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Rising burden of multimorbidity and related socio-demographic factors: a repeated cross-sectional study of Ontarians

OBJECTIVE: This study aimed to provide population-level data regarding trends in multimorbidity over 13 years. METHODS: We linked provincial health administrative data in Ontario, Canada, to create 3 cross-sectional panels of residents of any age in 2003, 2009, and 2016 to describe: (i) 13-year tren...

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Autores principales: Kone, Anna Pefoyo, Mondor, Luke, Maxwell, Colleen, Kabir, Umme Saika, Rosella, Laura C., Wodchis, Walter P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8043089/
https://www.ncbi.nlm.nih.gov/pubmed/33847995
http://dx.doi.org/10.17269/s41997-021-00474-y
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author Kone, Anna Pefoyo
Mondor, Luke
Maxwell, Colleen
Kabir, Umme Saika
Rosella, Laura C.
Wodchis, Walter P.
author_facet Kone, Anna Pefoyo
Mondor, Luke
Maxwell, Colleen
Kabir, Umme Saika
Rosella, Laura C.
Wodchis, Walter P.
author_sort Kone, Anna Pefoyo
collection PubMed
description OBJECTIVE: This study aimed to provide population-level data regarding trends in multimorbidity over 13 years. METHODS: We linked provincial health administrative data in Ontario, Canada, to create 3 cross-sectional panels of residents of any age in 2003, 2009, and 2016 to describe: (i) 13-year trends in multimorbidity prevalence and constellations among residents and across age, sex, and income; and (ii) chronic condition clusters. Multimorbidity was defined as having at least any 2 of 18 selected conditions, and further grouped into levels of 2, 3, 4, or 5 or more conditions. Age-sex standardized multimorbidity prevalence was estimated using the 2009 population as the standard. Clustering was defined using the observed combinations of conditions within levels of multimorbidity. RESULTS: Standardized prevalence of multimorbidity increased over time (26.5%, 28.8%, and 30.0% across sequential panels), across sex, age, and area-based income. Females, older adults and those living in lower income areas exhibited higher rates in all years. However, multimorbidity increased relatively more among males, younger adults, and those with 4 or 5 or more conditions. We observed numerous and increasing diversity in disease clusters, namely at higher levels of multimorbidity. CONCLUSION: Our study provides relevant and needed population-based information on the growing burden of multimorbidity, and related socio-demographic risk factors. Multimorbidity is markedly increasing among younger age cohorts. Also, there is an increasing complexity and lack of common clustering patterns at higher multimorbidity levels. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.17269/s41997-021-00474-y.
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spelling pubmed-80430892021-04-14 Rising burden of multimorbidity and related socio-demographic factors: a repeated cross-sectional study of Ontarians Kone, Anna Pefoyo Mondor, Luke Maxwell, Colleen Kabir, Umme Saika Rosella, Laura C. Wodchis, Walter P. Can J Public Health Quantitative Research OBJECTIVE: This study aimed to provide population-level data regarding trends in multimorbidity over 13 years. METHODS: We linked provincial health administrative data in Ontario, Canada, to create 3 cross-sectional panels of residents of any age in 2003, 2009, and 2016 to describe: (i) 13-year trends in multimorbidity prevalence and constellations among residents and across age, sex, and income; and (ii) chronic condition clusters. Multimorbidity was defined as having at least any 2 of 18 selected conditions, and further grouped into levels of 2, 3, 4, or 5 or more conditions. Age-sex standardized multimorbidity prevalence was estimated using the 2009 population as the standard. Clustering was defined using the observed combinations of conditions within levels of multimorbidity. RESULTS: Standardized prevalence of multimorbidity increased over time (26.5%, 28.8%, and 30.0% across sequential panels), across sex, age, and area-based income. Females, older adults and those living in lower income areas exhibited higher rates in all years. However, multimorbidity increased relatively more among males, younger adults, and those with 4 or 5 or more conditions. We observed numerous and increasing diversity in disease clusters, namely at higher levels of multimorbidity. CONCLUSION: Our study provides relevant and needed population-based information on the growing burden of multimorbidity, and related socio-demographic risk factors. Multimorbidity is markedly increasing among younger age cohorts. Also, there is an increasing complexity and lack of common clustering patterns at higher multimorbidity levels. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.17269/s41997-021-00474-y. Springer International Publishing 2021-04-13 /pmc/articles/PMC8043089/ /pubmed/33847995 http://dx.doi.org/10.17269/s41997-021-00474-y Text en © The Canadian Public Health Association 2021, corrected publication 2021
spellingShingle Quantitative Research
Kone, Anna Pefoyo
Mondor, Luke
Maxwell, Colleen
Kabir, Umme Saika
Rosella, Laura C.
Wodchis, Walter P.
Rising burden of multimorbidity and related socio-demographic factors: a repeated cross-sectional study of Ontarians
title Rising burden of multimorbidity and related socio-demographic factors: a repeated cross-sectional study of Ontarians
title_full Rising burden of multimorbidity and related socio-demographic factors: a repeated cross-sectional study of Ontarians
title_fullStr Rising burden of multimorbidity and related socio-demographic factors: a repeated cross-sectional study of Ontarians
title_full_unstemmed Rising burden of multimorbidity and related socio-demographic factors: a repeated cross-sectional study of Ontarians
title_short Rising burden of multimorbidity and related socio-demographic factors: a repeated cross-sectional study of Ontarians
title_sort rising burden of multimorbidity and related socio-demographic factors: a repeated cross-sectional study of ontarians
topic Quantitative Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8043089/
https://www.ncbi.nlm.nih.gov/pubmed/33847995
http://dx.doi.org/10.17269/s41997-021-00474-y
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