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Xiong LY, Wood Alexander M, Wong YY, Wu CY, Ruthirakuhan M, Edwards JD, Lanctôt KL, Black SE, Rabin JS, Cogo-Moreira H, Swardfager W. Latent profiles of modifiable dementia risk factors in later midlife: relationships with incident dementia, cognition, and neuroimaging outcomes. Mol Psychiatry 2024:10.1038/s41380-024-02685-4. [PMID: 39103532 DOI: 10.1038/s41380-024-02685-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 07/22/2024] [Accepted: 07/24/2024] [Indexed: 08/07/2024]
Abstract
In 2020, the Lancet Commission identified 12 modifiable factors that increase population-level dementia risk. It is unclear if these risk factors co-occur among individuals in a clinically meaningful way. Using latent class analysis, we identified profiles of modifiable dementia risk factors in dementia-free adults aged 60-64 years from the UK Biobank. We then estimated associations between these profiles with incident dementia, cognition, and neuroimaging outcomes, and explored the differences across profiles in the effects of a polygenic risk score for Alzheimer's disease on outcomes. In 55,333 males and 63,063 females, three sex-specific latent profiles were identified: cardiometabolic risk, substance use-related risk, and low risk. The cardiometabolic risk profile in both males and females was associated with greater incidence of all-cause dementia (male: OR [95% CI] = 2.33 [2.03, 2.66]; female: OR [95% CI] = 1.44 [1.24, 1.68]), poorer cognitive performance, greater brain atrophy, and greater white matter hyperintensity volume compared to the low risk profile. The substance use-related risk profile in males was associated with poorer cognitive performance and greater white matter hyperintensities compared to the low risk profile, but no difference in all-cause dementia incidence was observed (OR [95% CI] = 1.00 [0.95, 1.06]). In females, the substance use-related risk profile demonstrated increased dementia incidence (OR [95% CI] = 1.58 [1.57, 1.58]) and greater brain atrophy but smaller white matter hyperintensity volume compared to the low risk profile. The polygenic risk score had larger effects among females, and differentially influenced outcomes across profiles; for instance, there were larger effects of the polygenic risk score on atrophy in the cardiometabolic profile vs. the low risk profile among males, and larger effects of the polygenic risk score on loss of white matter integrity in the cardiometabolic profile vs. the low risk profile among females. These results reveal three modifiable dementia risk profiles, their unique cognitive/neuroimaging outcomes, and their interactions with genetic risk for Alzheimer's disease. These differences highlight the need to consider population heterogeneity in risk prediction tools and in planning personalized prevention strategies.
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Affiliation(s)
- Lisa Y Xiong
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
| | - Madeline Wood Alexander
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
- Rehabilitation Sciences Institute, University of Toronto, Toronto, ON, Canada
| | - Yuen Yan Wong
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
| | - Che-Yuan Wu
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
| | - Myuri Ruthirakuhan
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Jodi D Edwards
- University of Ottawa Heart Institute, Ottawa, ON, Canada
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada
- ICES, Ottawa, ON, Canada
| | - Krista L Lanctôt
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Sandra E Black
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
- Department of Neurology, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Jennifer S Rabin
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
- Rehabilitation Sciences Institute, University of Toronto, Toronto, ON, Canada
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Hugo Cogo-Moreira
- Department of Education, ICT and Learning, Østfold University College, Halden, Norway
| | - Walter Swardfager
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada.
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada.
- Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada.
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Liu Y, Gao X, Zhang Y, Zeng M, Liu Y, Wu Y, Hu W, Lai Y, Liao J. Geographical variation in dementia prevalence across China: a geospatial analysis. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2024; 47:101117. [PMID: 38974661 PMCID: PMC11225804 DOI: 10.1016/j.lanwpc.2024.101117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 05/25/2024] [Accepted: 05/30/2024] [Indexed: 07/09/2024]
Abstract
Background Dementia poses great health and social challenges in China. Dementia prevalence may vary across geographic areas, while comparable estimations on provincial level is lacking. This study aims to estimate dementia prevalence by provinces across China, taking into account risk factors of individual level and potential spatial correlation of provinces. Methods In this study, 17,176 adults aged 50 years or older were included from the fourth wave of the China Health and Retirement Longitudinal Study (CHARLS 2018), covering 28 provinces, autonomous regions and municipalities. To improve provincial representativeness, we constructed provincial survey weights based on China 7th census (2020). The prevalence of dementia and 95% Bayesian credible intervals (BCIs) were estimated using a Bayesian conditional autoregressive (CAR) model with spatially varying coefficients of covariates. Findings The weighted prevalence of dementia at provincial level in China in 2018 ranged from 2.62% (95%BCI: 1.70%, 3.91%) to 13.53% (95%BCI: 8.82%, 20.93%). High dementia prevalence was concentrated in North China, with a prominent high-high cluster, while provinces of low prevalence were concentrated on East and South China, characterized by a low-low cluster. Ordered by the median estimation of prevalence, the top 10% of provinces, include Xinjiang, Jilin, and Beijing. Meanwhile, Fujian, Zhejiang, and Guangdong rank among the last. The association between dementia prevalence and drinking, smoking, social isolation, physical inactivity, hearing impairment, hypertension, and diabetes exhibits provincial variation. Interpretation Our study identifies a geospatial disparity in dementia prevalence and risk factor effects across China's provinces, with high-high and low-low clusters in some northern and southern provinces, respectively. The findings emphasize the need for targeted strategies, such as addressing hypertension and hearing impairment, in specific regions for more effective dementia prevention and treatment. Funding National Science Foundation of China/the Economic and Social Research Council, UK Research and Innovation joint call: Understanding and Addressing Health and Social Challenges for Ageing in the UK and China. UK-China Health And Social Challenges Ageing Project (UKCHASCAP): present and future burden of dementia, and policy responses (grant number 72061137003, ES/T014377/1).
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Affiliation(s)
- Yixuan Liu
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510000, China
- Sun Yat-sen Global Health Institute, Institute of State Governance, Sun Yat-sen University, Guangzhou, China
| | - Xinyuan Gao
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510000, China
- Sun Yat-sen Global Health Institute, Institute of State Governance, Sun Yat-sen University, Guangzhou, China
| | - Yongjin Zhang
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510000, China
- Sun Yat-sen Global Health Institute, Institute of State Governance, Sun Yat-sen University, Guangzhou, China
| | - Minrui Zeng
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510000, China
- Sun Yat-sen Global Health Institute, Institute of State Governance, Sun Yat-sen University, Guangzhou, China
| | - Yuyang Liu
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510000, China
- Shenzhen Health Development Research and Data Management Center, Shenzhen, China
| | - Yanjuan Wu
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510000, China
- Sun Yat-sen Global Health Institute, Institute of State Governance, Sun Yat-sen University, Guangzhou, China
| | - Weihua Hu
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100871, China
| | - Yingsi Lai
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510000, China
- Sun Yat-sen Global Health Institute, Institute of State Governance, Sun Yat-sen University, Guangzhou, China
| | - Jing Liao
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510000, China
- Sun Yat-sen Global Health Institute, Institute of State Governance, Sun Yat-sen University, Guangzhou, China
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Dove A, Xu W. Cardiometabolic multimorbidity and cognitive decline. THE LANCET. HEALTHY LONGEVITY 2023:S2666-7568(23)00053-3. [PMID: 37150184 DOI: 10.1016/s2666-7568(23)00053-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 03/22/2023] [Indexed: 05/09/2023] Open
Affiliation(s)
- Abigail Dove
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, SE-171 65 Stockholm, Sweden.
| | - Weili Xu
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, SE-171 65 Stockholm, Sweden
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