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Multimorbidity and quality of life: a closer look
BACKGROUND: The presence of multiple chronic conditions is associated with lower health related quality of life (HRQOL). Disease severity also influences HRQOL. To analyse the effects of all possible combinations of single diseases along with their severity on HRQOL seems cumbersome. Grouping diseas...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2007
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2042974/ https://www.ncbi.nlm.nih.gov/pubmed/17683600 http://dx.doi.org/10.1186/1477-7525-5-52 |
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author | Fortin, Martin Dubois, Marie-France Hudon, Catherine Soubhi, Hassan Almirall, José |
author_facet | Fortin, Martin Dubois, Marie-France Hudon, Catherine Soubhi, Hassan Almirall, José |
author_sort | Fortin, Martin |
collection | PubMed |
description | BACKGROUND: The presence of multiple chronic conditions is associated with lower health related quality of life (HRQOL). Disease severity also influences HRQOL. To analyse the effects of all possible combinations of single diseases along with their severity on HRQOL seems cumbersome. Grouping diseases and their severity in specific organ domains may facilitate the study of the complex relationship between multiple chronic conditions and HRQOL. The goal of this study was to analyse impaired organ domains that affect the most HRQOL of patients with multiple chronic conditions in primary care and their possible interactions. METHODS: We analysed data from 238 patients recruited from the clientele of 21 family physicians. We classified all chronic conditions along with the measure of their severity into the 14 organ domains of the Cumulative Illness Rating Scale (CIRS). Patients also completed the 36-item Medical Outcomes Study questionnaire (SF-36). One-way analyses of variance were performed to study the relationship between the severity score for each CIRS domain and both physical component summary (PCS) and mental component summary (MCS) of HRQOL. Two-way analyses of variance were conducted to investigate the significance of possible organ domains interactions. Variables involved in significant bivariate relationships or interactions were candidates for inclusion in a multivariate model. Five additional variables were included in the multivariate model because of their possible confounding effect: perceived social support, age, education, perceived economic status and residual CIRS. RESULTS: Significant differences in the PCS (p < 0.01) were found in 12 of the 14 CIRS organ domains. A significant difference in MCS was found only in the Psychiatric domain. In the multivariate analysis for the PCS, the CIRS domains Musculoskeletal, Neurological, and Psychiatric, had an independent direct impact on PCS while the Upper gastrointestinal, Vascular, Cardiac and Respiratory domains were involved in interactions. A multivariate model was not necessary for the mental component. CONCLUSION: Vascular, Upper gastrointestinal and Musculoskeletal systems have strong negative effects on HRQOL. Among combinations of systems, the respiratory and cardiac combination is of particular concern because of a synergistic negative effect. This study paves the way for a future study with a bigger sample that could yield a model of wider generalizability. |
format | Text |
id | pubmed-2042974 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-20429742007-10-27 Multimorbidity and quality of life: a closer look Fortin, Martin Dubois, Marie-France Hudon, Catherine Soubhi, Hassan Almirall, José Health Qual Life Outcomes Research BACKGROUND: The presence of multiple chronic conditions is associated with lower health related quality of life (HRQOL). Disease severity also influences HRQOL. To analyse the effects of all possible combinations of single diseases along with their severity on HRQOL seems cumbersome. Grouping diseases and their severity in specific organ domains may facilitate the study of the complex relationship between multiple chronic conditions and HRQOL. The goal of this study was to analyse impaired organ domains that affect the most HRQOL of patients with multiple chronic conditions in primary care and their possible interactions. METHODS: We analysed data from 238 patients recruited from the clientele of 21 family physicians. We classified all chronic conditions along with the measure of their severity into the 14 organ domains of the Cumulative Illness Rating Scale (CIRS). Patients also completed the 36-item Medical Outcomes Study questionnaire (SF-36). One-way analyses of variance were performed to study the relationship between the severity score for each CIRS domain and both physical component summary (PCS) and mental component summary (MCS) of HRQOL. Two-way analyses of variance were conducted to investigate the significance of possible organ domains interactions. Variables involved in significant bivariate relationships or interactions were candidates for inclusion in a multivariate model. Five additional variables were included in the multivariate model because of their possible confounding effect: perceived social support, age, education, perceived economic status and residual CIRS. RESULTS: Significant differences in the PCS (p < 0.01) were found in 12 of the 14 CIRS organ domains. A significant difference in MCS was found only in the Psychiatric domain. In the multivariate analysis for the PCS, the CIRS domains Musculoskeletal, Neurological, and Psychiatric, had an independent direct impact on PCS while the Upper gastrointestinal, Vascular, Cardiac and Respiratory domains were involved in interactions. A multivariate model was not necessary for the mental component. CONCLUSION: Vascular, Upper gastrointestinal and Musculoskeletal systems have strong negative effects on HRQOL. Among combinations of systems, the respiratory and cardiac combination is of particular concern because of a synergistic negative effect. This study paves the way for a future study with a bigger sample that could yield a model of wider generalizability. BioMed Central 2007-08-06 /pmc/articles/PMC2042974/ /pubmed/17683600 http://dx.doi.org/10.1186/1477-7525-5-52 Text en Copyright © 2007 Fortin et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Fortin, Martin Dubois, Marie-France Hudon, Catherine Soubhi, Hassan Almirall, José Multimorbidity and quality of life: a closer look |
title | Multimorbidity and quality of life: a closer look |
title_full | Multimorbidity and quality of life: a closer look |
title_fullStr | Multimorbidity and quality of life: a closer look |
title_full_unstemmed | Multimorbidity and quality of life: a closer look |
title_short | Multimorbidity and quality of life: a closer look |
title_sort | multimorbidity and quality of life: a closer look |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2042974/ https://www.ncbi.nlm.nih.gov/pubmed/17683600 http://dx.doi.org/10.1186/1477-7525-5-52 |
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