Patterns of Multimorbidity in Working Australians
Author Information
Author(s): Holden Libby, Scuffham Paul A, Hilton Michael F, Muspratt Alexander, Ng Shu-Kay, Whiteford Harvey A
Primary Institution: Griffith University
Hypothesis
This paper aims to identify nonrandom clusters of multimorbidity.
Conclusion
Considerably more research is needed with large population-based datasets to better understand the complex nature and composition of multimorbid health conditions.
Supporting Evidence
- The study identified six clinically-meaningful groups of multimorbid health conditions.
- Some health conditions appeared in more than one cluster.
- The findings suggest that health conditions do not cluster neatly into organ or body systems.
Takeaway
The study found that many health problems often occur together in groups, which can help doctors understand and treat patients better.
Methodology
Exploratory factor analysis was used to identify nonrandomly occurring clusters of multimorbid health conditions from a cross-sectional dataset.
Potential Biases
The sample overrepresented females and excluded individuals on extended sick leave or out of the workforce.
Limitations
The study had a low response rate (22%) and may not represent the general population, as it only included employees from large organizations.
Participant Demographics
{"gender":{"female":65,"male":35},"age_groups":{"30-44":43,"45-59":37},"marital_status":{"married_or_cohabiting":71,"separated_divorced_widowed_never_married":29},"education_level":{"completed_tertiary":48},"annual_wage":{"earning_50000_or_more":53}}
Digital Object Identifier (DOI)
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