Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/116647
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Type: Journal article
Title: Patterns of multimorbid health conditions: a systematic review of analytical methods and comparison analysis
Author: Ng, S.
Tawiah, R.
Sawyer, M.
Scuffham, P.
Citation: International Journal of Epidemiology, 2018; 47(5):1687-1704
Publisher: Oxford University Press
Issue Date: 2018
ISSN: 0300-5771
1464-3685
Statement of
Responsibility: 
Shu Kay Ng, Richard Tawiah, Michael Sawyer and Paul Scuffham
Abstract: Background: The latest review of studies on multimorbidity patterns showed high heterogeneity in the methodology for identifying groups of multimorbid conditions. However, it is unclear how analytical methods used influence the identified multimorbidity patterns. Methods: We undertook a systematic review of analytical methods used to identify multimorbidity patterns in PubMed and EMBASE from their inception to January 2017. We conducted a comparison analysis to assess the effect the analytical methods had on the multimorbidity patterns identified, using the Australian National Health Survey (NHS) 2007-08 data. Results: We identified 13 194 studies and excluded 13 091 based on titles/abstracts. From the full-text reviews of the 103 remaining publications, we identified 41 studies that used five different analytical methods to identify multimorbid conditions in the studies. Thirty-seven studies (90%) adopted either the factor-analysis or hierarchical-clustering methods, but heterogeneity arises for the use of different proximity measures within each method to form clusters. Our comparison analysis showed the variation in identified groups of multimorbid conditions when applying the methods to the same NHS data. We extracted main similarities among the groupings obtained by the five methods: (i) cardiovascular and metabolic diseases, (ii) mental health problems and (iii) allergic diseases. Conclusion: We showed the extent of effects for heterogeneous analytical methods on identification of multimorbidity patterns. However, more work is needed to guide investigators for choosing the best analytical method to improve the validity and generalizability of findings. Investigators should also attempt to compare results obtained by various methods for a consensus grouping of multimorbid conditions.
Keywords: Multimorbidity pattern; analytical method; health condition; comparison analysis; health survey
Rights: © The Author(s) 2018; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association
RMID: 0030101919
DOI: 10.1093/ije/dyy134
Appears in Collections:Medicine publications

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