Patterns of multimorbidity in working Australians

Holden, Libby, Scuffham, Paul A., Hilton, Michael F., Muspratt, Alexander, Ng, Shu-Kay and Whiteford, Harvey A. (2011) Patterns of multimorbidity in working Australians. Population Health Metrics, 9 15.1-15.5. doi:10.1186/1478-7954-9-15


Author Holden, Libby
Scuffham, Paul A.
Hilton, Michael F.
Muspratt, Alexander
Ng, Shu-Kay
Whiteford, Harvey A.
Title Patterns of multimorbidity in working Australians
Journal name Population Health Metrics   Check publisher's open access policy
ISSN 1478-7954
Publication date 2011-06-02
Sub-type Article (original research)
DOI 10.1186/1478-7954-9-15
Open Access Status DOI
Volume 9
Start page 15.1
End page 15.5
Total pages 6
Place of publication London, United Kingdom
Publisher BioMed Central Ltd.
Language eng
Subject 2739 Public Health, Environmental and Occupational Health
2713 Epidemiology
Abstract Background: Multimorbidity 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.Methods: The 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.Results: Six 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.Conclusions: Considerably 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.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Public Health Publications
 
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