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The disease burden of multimorbidity and its interaction with educational level

INTRODUCTION: Policies to adequately respond to the rise in multimorbidity have top-priority. To understand the actual burden of multimorbidity, this study aimed to: 1) estimate the trend in prevalence of multimorbidity in the Netherlands, 2) study the association between multimorbidity and physical...

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Autores principales: Chen, Yi Hsuan, Karimi, Milad, Rutten-van Mölken, Maureen P. M. H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7714131/
https://www.ncbi.nlm.nih.gov/pubmed/33270760
http://dx.doi.org/10.1371/journal.pone.0243275
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author Chen, Yi Hsuan
Karimi, Milad
Rutten-van Mölken, Maureen P. M. H.
author_facet Chen, Yi Hsuan
Karimi, Milad
Rutten-van Mölken, Maureen P. M. H.
author_sort Chen, Yi Hsuan
collection PubMed
description INTRODUCTION: Policies to adequately respond to the rise in multimorbidity have top-priority. To understand the actual burden of multimorbidity, this study aimed to: 1) estimate the trend in prevalence of multimorbidity in the Netherlands, 2) study the association between multimorbidity and physical and mental health outcomes and healthcare cost, and 3) investigate how the association between multimorbidity and health outcomes interacts with socio-economic status (SES). METHODS: Prevalence estimates were obtained from a nationally representative pharmacy database over 2007–2016. Impact on costs was estimated in a fixed effect regression model on claims data over 2009–2015. Data on physical and mental health and SES were obtained from the National Health Survey in 2017, in which the Katz-10 was used to measure limitations in activities of daily living (ADL) and the Mental Health Inventory (MHI) to measure mental health. SES was approximated by the level of education. Generalized linear models (2-part models for ADL) were used to analyze the health data. In all models an indicator variable for the presence or absence of multimorbidity was included or a categorical variable for the number of chronic conditions. Interactions terms of multimorbidity and educational level were added into the previously mentioned models. RESULTS: Over the past ten years, there was an increase of 1.6%-point in the percentage of people with multimorbidity. The percentage of people with three or more conditions increased with +2.1%-point. People with multimorbidity had considerably worse physical and mental health outcomes than people without multimorbidity. For the ADL, the impact of multimorbidity was three times greater in the lowest educational level than in the highest educational level. For the MHI, the impact of multimorbidity was two times greater in the lowest than in the highest educational level. Each additional chronic condition was associated with a greater worsening in health outcomes. Similarly, for costs, where there was no evidence of a diminishing impact of additional conditions either. In patients with multimorbidity total healthcare costs were on average €874 higher than in patients with a single morbidity. CONCLUSION: The impact of multimorbidity on health and costs seems to be greater in the sicker and lower educated population.
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spelling pubmed-77141312020-12-09 The disease burden of multimorbidity and its interaction with educational level Chen, Yi Hsuan Karimi, Milad Rutten-van Mölken, Maureen P. M. H. PLoS One Research Article INTRODUCTION: Policies to adequately respond to the rise in multimorbidity have top-priority. To understand the actual burden of multimorbidity, this study aimed to: 1) estimate the trend in prevalence of multimorbidity in the Netherlands, 2) study the association between multimorbidity and physical and mental health outcomes and healthcare cost, and 3) investigate how the association between multimorbidity and health outcomes interacts with socio-economic status (SES). METHODS: Prevalence estimates were obtained from a nationally representative pharmacy database over 2007–2016. Impact on costs was estimated in a fixed effect regression model on claims data over 2009–2015. Data on physical and mental health and SES were obtained from the National Health Survey in 2017, in which the Katz-10 was used to measure limitations in activities of daily living (ADL) and the Mental Health Inventory (MHI) to measure mental health. SES was approximated by the level of education. Generalized linear models (2-part models for ADL) were used to analyze the health data. In all models an indicator variable for the presence or absence of multimorbidity was included or a categorical variable for the number of chronic conditions. Interactions terms of multimorbidity and educational level were added into the previously mentioned models. RESULTS: Over the past ten years, there was an increase of 1.6%-point in the percentage of people with multimorbidity. The percentage of people with three or more conditions increased with +2.1%-point. People with multimorbidity had considerably worse physical and mental health outcomes than people without multimorbidity. For the ADL, the impact of multimorbidity was three times greater in the lowest educational level than in the highest educational level. For the MHI, the impact of multimorbidity was two times greater in the lowest than in the highest educational level. Each additional chronic condition was associated with a greater worsening in health outcomes. Similarly, for costs, where there was no evidence of a diminishing impact of additional conditions either. In patients with multimorbidity total healthcare costs were on average €874 higher than in patients with a single morbidity. CONCLUSION: The impact of multimorbidity on health and costs seems to be greater in the sicker and lower educated population. Public Library of Science 2020-12-03 /pmc/articles/PMC7714131/ /pubmed/33270760 http://dx.doi.org/10.1371/journal.pone.0243275 Text en © 2020 Chen 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
Chen, Yi Hsuan
Karimi, Milad
Rutten-van Mölken, Maureen P. M. H.
The disease burden of multimorbidity and its interaction with educational level
title The disease burden of multimorbidity and its interaction with educational level
title_full The disease burden of multimorbidity and its interaction with educational level
title_fullStr The disease burden of multimorbidity and its interaction with educational level
title_full_unstemmed The disease burden of multimorbidity and its interaction with educational level
title_short The disease burden of multimorbidity and its interaction with educational level
title_sort disease burden of multimorbidity and its interaction with educational level
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7714131/
https://www.ncbi.nlm.nih.gov/pubmed/33270760
http://dx.doi.org/10.1371/journal.pone.0243275
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