Abstract
BackgroundMultimorbidity is becoming more prevalent. Previously-used methods of assessing multimorbidity relied on counting the number of health conditions, often in relation to an index condition (comorbidity), or grouping conditions based on body or organ systems. Recent refinements in statistical approaches have resulted in improved methods to capture patterns of multimorbidity, allowing for the identification of nonrandomly occurring clusters of multimorbid health conditions. This paper aims to identify nonrandom clusters of multimorbidity.MethodsThe Australian Work Outcomes Research Cost-benefit (WORC) study cross-sectional screening dataset (approximately 78,000 working Australians) was used to explore patterns of multimorbidity. Exploratory factor analysis was used to identify nonrandomly occurring clusters of multimorbid health conditions.ResultsSix clinically-meaningful groups of multimorbid health conditions were identified. These were: factor 1: arthritis, osteoporosis, other chronic pain, bladder problems, and irritable bowel; factor 2: asthma, chronic obstructive pulmonary disease, and allergies; factor 3: back/neck pain, migraine, other chronic pain, and arthritis; factor 4: high blood pressure, high cholesterol, obesity, diabetes, and fatigue; factor 5: cardiovascular disease, diabetes, fatigue, high blood pressure, high cholesterol, and arthritis; and factor 6: irritable bowel, ulcer, heartburn, and other chronic pain. These clusters do not fall neatly into organ or body systems, and some conditions appear in more than one cluster.ConclusionsConsiderably more research is needed with large population-based datasets and a comprehensive set of reliable health diagnoses to better understand the complex nature and composition of multimorbid health conditions.
Highlights
Data The Australian Work Outcomes Research Cost-benefit (WORC) project provides a large cross-sectional data set of 78,430 working Australians to explore clusters of nonrandomly occurring multimorbid health conditions
The following health conditions were included in the analyses, as these were available in the Health and Productivity Questionnaire (HPQ): arthritis, asthma, back/neck pain, cancers, skin cancers, chronic obstructive pulmonary disease (COPD), cardiovascular disease (CVD), psychological distress, drug and alcohol problems, diabetes, fatigue, high blood pressure, high cholesterol, injury, migraine, obesity, bladder problems, heartburn, irritable bowel disorder, ulcers, osteoporosis, or other chronic pain
The two largest age groups were those aged 30-44 years and those aged 45-59 years, comprising 80% of the sample. Those aged less than 18 years and over 70 years were excluded from the study, as these age groups are not usually in the Australian workforce (0.2% deleted)
Summary
Comorbidity and multimorbidity are both used to describe two or more health conditions, a distinction is made between these two terms. Comorbidity is used when an index condition of interest is being discussed, and multimorbidity is used when no reference condition is considered [4]. These distinctions often are not clearly applied, and both terms are used interchangeably in the literature, we will. International and Australian research demonstrates the prevalence of comorbidity or multimorbidity as increasing significantly with age [3,4,5,6], indicating that patients with multimorbidity in general practice represent the rule, rather than the exception[5,7,8]. An Australian study exploring data obtained through 305 general practitioners in 2005 reported that the prevalence of multimorbidity increased with age, with 83% of surveyed patients aged 75 years or older having multimorbidity [6]
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