Abstract
Objective: To examine the effect of various morbidity clusters of chronic diseases on health-related time use and to explore factors associated with heavy time burden (more than 30 hours/month) of health-related activities.
Methods: Using a national survey, data were collected from 2,540 senior Australians. Natural clusters were identified using cluster analysis and clinical clusters using clinical expert opinion. We undertook a set of linear regressions to model people's time use, and logistic regressions to model heavy time burden.
Results: Time use increases with the number of chronic diseases. Six of the 12 diseases are significantly associated with higher time use, with the highest effect for diabetes followed by depression; 18% reported a heavy time burden, with diabetes again being the most significant disease. Clusters and dominant comorbid groupings do not contribute to predicting time use or time burden.
Conclusions: Total number of diseases and specific diseases are useful determinants of time use and heavy time burden. Dominant groupings and disease clusters do not predict time use. Implications: In considering time demands on patients and the need for care co-ordination, care providers need to be aware of how many and what specific diseases the patient faces.
| Original language | English |
|---|---|
| Pages (from-to) | 277-283 |
| Number of pages | 7 |
| Journal | Australian and New Zealand Journal of Public Health |
| Volume | 39 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 1 Jun 2015 |
| Externally published | Yes |
