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Community prevalence and dyad disease pattern of multimorbidity in China and India: a systematic review

BACKGROUND: Driven by the increasing life expectancy, China and India, the two most populous countries in the world are experiencing a rising burden of multimorbidity. This study aims to explore community prevalence and dyad patterns of multimorbidity in China and India. METHODS: We conducted a syst...

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Autores principales: Zhang, Xinyi, Padhi, Asutosh, Wei, Ting, Xiong, Shangzhi, Yu, Jie, Ye, Pengpeng, Tian, Wenijng, Sun, Hongru, Peiris, David, Praveen, Devarsetty, Tian, Maoyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9486196/
https://www.ncbi.nlm.nih.gov/pubmed/36113890
http://dx.doi.org/10.1136/bmjgh-2022-008880
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author Zhang, Xinyi
Padhi, Asutosh
Wei, Ting
Xiong, Shangzhi
Yu, Jie
Ye, Pengpeng
Tian, Wenijng
Sun, Hongru
Peiris, David
Praveen, Devarsetty
Tian, Maoyi
author_facet Zhang, Xinyi
Padhi, Asutosh
Wei, Ting
Xiong, Shangzhi
Yu, Jie
Ye, Pengpeng
Tian, Wenijng
Sun, Hongru
Peiris, David
Praveen, Devarsetty
Tian, Maoyi
author_sort Zhang, Xinyi
collection PubMed
description BACKGROUND: Driven by the increasing life expectancy, China and India, the two most populous countries in the world are experiencing a rising burden of multimorbidity. This study aims to explore community prevalence and dyad patterns of multimorbidity in China and India. METHODS: We conducted a systematic review of five English and Chinese electronic databases. Studies involving adults 18 years or older at a community level, which reported multimorbidity prevalence and/or patterns were included. A modified Newcastle-Ottawa Scale was used for quality assessment. Despite large heterogeneity among reported studies, a systematic synthesis of the results was conducted to report the findings. RESULTS: From 13 996 studies retrieved, 59 studies met the inclusion criteria (46 in China, 9 in India and 4 in both). The median prevalence of multimorbidity was 30.7% (IQR 17.1, 49.4), ranging from 1.5% to 90.5%. There was a large difference in multimorbidity prevalence between China and India, with median prevalence being 36.1% (IQR 19.6, 48.8) and 28.3% (IQR 8.9, 56.8), respectively. Among 27 studies that reported age-specific prevalence, 19 studies found multimorbidity prevalence increased with age, while 8 studies observed a paradoxical reduction in the oldest age group. Of the 34 studies that reported sex-specific prevalence, 86% (n=32) observed a higher prevalence in females. The most common multimorbidity patterns from 14 studies included hypertensive diseases combined with diabetes mellitus, arthropathies, heart diseases and metabolic disorders. All included studies were rated as fair or poor quality. CONCLUSION: Multimorbidity is highly prevalent in China and India with hypertensive diseases and other comorbidities being the most observed patterns. The overall quality of the studies was low and there was a lack of representative samples in most studies. Large epidemiology studies, using a common definition of multimorbidity and national representative samples, with sex disaggregation are needed in both countries. PROSPERO REGISTRATION NUMBER: CRD42020176774.
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spelling pubmed-94861962022-09-21 Community prevalence and dyad disease pattern of multimorbidity in China and India: a systematic review Zhang, Xinyi Padhi, Asutosh Wei, Ting Xiong, Shangzhi Yu, Jie Ye, Pengpeng Tian, Wenijng Sun, Hongru Peiris, David Praveen, Devarsetty Tian, Maoyi BMJ Glob Health Original Research BACKGROUND: Driven by the increasing life expectancy, China and India, the two most populous countries in the world are experiencing a rising burden of multimorbidity. This study aims to explore community prevalence and dyad patterns of multimorbidity in China and India. METHODS: We conducted a systematic review of five English and Chinese electronic databases. Studies involving adults 18 years or older at a community level, which reported multimorbidity prevalence and/or patterns were included. A modified Newcastle-Ottawa Scale was used for quality assessment. Despite large heterogeneity among reported studies, a systematic synthesis of the results was conducted to report the findings. RESULTS: From 13 996 studies retrieved, 59 studies met the inclusion criteria (46 in China, 9 in India and 4 in both). The median prevalence of multimorbidity was 30.7% (IQR 17.1, 49.4), ranging from 1.5% to 90.5%. There was a large difference in multimorbidity prevalence between China and India, with median prevalence being 36.1% (IQR 19.6, 48.8) and 28.3% (IQR 8.9, 56.8), respectively. Among 27 studies that reported age-specific prevalence, 19 studies found multimorbidity prevalence increased with age, while 8 studies observed a paradoxical reduction in the oldest age group. Of the 34 studies that reported sex-specific prevalence, 86% (n=32) observed a higher prevalence in females. The most common multimorbidity patterns from 14 studies included hypertensive diseases combined with diabetes mellitus, arthropathies, heart diseases and metabolic disorders. All included studies were rated as fair or poor quality. CONCLUSION: Multimorbidity is highly prevalent in China and India with hypertensive diseases and other comorbidities being the most observed patterns. The overall quality of the studies was low and there was a lack of representative samples in most studies. Large epidemiology studies, using a common definition of multimorbidity and national representative samples, with sex disaggregation are needed in both countries. PROSPERO REGISTRATION NUMBER: CRD42020176774. BMJ Publishing Group 2022-09-16 /pmc/articles/PMC9486196/ /pubmed/36113890 http://dx.doi.org/10.1136/bmjgh-2022-008880 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research
Zhang, Xinyi
Padhi, Asutosh
Wei, Ting
Xiong, Shangzhi
Yu, Jie
Ye, Pengpeng
Tian, Wenijng
Sun, Hongru
Peiris, David
Praveen, Devarsetty
Tian, Maoyi
Community prevalence and dyad disease pattern of multimorbidity in China and India: a systematic review
title Community prevalence and dyad disease pattern of multimorbidity in China and India: a systematic review
title_full Community prevalence and dyad disease pattern of multimorbidity in China and India: a systematic review
title_fullStr Community prevalence and dyad disease pattern of multimorbidity in China and India: a systematic review
title_full_unstemmed Community prevalence and dyad disease pattern of multimorbidity in China and India: a systematic review
title_short Community prevalence and dyad disease pattern of multimorbidity in China and India: a systematic review
title_sort community prevalence and dyad disease pattern of multimorbidity in china and india: a systematic review
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9486196/
https://www.ncbi.nlm.nih.gov/pubmed/36113890
http://dx.doi.org/10.1136/bmjgh-2022-008880
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