissa Bopp, Matthias Minder, Christoph E |
author_sort | Holzer, Barbara M |
collection | PubMed |
description | BACKGROUND: Presently, there is no consensus on how to define multimorbidity. In this paper we investigate the connection between prevalence estimates for two or more and three or more chronic conditions to improve comparability of multimorbidity studies with different cut-offs. METHODS: In a systematic review of the literature published between January, 1990 and December, 2011, we found 52 suitable studies, many providing prevalence estimates for several age groups. A total of 31 studies reported both the prevalence for multimorbidity based on two or more chronic conditions and three or more chronic conditions, which were analysed in this study. Our research question was whether there is a systematic interrelation between these two prevalence estimates, and how this could be used to improve the comparability of studies on the burden of multimorbidity. RESULTS: Actually, we found a tight relationship between the prevalence of two or more and three or more chronic conditions. Moreover, each of these estimates can be predicted from the other. I.e. the cut-offs of two or three for the number of chronic conditions produce essentially the same information on prevalence. CONCLUSIONS: Our study shows a way to enhance and improve the comparability of prevalence estimates from different multimorbidity studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2458-14-780) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4133617 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41336172014-08-16 Overcoming cut-off restrictions in multimorbidity prevalence estimates Holzer, Barbara M Siebenhuener, Klarissa Bopp, Matthias Minder, Christoph E BMC Public Health Research Article BACKGROUND: Presently, there is no consensus on how to define multimorbidity. In this paper we investigate the connection between prevalence estimates for two or more and three or more chronic conditions to improve comparability of multimorbidity studies with different cut-offs. METHODS: In a systematic review of the literature published between January, 1990 and December, 2011, we found 52 suitable studies, many providing prevalence estimates for several age groups. A total of 31 studies reported both the prevalence for multimorbidity based on two or more chronic conditions and three or more chronic conditions, which were analysed in this study. Our research question was whether there is a systematic interrelation between these two prevalence estimates, and how this could be used to improve the comparability of studies on the burden of multimorbidity. RESULTS: Actually, we found a tight relationship between the prevalence of two or more and three or more chronic conditions. Moreover, each of these estimates can be predicted from the other. I.e. the cut-offs of two or three for the number of chronic conditions produce essentially the same information on prevalence. CONCLUSIONS: Our study shows a way to enhance and improve the comparability of prevalence estimates from different multimorbidity studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2458-14-780) contains supplementary material, which is available to authorized users. BioMed Central 2014-08-01 /pmc/articles/PMC4133617/ /pubmed/25084825 http://dx.doi.org/10.1186/1471-2458-14-780 Text en © Holzer et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. 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 work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Holzer, Barbara M Siebenhuener, Klarissa Bopp, Matthias Minder, Christoph E Overcoming cut-off restrictions in multimorbidity prevalence estimates |
title | Overcoming cut-off restrictions in multimorbidity prevalence estimates |
title_full | Overcoming cut-off restrictions in multimorbidity prevalence estimates |
title_fullStr | Overcoming cut-off restrictions in multimorbidity prevalence estimates |
title_full_unstemmed | Overcoming cut-off restrictions in multimorbidity prevalence estimates |
title_short | Overcoming cut-off restrictions in multimorbidity prevalence estimates |
title_sort | overcoming cut-off restrictions in multimorbidity prevalence estimates |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4133617/ https://www.ncbi.nlm.nih.gov/pubmed/25084825 http://dx.doi.org/10.1186/1471-2458-14-780 |
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