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Multimorbidity, disease clusters and risk of all-cause and cause-specific mortality: a population-based prospective cohort study

Abstract:
The number of people living with ≥ two health conditions, termed multimorbidity, is increasing. We investigated the impact of multimorbidity on all-cause and cause-specific mortality risk in 502,370 UK Biobank participants aged 40 to 70 years. Participants attended an assessment centre between 2006 and 2010 and self-reported medical conditions during a nurse-led verbal interview. The presence of ≥ 2 long-term conditions from a preselected list of 43 conditions was used to define multimorbidity. In a training sample (80% of participants with multimorbidity), disease clusters were identified in four groups: women aged (1) 40–59 or (2) 60–70, and men aged (3) 40–59 or (4) 60–70. Mortality was ascertained from linkage to death records. Multivariate Cox proportional-hazards regression models were used to assess the association between multimorbidity and mortality adjusted for age, sex, ethnicity, socioeconomic status and education. Over a 16-year follow-up period (median = 13 years) dose–response associations were observed between number of multimorbid conditions and risk of all-cause mortality (n = 44,399 deaths), and particularly strong dose-response associations with cause-specific deaths due to cardiovascular and respiratory conditions. For women, a mental health/cancer/pain-related conditions cluster at ages 40–59 (Hazard Ratio [HR] = 2.61, 95% Confidence Interval [CI] 2.33–2.93), and a respiratory and pain-related conditions cluster at ages 60–70 (HR = 2.03, 95% CI 1.0–2.17), were associated with the greatest risk of mortality. For men, clusters of cardiometabolic conditions at ages 40–59 (HR = 3.43, 95% CI 3.14–3.74) and 60–70 (HR = 2.24, 95% CI 2.13–2.35) were associated with greater mortality risk. These findings suggest that understanding the impact of multimorbidity, and especially clusters of disease, is important for tailoring healthcare approaches for mortality risk reduction.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/s41598-025-25285-w

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Institution:
University of Oxford
Department:
Big Data Institute
Role:
Author
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Institution:
University of Oxford
Department:
Big Data Institute
Role:
Author
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Institution:
University of Oxford
Division:
MSD
Department:
Nuffield Department of Population Health
Role:
Author
More by this author
Institution:
University of Oxford
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Nuffield Department of Population Health
Role:
Author


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Funder identifier:
https://ror.org/054225q67


Publisher:
Nature Research
Journal:
Scientific Reports More from this journal
Volume:
15
Issue:
1
Article number:
41393
Publication date:
2025-11-21
Acceptance date:
2025-10-20
DOI:
EISSN:
2045-2322
ISSN:
2045-2322


Language:
English
Pubs id:
2334182
UUID:
uuid_0a102581-4a94-4d34-a1c9-f6e2904bb9f9
Local pid:
pubs:2334182
Source identifiers:
3496450
Deposit date:
2025-11-21
ARK identifier:
This ORA record was generated from metadata provided by an external service. It has not been edited by the ORA Team.

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