Abstract
Understanding patterns and identifying common clusters of chronic diseases may help policymakers, researchers, and clinicians to understand the needs of the care process better and potentially save both provider and patient time and cost. However, only limited research has been conducted in this area, and ambiguity remains as those limited previous studies used different approaches to identify common clusters and findings may vary with approaches. This study estimates the prevalence of common chronic diseases and examines co-occurrence of diseases using four approaches: (i) identification of the most occurring pairs and triplets of comorbid diseases; performing (ii) cluster analysis of diseases, (iii) principal component analysis, and (iv) latent class analysis. Data were collected using a questionnaire mailed to a cross-sectional sample of senior Australians, with 4574 responses. Eighty-two percent of respondents reported having at least one chronic disease and over 52% reported having at least two chronic diseases. Respondents suffering from any chronic diseases had an average of 2.4 comorbid diseases. Three defined groups of chronic diseases were identified: (i) asthma, bronchitis, arthritis, osteoporosis and depression; (ii) high blood pressure and diabetes; and (iii) cancer, with heart disease and stroke either making a separate group or “attaching” themselves to different groups in different analyses. The groups were largely consistent across the approaches. Stability and sensitivity analyses also supported the consistency of the groups. The consistency of the findings suggests there is co-occurrence of diseases beyond chance, and patterns of co-occurrence are important for clinicians, patients, policymakers and researchers. Further studies are needed to provide a strong evidence base to identify comorbid groups which would benefit from appropriate guidelines for the care and management of patients with particular disease clusters.
Highlights
Multimorbid and comorbid chronic diseases are increasingly placing a greater burden on individuals, communities and health care services
This study aimed to identify the pattern of co-occurrence of common chronic diseases in senior Australians, and to explore whether and how the patterns identified differed if different analytic methods were used
This study focused on a sub-set of those conditions comprising the most common serious chronic diseases in Australia [21]: cancer, heart disease, high blood pressure (HBP), stroke, asthma/hayfever, bronchitis/emphysema, diabetes, arthritis, osteoporosis, Parkinson’s disease, depression
Summary
Multimorbid and comorbid chronic diseases are increasingly placing a greater burden on individuals, communities and health care services. It is increasingly recognised that diseases tend to occur together leading to a rising interest in the ‘common pathways’ implicated in the clustering of diseases and required responses to the potential to help better organise medical responses [1,2,3]. This co-occurrence of diseases has implications from a disease management point of view, as the features of comorbid diseases can be much more complicated than a simple aggregation of individual illnesses [4]. Using a single-morbidity model – where the impact of a single disease is explored – may mean one fails to grasp the pattern of disease, leading to inadequate clinical management, or to inadequate understanding of the disease effect by researchers and policymakers
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