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Definitions and Prevalence of Multimorbidity in Large Database Studies: A Scoping Review

Author

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  • Ying Pin Chua

    (Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 639798, Singapore)

  • Ying Xie

    (Clinical Research Unit, National Healthcare Group Polyclinics, Singapore 138543, Singapore)

  • Poay Sian Sabrina Lee

    (Clinical Research Unit, National Healthcare Group Polyclinics, Singapore 138543, Singapore)

  • Eng Sing Lee

    (Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 639798, Singapore
    Clinical Research Unit, National Healthcare Group Polyclinics, Singapore 138543, Singapore)

Abstract

Background: Multimorbidity presents a key challenge to healthcare systems globally. However, heterogeneity in the definition of multimorbidity and design of epidemiological studies results in difficulty in comparing multimorbidity studies. This scoping review aimed to describe multimorbidity prevalence in studies using large datasets and report the differences in multimorbidity definition and study design. Methods: We conducted a systematic search of MEDLINE, EMBASE, and CINAHL databases to identify large epidemiological studies on multimorbidity. We used the Preferred Reporting Items for Systematic Reviews and Meta-analysis Extension for Scoping Reviews (PRISMA-ScR) protocol for reporting the results. Results: Twenty articles were identified. We found two key definitions of multimorbidity: at least two (MM2+) or at least three (MM3+) chronic conditions. The prevalence of multimorbidity MM2+ ranged from 15.3% to 93.1%, and 11.8% to 89.7% in MM3+. The number of chronic conditions used by the articles ranged from 15 to 147, which were organized into 21 body system categories. There were seventeen cross-sectional studies and three retrospective cohort studies, and four diagnosis coding systems were used. Conclusions: We found a wide range in reported prevalence, definition, and conduct of multimorbidity studies. Obtaining consensus in these areas will facilitate better understanding of the magnitude and epidemiology of multimorbidity.

Suggested Citation

  • Ying Pin Chua & Ying Xie & Poay Sian Sabrina Lee & Eng Sing Lee, 2021. "Definitions and Prevalence of Multimorbidity in Large Database Studies: A Scoping Review," IJERPH, MDPI, vol. 18(4), pages 1-12, February.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:4:p:1673-:d:496619
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    References listed on IDEAS

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    1. Juan F Orueta & Arturo García-Álvarez & Manuel García-Goñi & Francesco Paolucci & Roberto Nuño-Solinís, 2014. "Prevalence and Costs of Multimorbidity by Deprivation Levels in the Basque Country: A Population Based Study Using Health Administrative Databases," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-11, February.
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    Cited by:

    1. Yiming Chen & Lei Shi & Xiao Zheng & Juan Yang & Yaqing Xue & Shujuan Xiao & Benli Xue & Jiachi Zhang & Xinru Li & Huang Lin & Chao Ma & Chichen Zhang, 2022. "Patterns and Determinants of Multimorbidity in Older Adults: Study in Health-Ecological Perspective," IJERPH, MDPI, vol. 19(24), pages 1-15, December.

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