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Multimorbidity and health-related quality of life (HRQoL) in a nationally representative population sample: implications of count versus cluster method for defining multimorbidity on HRQoL
Citation
Wang, L and Palmer, AJ and Cocker, F and Sanderson, K, Multimorbidity and health-related quality of life (HRQoL) in a nationally representative population sample: implications of count versus cluster method for defining multimorbidity on HRQoL, Health and Quality of Life Outcomes, 15, (1) Article 7. ISSN 1477-7525 (2017) [Refereed Article]
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Copyright Statement
Copyright 2017 The Authors. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/
DOI: doi:10.1186/s12955-016-0580-x
Abstract
Methods: Data were derived from the nationally representative 2007 Australian National Survey of Mental Health and Wellbeing (n = 8841). The HRQoL scores were measured using the Assessment of Quality of Life (AQoL-4D) instrument. The simple count (2+ & 3+ conditions) and hierarchical cluster methods were used to define/identify clusters of multimorbidity. Linear regression was used to assess the associations between HRQoL and multimorbidity as defined by the different methods.
Results: The assessment of multimorbidity, which was defined using the count method, resulting in the prevalence of 26% (MM2+) and 10.1% (MM3+). Statistically significant clusters identified through hierarchical cluster analysis included heart or circulatory conditions (CVD)/arthritis (cluster-1, 9%) and major depressive disorder (MDD)/anxiety (cluster-2, 4%). A sensitivity analysis suggested that the stability of the clusters resulted from hierarchical clustering. The sociodemographic profiles were similar between MM2+, MM3+ and cluster-1, but were different from cluster-2. HRQoL was negatively associated with MM2+ (β: -0.18, SE: -0.01, p < 0.001), MM3+ (β: -0.23, SE: -0.02, p < 0.001), cluster-1 (β: -0.10, SE: 0.01, p < 0.001) and cluster-2 (β: -0.36, SE: 0.01, p < 0.001).
Conclusions: Our findings confirm the existence of an inverse relationship between multimorbidity and HRQoL in the Australian population and indicate that the hierarchical clustering approach is validated when the outcome of interest is HRQoL from this head-to-head comparison. Moreover, a simple count fails to identify if there are specific conditions of interest that are driving poorer HRQoL. Researchers should exercise caution when selecting a definition of multimorbidity because it may significantly influence the study outcomes.
Item Details
Item Type: | Refereed Article |
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Keywords: | multimorbidity, definition, AQoL-4D, hierarchical cluster, health-related quality of life (HRQoL) |
Research Division: | Economics |
Research Group: | Applied economics |
Research Field: | Health economics |
Objective Division: | Health |
Objective Group: | Evaluation of health and support services |
Objective Field: | Evaluation of health and support services not elsewhere classified |
UTAS Author: | Wang, L (Ms Lilli Wang) |
UTAS Author: | Palmer, AJ (Professor Andrew Palmer) |
UTAS Author: | Sanderson, K (Associate Professor Kristy Sanderson) |
ID Code: | 114256 |
Year Published: | 2017 |
Web of Science® Times Cited: | 34 |
Deposited By: | Menzies Institute for Medical Research |
Deposited On: | 2017-02-09 |
Last Modified: | 2018-05-29 |
Downloads: | 118 View Download Statistics |
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