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Definitions and Prevalence of Multimorbidity in Large Database Studies: A Scoping Review
Background: Multimorbidity presents a key challenge to healthcare systems globally. However, heterogeneity in the definition of multimorbidity and design of epidemiological studies results in difficulty in comparing multimorbidity studies. This scoping review aimed to describe multimorbidity prevale...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7916224/ https://www.ncbi.nlm.nih.gov/pubmed/33572441 http://dx.doi.org/10.3390/ijerph18041673 |
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author | Chua, Ying Pin Xie, Ying Lee, Poay Sian Sabrina Lee, Eng Sing |
author_facet | Chua, Ying Pin Xie, Ying Lee, Poay Sian Sabrina Lee, Eng Sing |
author_sort | Chua, Ying Pin |
collection | PubMed |
description | Background: Multimorbidity presents a key challenge to healthcare systems globally. However, heterogeneity in the definition of multimorbidity and design of epidemiological studies results in difficulty in comparing multimorbidity studies. This scoping review aimed to describe multimorbidity prevalence in studies using large datasets and report the differences in multimorbidity definition and study design. Methods: We conducted a systematic search of MEDLINE, EMBASE, and CINAHL databases to identify large epidemiological studies on multimorbidity. We used the Preferred Reporting Items for Systematic Reviews and Meta-analysis Extension for Scoping Reviews (PRISMA-ScR) protocol for reporting the results. Results: Twenty articles were identified. We found two key definitions of multimorbidity: at least two (MM2+) or at least three (MM3+) chronic conditions. The prevalence of multimorbidity MM2+ ranged from 15.3% to 93.1%, and 11.8% to 89.7% in MM3+. The number of chronic conditions used by the articles ranged from 15 to 147, which were organized into 21 body system categories. There were seventeen cross-sectional studies and three retrospective cohort studies, and four diagnosis coding systems were used. Conclusions: We found a wide range in reported prevalence, definition, and conduct of multimorbidity studies. Obtaining consensus in these areas will facilitate better understanding of the magnitude and epidemiology of multimorbidity. |
format | Online Article Text |
id | pubmed-7916224 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-79162242021-03-01 Definitions and Prevalence of Multimorbidity in Large Database Studies: A Scoping Review Chua, Ying Pin Xie, Ying Lee, Poay Sian Sabrina Lee, Eng Sing Int J Environ Res Public Health Review Background: Multimorbidity presents a key challenge to healthcare systems globally. However, heterogeneity in the definition of multimorbidity and design of epidemiological studies results in difficulty in comparing multimorbidity studies. This scoping review aimed to describe multimorbidity prevalence in studies using large datasets and report the differences in multimorbidity definition and study design. Methods: We conducted a systematic search of MEDLINE, EMBASE, and CINAHL databases to identify large epidemiological studies on multimorbidity. We used the Preferred Reporting Items for Systematic Reviews and Meta-analysis Extension for Scoping Reviews (PRISMA-ScR) protocol for reporting the results. Results: Twenty articles were identified. We found two key definitions of multimorbidity: at least two (MM2+) or at least three (MM3+) chronic conditions. The prevalence of multimorbidity MM2+ ranged from 15.3% to 93.1%, and 11.8% to 89.7% in MM3+. The number of chronic conditions used by the articles ranged from 15 to 147, which were organized into 21 body system categories. There were seventeen cross-sectional studies and three retrospective cohort studies, and four diagnosis coding systems were used. Conclusions: We found a wide range in reported prevalence, definition, and conduct of multimorbidity studies. Obtaining consensus in these areas will facilitate better understanding of the magnitude and epidemiology of multimorbidity. MDPI 2021-02-09 2021-02 /pmc/articles/PMC7916224/ /pubmed/33572441 http://dx.doi.org/10.3390/ijerph18041673 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Chua, Ying Pin Xie, Ying Lee, Poay Sian Sabrina Lee, Eng Sing Definitions and Prevalence of Multimorbidity in Large Database Studies: A Scoping Review |
title | Definitions and Prevalence of Multimorbidity in Large Database Studies: A Scoping Review |
title_full | Definitions and Prevalence of Multimorbidity in Large Database Studies: A Scoping Review |
title_fullStr | Definitions and Prevalence of Multimorbidity in Large Database Studies: A Scoping Review |
title_full_unstemmed | Definitions and Prevalence of Multimorbidity in Large Database Studies: A Scoping Review |
title_short | Definitions and Prevalence of Multimorbidity in Large Database Studies: A Scoping Review |
title_sort | definitions and prevalence of multimorbidity in large database studies: a scoping review |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7916224/ https://www.ncbi.nlm.nih.gov/pubmed/33572441 http://dx.doi.org/10.3390/ijerph18041673 |
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