Abstract
BackgroundNo universally accepted definition of multimorbidity (MM) exists, and implications of different definitions have not been explored. This study examined the performance of the count and cluster definitions of multimorbidity on the sociodemographic profile and health-related quality of life (HRQoL) in a general population.MethodsData 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.ResultsThe 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).ConclusionsOur 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.
Highlights
No universally accepted definition of multimorbidity (MM) exists, and implications of different definitions have not been explored
health-related quality of life (HRQoL) scores decrease with an increasing number of co-occurring chronic conditions [8], the full impact of multimorbidity on HRQoL is unlikely to be captured by the simple count method [9]
We analysed data from 8841 respondents which could be generalizable to 16,015,000 Australian adults
Summary
No universally accepted definition of multimorbidity (MM) exists, and implications of different definitions have not been explored. This study examined the performance of the count and cluster definitions of multimorbidity on the sociodemographic profile and health-related quality of life (HRQoL) in a general population. The presence of multiple chronic conditions, known as multimorbidity, is in the health care spotlight due to its increasing prevalence, complex management and large economic disease burden [1, 2]. The impact of multimorbidity on HRQoL has been investigated based on two general categories of multimorbidity: i) the number of chronic conditions (count definition) and ii) the cluster of chronic conditions (cluster definition) [6, 7]. HRQoL scores decrease with an increasing number of co-occurring chronic conditions [8], the full impact of multimorbidity on HRQoL is unlikely to be captured by the simple count method [9]. The impact of the different definitions of multimorbidity on HRQoL in a primary care setting is still unclear [8]
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