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Prevalence of and factors associated with multimorbidity among 18 101 adults in the South East Asia Community Observatory Health and Demographic Surveillance System in Malaysia: a population-based, cross-sectional study of the MUTUAL consortium

OBJECTIVES: To assess the prevalence and factors associated with multimorbidity in a community-dwelling general adult population on a large Health and Demographic Surveillance System (HDSS) scale. DESIGN: Population-based cross-sectional study. SETTING: South East Asia Community Observatory HDSS sit...

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Autores principales: Tan, Michelle M C, Prina, A Matthew, Muniz-Terrera, Graciela, Mohan, Devi, Ismail, Roshidi, Assefa, Esubalew, Keinert, Ana Á M, Kassim, Zaid, Allotey, Pascale, Reidpath, Daniel, Su, Tin Tin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9791377/
https://www.ncbi.nlm.nih.gov/pubmed/36564121
http://dx.doi.org/10.1136/bmjopen-2022-068172
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author Tan, Michelle M C
Prina, A Matthew
Muniz-Terrera, Graciela
Mohan, Devi
Ismail, Roshidi
Assefa, Esubalew
Keinert, Ana Á M
Kassim, Zaid
Allotey, Pascale
Reidpath, Daniel
Su, Tin Tin
author_facet Tan, Michelle M C
Prina, A Matthew
Muniz-Terrera, Graciela
Mohan, Devi
Ismail, Roshidi
Assefa, Esubalew
Keinert, Ana Á M
Kassim, Zaid
Allotey, Pascale
Reidpath, Daniel
Su, Tin Tin
author_sort Tan, Michelle M C
collection PubMed
description OBJECTIVES: To assess the prevalence and factors associated with multimorbidity in a community-dwelling general adult population on a large Health and Demographic Surveillance System (HDSS) scale. DESIGN: Population-based cross-sectional study. SETTING: South East Asia Community Observatory HDSS site in Malaysia. PARTICIPANTS: Of 45 246 participants recruited from 13 431 households, 18 101 eligible adults aged 18–97 years (mean age 47 years, 55.6% female) were included. MAIN OUTCOME MEASURES: The main outcome was prevalence of multimorbidity. Multimorbidity was defined as the coexistence of two or more chronic conditions per individual. A total of 13 chronic diseases were selected and were further classified into 11 medical conditions to account for multimorbidity. The conditions were heart disease, stroke, diabetes mellitus, hypertension, chronic kidney disease, musculoskeletal disorder, obesity, asthma, vision problem, hearing problem and physical mobility problem. Risk factors for multimorbidity were also analysed. RESULTS: Of the study cohort, 28.5% people lived with multimorbidity. The individual prevalence of the chronic conditions ranged from 1.0% to 24.7%, with musculoskeletal disorder (24.7%), obesity (20.7%) and hypertension (18.4%) as the most prevalent chronic conditions. The number of chronic conditions increased linearly with age (p<0.001). In the logistic regression model, multimorbidity is associated with female sex (adjusted OR 1.28, 95% CI 1.17 to 1.40, p<0.001), education levels (primary education compared with no education: adjusted OR 0.63, 95% CI 0.53 to 0.74; secondary education: adjusted OR 0.60, 95% CI 0.51 to 0.70; tertiary education: adjusted OR 0.65, 95% CI 0.54 to 0.80; p<0.001) and employment status (working adults compared with retirees: adjusted OR 0.70, 95% CI 0.60 to 0.82, p<0.001), in addition to age (adjusted OR 1.05, 95% CI 1.05 to 1.05, p<0.001). CONCLUSIONS: The current single-disease services in primary and secondary care should be accompanied by strategies to address complexities associated with multimorbidity, taking into account the factors associated with multimorbidity identified. Future research is needed to identify the most commonly occurring clusters of chronic diseases and their risk factors to develop more efficient and effective multimorbidity prevention and treatment strategies.
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spelling pubmed-97913772022-12-27 Prevalence of and factors associated with multimorbidity among 18 101 adults in the South East Asia Community Observatory Health and Demographic Surveillance System in Malaysia: a population-based, cross-sectional study of the MUTUAL consortium Tan, Michelle M C Prina, A Matthew Muniz-Terrera, Graciela Mohan, Devi Ismail, Roshidi Assefa, Esubalew Keinert, Ana Á M Kassim, Zaid Allotey, Pascale Reidpath, Daniel Su, Tin Tin BMJ Open Epidemiology OBJECTIVES: To assess the prevalence and factors associated with multimorbidity in a community-dwelling general adult population on a large Health and Demographic Surveillance System (HDSS) scale. DESIGN: Population-based cross-sectional study. SETTING: South East Asia Community Observatory HDSS site in Malaysia. PARTICIPANTS: Of 45 246 participants recruited from 13 431 households, 18 101 eligible adults aged 18–97 years (mean age 47 years, 55.6% female) were included. MAIN OUTCOME MEASURES: The main outcome was prevalence of multimorbidity. Multimorbidity was defined as the coexistence of two or more chronic conditions per individual. A total of 13 chronic diseases were selected and were further classified into 11 medical conditions to account for multimorbidity. The conditions were heart disease, stroke, diabetes mellitus, hypertension, chronic kidney disease, musculoskeletal disorder, obesity, asthma, vision problem, hearing problem and physical mobility problem. Risk factors for multimorbidity were also analysed. RESULTS: Of the study cohort, 28.5% people lived with multimorbidity. The individual prevalence of the chronic conditions ranged from 1.0% to 24.7%, with musculoskeletal disorder (24.7%), obesity (20.7%) and hypertension (18.4%) as the most prevalent chronic conditions. The number of chronic conditions increased linearly with age (p<0.001). In the logistic regression model, multimorbidity is associated with female sex (adjusted OR 1.28, 95% CI 1.17 to 1.40, p<0.001), education levels (primary education compared with no education: adjusted OR 0.63, 95% CI 0.53 to 0.74; secondary education: adjusted OR 0.60, 95% CI 0.51 to 0.70; tertiary education: adjusted OR 0.65, 95% CI 0.54 to 0.80; p<0.001) and employment status (working adults compared with retirees: adjusted OR 0.70, 95% CI 0.60 to 0.82, p<0.001), in addition to age (adjusted OR 1.05, 95% CI 1.05 to 1.05, p<0.001). CONCLUSIONS: The current single-disease services in primary and secondary care should be accompanied by strategies to address complexities associated with multimorbidity, taking into account the factors associated with multimorbidity identified. Future research is needed to identify the most commonly occurring clusters of chronic diseases and their risk factors to develop more efficient and effective multimorbidity prevention and treatment strategies. BMJ Publishing Group 2022-12-23 /pmc/articles/PMC9791377/ /pubmed/36564121 http://dx.doi.org/10.1136/bmjopen-2022-068172 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
spellingShingle Epidemiology
Tan, Michelle M C
Prina, A Matthew
Muniz-Terrera, Graciela
Mohan, Devi
Ismail, Roshidi
Assefa, Esubalew
Keinert, Ana Á M
Kassim, Zaid
Allotey, Pascale
Reidpath, Daniel
Su, Tin Tin
Prevalence of and factors associated with multimorbidity among 18 101 adults in the South East Asia Community Observatory Health and Demographic Surveillance System in Malaysia: a population-based, cross-sectional study of the MUTUAL consortium
title Prevalence of and factors associated with multimorbidity among 18 101 adults in the South East Asia Community Observatory Health and Demographic Surveillance System in Malaysia: a population-based, cross-sectional study of the MUTUAL consortium
title_full Prevalence of and factors associated with multimorbidity among 18 101 adults in the South East Asia Community Observatory Health and Demographic Surveillance System in Malaysia: a population-based, cross-sectional study of the MUTUAL consortium
title_fullStr Prevalence of and factors associated with multimorbidity among 18 101 adults in the South East Asia Community Observatory Health and Demographic Surveillance System in Malaysia: a population-based, cross-sectional study of the MUTUAL consortium
title_full_unstemmed Prevalence of and factors associated with multimorbidity among 18 101 adults in the South East Asia Community Observatory Health and Demographic Surveillance System in Malaysia: a population-based, cross-sectional study of the MUTUAL consortium
title_short Prevalence of and factors associated with multimorbidity among 18 101 adults in the South East Asia Community Observatory Health and Demographic Surveillance System in Malaysia: a population-based, cross-sectional study of the MUTUAL consortium
title_sort prevalence of and factors associated with multimorbidity among 18 101 adults in the south east asia community observatory health and demographic surveillance system in malaysia: a population-based, cross-sectional study of the mutual consortium
topic Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9791377/
https://www.ncbi.nlm.nih.gov/pubmed/36564121
http://dx.doi.org/10.1136/bmjopen-2022-068172
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