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Impact of household size and co-resident multimorbidity on unplanned hospitalisation and transition to care home
,
Stewart W. Mercer,
Eleojo Abubakar,
Andrew Lawson ,
Nazir Lone ,
Anna Rawlings ,
Jane Lyons,
Ronan Lyons,
Amy Mizen ,
Rich Fry ,
Gergő Baranyi,
Jamie Pearce,
Chris Dibben,
Karin Modig,
Rhiannon Owen ,
Bruce Guthrie
Nature Communications, Volume: 16, Start page: 1718
Swansea University Authors:
Anna Rawlings , Jane Lyons, Ronan Lyons, Amy Mizen , Rich Fry , Rhiannon Owen
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© The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
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DOI (Published version): 10.1038/s41467-025-56990-9
Abstract
The ability to manage ill health and care needs might be affected by who a person lives with. This study examined how the risk of unplanned hospitalisation and transition to living in a care home varied according to household size and co-resident multimorbidity. Here we show results from a cohort st...
| Published in: | Nature Communications |
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| ISSN: | 2041-1723 |
| Published: |
Springer Nature
2025
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa68925 |
| Abstract: |
The ability to manage ill health and care needs might be affected by who a person lives with. This study examined how the risk of unplanned hospitalisation and transition to living in a care home varied according to household size and co-resident multimorbidity. Here we show results from a cohort study using Welsh nationwide linked healthcare and census data, that employed multilevel multistate models to account for the competing risk of death and clustering within households. The highest rates of unplanned hospitalisation and care home transition were in those living alone. Event rates were lower in all shared households and lowest when co-residents did not have multimorbidity. These differences were more substantial for care home transition. Therefore, living alone or with co-residents with multimorbidity poses additional risk for unplanned hospitalisation and care home transition beyond an individual’s sociodemographic and health characteristics. Understanding the mechanisms behind these associations is necessary to inform targeted intervention strategies. |
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| College: |
Faculty of Medicine, Health and Life Sciences |
| Funders: |
Medical Research Council MR/W000253/1 fellowship for C.M.; National Institute for Health Research (NIHR) Artificial Intelligence and Multimorbidity for B.G. and S.W.M.: Clustering in Individuals, Space and Clinical Context (AIM-CISC) grant NIHR202639; Legal and General plc funding for the Advanced Care Research Centre for B.G. and S.W.M. |
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