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Global Multimorbidity Patterns: A Cross-Sectional, Population-Based, Multi-Country Study
Open accessAbstract
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.
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Barnett, K., Mercer, S. W., Norbury, M., Watt, G., Wyke, S., & Guthrie, B. (2012) · The Lancet · doi:10.1016/s0140-6736(12)60240-2 · Cited by 6,972
Cited by
Asogwa, O. A., Boateng, D., Marzà-Florensa, A., Peters, S., Levitt, N., van Olmen, J., & Klipstein-Grobusch, K. (2022) · BMJ Open · doi:10.1136/bmjopen-2021-049133 · Cited by 221
Ali, M. K., Chwastiak, L., Poongothai, S., Emmert-Fees, K. M. F., Patel, S. A., Anjana, R. M., Sagar, R., Shankar, R., Sridhar, G. R., Kosuri, M., et al. (2020) · JAMA · doi:10.1001/jama.2020.11747 · Cited by 143
Stubbs, B., Vancampfort, D., Firth, J., Schuch, F. B., Hallgren, M., Smith, L., Gardner, B., Kahl, K. G., Veronese, N., Solmi, M., et al. (2018) · Journal of Affective Disorders · doi:10.1016/j.jad.2017.12.104 · Cited by 138
May, C. R., Cummings, A., Myall, M., Harvey, J., Pope, C., Griffiths, P., Roderick, P., Arber, M., Boehmer, K., Mair, F. S., et al. (2016) · BMJ Open · doi:10.1136/bmjopen-2016-011694 · Cited by 95
Irisin, an exercise-induced bioactive peptide beneficial for health promotion during aging process
Zhang, H., Wu, X., Liang, J., Kirberger, M., & Chen, N. (2022) · Ageing Research Reviews · doi:10.1016/j.arr.2022.101680 · Cited by 88
Metadata
- Authors
- Garin, N., Koyanagi, A., Chatterji, S., Tyrovolas, S., Olaya, B., Leonardi, M., Lara, E., Koskinen, S., Tobiasz-Adamczyk, B., Ayuso-Mateos, J. L., & Haro, J. M.
- Venue
- The Journals of Gerontology Series A: Biological Sciences and Medical Sciences
- Publisher
- Oxford University Press (OUP)
- Published
- 2015-09-29
- Volume
- 71
- Issue
- 2
- Pages
- 205-214
- ISSN
- 1079-5006 (ISSN-L)
- 1758-535X
- OpenAlex
- W2266821176
- Cited by
- 635
- References
- 1
- FWCI
- 21.33
- Type
- journal article
- Language
- en
- Open access
- bronze
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