Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2011 Jun 2;9(1):15.
doi: 10.1186/1478-7954-9-15.

Patterns of multimorbidity in working Australians

Libby Holden  1 , Paul A Scuffham #  1 , Michael F Hilton #  2 , Alexander Muspratt #  3 , Shu-Kay Ng #  1 , Harvey A Whiteford #  2   3
Affiliations

Patterns of multimorbidity in working Australians

Libby Holden et al. Popul Health Metr. .

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.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Scree Test with Eigenvalues for Range of Solutions.
See this image and copyright information in PMC

References

    1. Kessler RC. Comorbidity. Amsterdam, NY: Elsevier Science Ltd; 2001.
    1. van den Akker M, Buntinx F, Metsemakers J, Knottnerus J. Marginal impact of psychosocial factors on multimorbidity: results of an explorative nested case-control study. Social Science & Medicine. 2000;50:1679–1693. doi: 10.1016/S0277-9536(99)00408-6. - DOI - PubMed
    1. van den Akker M, Buntinx F, Metsemakers JF, Roos S, Knottnerus JA. Multimorbidity in general practice: prevalence, incidence, and determinants of co-occurring chronic and recurrent diseases. J Clin Epidemiol. 1998;51:367–375. doi: 10.1016/S0895-4356(97)00306-5. - DOI - PubMed
    1. van den Akker M, Buntinx F, Roos S, Knottnerus J. Problems in determining occurrence rates of multimorbidity. Journal of Clinical Epidemiology. 2001;54:675–679. doi: 10.1016/S0895-4356(00)00358-9. - DOI - PubMed
    1. Fortin M, Bravo G, Hudon C, Vanasse A, Lapointe L. Prevalence of multimorbidity among adults seen in family practice. Annals of Family Medicine. 2005;3:223. doi: 10.1370/afm.272. - DOI - PMC - PubMed

LinkOut - more resources