Abstract
Multimorbidity—the co-occurrence of two or more chronic health conditions—affects > 86% of people with dementia. It is associated with cognitive and functional decline, reduced health-related quality of life, increased health-care use, and higher mortality. The relationship between multimorbidity and dementia is potentially bidirectional; conditions such as hypertension and diabetes increase the risk of developing dementia, and cognitive impairment can complicate their management. This complexity presents challenges in health care and research, affecting treatment decisions and often leading to the exclusion of these individuals from clinical trials. Understanding multimorbidity through long-term prospective studies is crucial to clarify its relationship with dementia. Investigating specific disease combinations, environmental and genetic factors, and their impacts on cognitive health will guide the development of effective prediction models and inclusive intervention strategies for diverse global populations across the life course. Highlights: Multimorbidity affects > 86% of individuals with dementia, worsening outcomes. The relationship between multimorbidity and dementia is potentially bidirectional. Chronic conditions hinder dementia management and clinical trial inclusion. Life-course multimorbidity research is key to dementia risk reduction strategies. Prospective studies are needed to improve prediction models and interventions.
| Original language | English |
|---|---|
| Article number | e70546 |
| Journal | Alzheimer's and Dementia |
| Volume | 21 |
| Issue number | 8 |
| DOIs | |
| State | Published - Aug 2025 |
Bibliographical note
Publisher Copyright:© 2025 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.
Funding
The authors are members of the Comorbidity & Multimorbidity in Dementia Work Group within the Design and Data Analytics Professional Interest Area of the Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment (ISTAART). The authors would like to thank the ISTAART staff, particularly Jodi Titiner, for their support. J.B. and T.J.W. are funded by the National Institute for Health and Care Research (NIHR) Applied Research Collaboration (ARC) North East and North Cumbria (NENC) (NIHR200173). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. K.A.Q.C. is funded by the National Institute on Aging (NIA; R01-AG087258). I.F. is supported by a grant from the NIA (R01AG073593). S.M. is supported by the NIA under award number U19AG078109. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. E.K. is supported by funding from the Nicolaus and Margrit Langbehn Foundation. U.S. acknowledges support from the Ontario Graduate Scholarship, Queen Elizabeth II/Paul and Adelle DEACON Graduate Scholarships in Science and Technology, and University of Toronto Fellowship, Canada. P.P.Z. was supported by the National Center on Advancing Translational Sciences Training Program Award Number 3OT2OD032581-01S1-713 on Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) Coordinating Center & Data Science Training Core and Communications Hub and the National Institutes on Aging (NIA) Center on the Demography and Economics of Aging, Center for Healthy Aging Behaviors and Longitudinal Investigation (CHABLIS), grant P30 AG066619 through the University of Chicago. J.B. and T.J.W. are funded by the National Institute for Health and Care Research (NIHR) Applied Research Collaboration (ARC) North East and North Cumbria (NENC) (NIHR200173). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. K.A.Q.C. is funded by the National Institute on Aging (NIA; R01‐AG087258). I.F. is supported by a grant from the NIA (R01AG073593). S.M. is supported by the NIA under award number U19AG078109. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. E.K. is supported by funding from the Nicolaus and Margrit Langbehn Foundation. U.S. acknowledges support from the Ontario Graduate Scholarship, Queen Elizabeth II/Paul and Adelle DEACON Graduate Scholarships in Science and Technology, and University of Toronto Fellowship, Canada. P.P.Z. was supported by the National Center on Advancing Translational Sciences Training Program Award Number 3OT2OD032581‐01S1‐713 on Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM‐AHEAD) Coordinating Center & Data Science Training Core and Communications Hub and the National Institutes on Aging (NIA) Center on the Demography and Economics of Aging, Center for Healthy Aging Behaviors and Longitudinal Investigation (CHABLIS), grant P30 AG066619 through the University of Chicago.
| Funders | Funder number |
|---|---|
| Alzheimer's Association | |
| Toronto Western Hospital University of Toronto | |
| The University of Chicago | |
| National Institute for Health and Care Research | |
| National Institutes of Health (NIH) | |
| ISTAART | |
| Nicolaus and Margrit Langbehn Foundation | |
| Applied Research Collaboration | NIHR200173 |
| National Institute on Aging | R01AG073593, R01‐AG087258, U19AG078109, P30 AG066619 |
| National Center for Advancing Translational Sciences (NCATS) | 3OT2OD032581‐01S1‐713 |
Keywords
- all-cause dementia
- comorbidity
- multimorbidity
- multiple long-term conditions
ASJC Scopus subject areas
- Epidemiology
- Health Policy
- Developmental Neuroscience
- Clinical Neurology
- Geriatrics and Gerontology
- Cellular and Molecular Neuroscience
- Psychiatry and Mental health
