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Global Multimorbidity Patterns

A Cross-Sectional, Population-Based, Multi-Country Study

Bibliographic Data

ID23364424
AuthorsNoé Garín (0000-0002-1559-9453, Universitat Autonòma de Barcelona), Ai Koyanagi (0000-0002-9565-5004, Centro de Investigación Biomédica en Red de Salud Mental), Somnath Chatterji (0000-0002-3085-6550, World Health Organization), Stefanos Tyrovola (0000-0003-4797-7743, Centro de Investigación Biomédica en Red de Salud Mental), Stefanos Tyrovolas (0000-0003-1498-0997), Beatriz Olaya (0000-0003-2046-3929, Centro de Investigación Biomédica en Red de Salud Mental), Matilde Leonardi (0000-0003-0552-8923, Fondazione IRCCS Istituto Neurologico Carlo Besta), Elvira Lara (0000-0002-7424-2198, Centro de Investigación Biomédica en Red de Salud Mental), Seppo Koskinen (0000-0003-1572-1735, Finnish Institute for Health and Welfare), Beata Tobiasz-Adamczyk (0000-0001-6311-3983, Jagiellonian University), José Luis Ayuso-Mateos (0000-0002-7544-826X, Centro de Investigación Biomédica en Red de Salud Mental), Josep Maria Haro (0000-0002-3984-277X, Centro de Investigación Biomédica en Red de Salud Mental)
Year2016
Volume71
Issue2
Pages205-214
Publication date2016-02-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueThe Journals of Gerontology Series A: Biological Sciences and Medical Sciences (JOURNAL)
Journal identifiersISSN: 1079-5006 • E-ISSN: 1758-535X
PublisherOxford University Press (OUP) (PUBLISHER)
DOI10.1093/gerona/glv128
PMID26419978
OpenAlexW2266821176
LanguageEN
Citations received91
References cited34

BACKGROUND: Population ageing challenges health care systems due to the high prevalence and impact of multimorbidity in older adults. However, little is known about how chronic conditions present in certain multimorbidity patterns, which could have great impact on public health at several levels. The aim of our study was to identify and describe multimorbidity patterns in low-, middle-, and high-income countries. METHODS: We analyzed data from the Collaborative Research on Ageing in Europe project (Finland, Poland, and Spain) and the World Health Organization's Study on Global Ageing and Adult Health (China, Ghana, India, Mexico, Russia, and South Africa). These cross-sectional studies obtained data from 41,909 noninstitutionalized adults older than 50 years. Exploratory factor analysis was performed to detect multimorbidity patterns. Additional adjusted binary logistic regressions were performed to identify associations between sociodemographic factors and multimorbidity. RESULTS: Overall multimorbidity prevalence was high across countries. Hypertension, cataract, and arthritis were the most prevalent comorbid conditions. Two or three multimorbidity patterns were found per country. Several patterns were identified across several countries: "cardio-respiratory" (angina, asthma, and chronic obstructive pulmonary disease), "metabolic" (diabetes, obesity, and hypertension), and "mental-articular" (arthritis and depression). CONCLUSIONS: A high prevalence of multimorbidity occurs in older adults across countries, with low- and middle-income countries gradually approaching the figures of richer countries. Certain multimorbidity patterns are present in several countries, which suggest that common underlying etiopathogenic factors may play a role. Deeper understanding of these patterns may lead to the development of preventive actions to diminish their prevalence and also give rise to new, comprehensive approaches for the management of these co-occurring conditions.

Asthma · Comorbidity · Cross-sectional study · Environmental health · Multimorbidity · Obesity · Population · Population ageing · Public health · Chronic Disease Management Strategies · Demography · Healthcare Systems and Reforms · Medicine · Primary Care and Health Outcomes · Gerontology

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Unique citing works91
Citations per year10,11
Citation span2017 - 2026 (10)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 84

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