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Zhao Q, Seow WJ. Association of solid fuel use with cognitive function and the modifying role of lifestyle: a nationwide cohort study in China. ENVIRONMENTAL RESEARCH 2024:119538. [PMID: 38971352 DOI: 10.1016/j.envres.2024.119538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 05/24/2024] [Accepted: 06/30/2024] [Indexed: 07/08/2024]
Abstract
BACKGROUND Indoor air pollution from solid fuel use might be harmful for cognitive function, while healthy lifestyle is associated with better cognitive function. The extent to which lifestyle modifies the association of solid fuel use with cognitive function remains unknown. METHODS A total of 21,008 individuals aged 16 to 92 were enrolled in 2010 and followed up to 2014 in the China Family Panel Studies (CFPS). Cognitive function was assessed using standardized math test and word test in three waves. Solid fuel use was assessed by self-report of firewood, straw, or coal for cooking at baseline. Lifestyle profile was classified into two groups (favorable vs. unfavorable) based on five modifiable lifestyle factors including alcohol drinking, smoking, body mass index, diet, and physical activity. Linear mixed-effects models were employed to assess the association of solid fuel use and lifestyle with cognitive function. The effect modification of lifestyle was analyzed. RESULTS A total of 49.7% of the study population used solid cooking fuel and 17.4% had a favorable lifestyle. Solid fuel use was associated with a significant decrease in cognitive function (β = -0.29, 95% CI: -0.39, -0.19 for math test; β = -0.62, 95% CI: -0.84, -0.41 for word test). Lifestyle significantly modified this association (p-interaction: 0.006 for math test; 0.016 for word test), with the corresponding association being less pronounced among participants adhering to a favorable lifestyle compared to those with an unfavorable lifestyle. CONCLUSION A favorable lifestyle may attenuate the negative association of solid fuel use with cognitive function. Adopting a favorable lifestyle has the potential to counteract the adverse neurological effect caused by indoor air pollution.
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Affiliation(s)
- Qi Zhao
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Wei Jie Seow
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore; Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore.
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Prince JB, Davis HL, Tan J, Muller-Townsend K, Markovic S, Lewis DMG, Hastie B, Thompson MB, Drummond PD, Fujiyama H, Sohrabi HR. Cognitive and neuroscientific perspectives of healthy ageing. Neurosci Biobehav Rev 2024; 161:105649. [PMID: 38579902 DOI: 10.1016/j.neubiorev.2024.105649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 03/17/2024] [Accepted: 03/30/2024] [Indexed: 04/07/2024]
Abstract
With dementia incidence projected to escalate significantly within the next 25 years, the United Nations declared 2021-2030 the Decade of Healthy Ageing, emphasising cognition as a crucial element. As a leading discipline in cognition and ageing research, psychology is well-equipped to offer insights for translational research, clinical practice, and policy-making. In this comprehensive review, we discuss the current state of knowledge on age-related changes in cognition and psychological health. We discuss cognitive changes during ageing, including (a) heterogeneity in the rate, trajectory, and characteristics of decline experienced by older adults, (b) the role of cognitive reserve in age-related cognitive decline, and (c) the potential for cognitive training to slow this decline. We also examine ageing and cognition through multiple theoretical perspectives. We highlight critical unresolved issues, such as the disparate implications of subjective versus objective measures of cognitive decline and the insufficient evaluation of cognitive training programs. We suggest future research directions, and emphasise interdisciplinary collaboration to create a more comprehensive understanding of the factors that modulate cognitive ageing.
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Affiliation(s)
- Jon B Prince
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia.
| | - Helen L Davis
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia
| | - Jane Tan
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia
| | - Katrina Muller-Townsend
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia
| | - Shaun Markovic
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia; Discipline of Psychology, Counselling and Criminology, Edith Cowan University, WA, Australia
| | - David M G Lewis
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia
| | | | - Matthew B Thompson
- School of Psychology, Murdoch University, WA, Australia; Centre for Biosecurity and One Health, Harry Butler Institute, Murdoch University, WA, Australia
| | - Peter D Drummond
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia
| | - Hakuei Fujiyama
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia; Centre for Molecular Medicine and Innovative Therapeutics, Murdoch University, WA, Australia
| | - Hamid R Sohrabi
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia; School of Medical and Health Sciences, Edith Cowan University, WA, Australia; Department of Biomedical Sciences, Macquarie University, NSW, Australia.
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Eliasen EH, Weihe P, Debes F, Tróndarson M, Petersen MS. 10-Year Cognitive Change in the Faroese Septuagenarian Cohort and Impact of Sociodemographic, Lifestyle, and Health Factors. J Aging Health 2024:8982643241255405. [PMID: 38819787 DOI: 10.1177/08982643241255405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2024]
Abstract
OBJECTIVES To investigate cognitive change in multiple cognitive domains in a population-based cohort of 713 Faroese older adults. METHODS Participants were cognitively tested at baseline (70-74 years) and re-evaluated after 10 years. Changes in cognitive performance and the impact of sociodemographic factors, lifestyle, and health conditions were analysed using mixed-effect models. Participants free from dementia were studied in separate analyses. RESULTS A significant decline over 10 years was observed in most of the neuropsychological tests. People living in rural areas, married or cohabiting people, people without professional education, slightly older persons, smokers, teetotalers, and people with heart disease and abnormal electrocardiogram (ECG) had a steeper decline in cognitive ability. Conflicting results were found for sex and people with myocardial infarction (MI). DISCUSSION There are modifiable factors that contribute to cognitive decline which should be addressed in future public health efforts.
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Affiliation(s)
- Eina H Eliasen
- Department of Research, The National Hospital of the Faroe Islands, Tórshavn, Faroe Islands
- Faculty of Health Sciences, University of the Faroe Islands, Tórshavn, Faroe Islands
| | - Pál Weihe
- Department of Research, The National Hospital of the Faroe Islands, Tórshavn, Faroe Islands
- Faculty of Health Sciences, University of the Faroe Islands, Tórshavn, Faroe Islands
- Center of Health Sciences, University of the Faroe Islands, Tórshavn, Faroe Islands
| | - Fróði Debes
- Department of Research, The National Hospital of the Faroe Islands, Tórshavn, Faroe Islands
| | - Marjun Tróndarson
- Department of Research, The National Hospital of the Faroe Islands, Tórshavn, Faroe Islands
| | - Maria Skaalum Petersen
- Department of Research, The National Hospital of the Faroe Islands, Tórshavn, Faroe Islands
- Faculty of Health Sciences, University of the Faroe Islands, Tórshavn, Faroe Islands
- Center of Health Sciences, University of the Faroe Islands, Tórshavn, Faroe Islands
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Chen S, Nagel CL, Liu R, Botoseneanu A, Allore HG, Newsom JT, Thielke S, Kaye J, Quiñones AR. Mental-somatic multimorbidity in trajectories of cognitive function for middle-aged and older adults. PLoS One 2024; 19:e0303599. [PMID: 38743678 PMCID: PMC11093294 DOI: 10.1371/journal.pone.0303599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/26/2024] [Indexed: 05/16/2024] Open
Abstract
INTRODUCTION Multimorbidity may confer higher risk for cognitive decline than any single constituent disease. This study aims to identify distinct trajectories of cognitive impairment probability among middle-aged and older adults, and to assess the effect of changes in mental-somatic multimorbidity on these distinct trajectories. METHODS Data from the Health and Retirement Study (1998-2016) were employed to estimate group-based trajectory models identifying distinct trajectories of cognitive impairment probability. Four time-varying mental-somatic multimorbidity combinations (somatic, stroke, depressive, stroke and depressive) were examined for their association with observed trajectories of cognitive impairment probability with age. Multinomial logistic regression analysis was conducted to quantify the association of sociodemographic and health-related factors with trajectory group membership. RESULTS Respondents (N = 20,070) had a mean age of 61.0 years (SD = 8.7) at baseline. Three distinct cognitive trajectories were identified using group-based trajectory modelling: (1) Low risk with late-life increase (62.6%), (2) Low initial risk with rapid increase (25.7%), and (3) High risk (11.7%). For adults following along Low risk with late-life increase, the odds of cognitive impairment for stroke and depressive multimorbidity (OR:3.92, 95%CI:2.91,5.28) were nearly two times higher than either stroke multimorbidity (OR:2.06, 95%CI:1.75,2.43) or depressive multimorbidity (OR:2.03, 95%CI:1.71,2.41). The odds of cognitive impairment for stroke and depressive multimorbidity in Low initial risk with rapid increase or High risk (OR:4.31, 95%CI:3.50,5.31; OR:3.43, 95%CI:2.07,5.66, respectively) were moderately higher than stroke multimorbidity (OR:2.71, 95%CI:2.35, 3.13; OR: 3.23, 95%CI:2.16, 4.81, respectively). In the multinomial logistic regression model, non-Hispanic Black and Hispanic respondents had higher odds of being in Low initial risk with rapid increase and High risk relative to non-Hispanic White adults. CONCLUSIONS These findings show that depressive and stroke multimorbidity combinations have the greatest association with rapid cognitive declines and their prevention may postpone these declines, especially in socially disadvantaged and minoritized groups.
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Affiliation(s)
- Siting Chen
- OHSU-PSU School of Public Health, Portland, Oregon, United States of America
| | - Corey L. Nagel
- College of Nursing, University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States of America
| | - Ruotong Liu
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon, United States of America
| | - Anda Botoseneanu
- Department of Health & Human Services, University of Michigan, Dearborn, Michigan, United States of America
- Institute of Gerontology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Heather G. Allore
- Department of Internal Medicine, Yale University, New Haven, Connecticut, United States of America
- Department of Biostatistics, Yale University, New Haven, Connecticut, United States of America
| | - Jason T. Newsom
- Department of Psychology, Portland State University, Portland, Oregon, United States of America
| | - Stephen Thielke
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, Washington, United States of America
| | - Jeffrey Kaye
- Department of Neurology, Oregon Health & Science University, Portland, Oregon, United States of America
| | - Ana R. Quiñones
- OHSU-PSU School of Public Health, Portland, Oregon, United States of America
- Department of Family Medicine, Oregon Health & Science University, Portland, Oregon, United States of America
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Ksinan AJ, Dalecká A, Court T, Pikhart H, Bobák M. Pulmonary function and trajectories of cognitive decline in aging population. Exp Gerontol 2024; 189:112386. [PMID: 38428543 DOI: 10.1016/j.exger.2024.112386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 02/21/2024] [Accepted: 02/23/2024] [Indexed: 03/03/2024]
Abstract
BACKGROUND The number of older people with cognitive impairment is increasing worldwide. Impaired lung function might be associated with cognitive decline in older age; however, results from large longitudinal studies are lacking. In this study, we examined the longitudinal associations between pulmonary function and the trajectories of cognitive decline using prospective population-based SHARE data from 14 countries. METHODS The analytic sample included N = 32,049 older adults (Mean age at baseline = 64.76 years). The dependent variable was cognitive performance, measured repeatedly across six waves in three domains: verbal fluency, memory, and numeracy. The main predictor of interest was peak expiratory flow (PEF). The data were analyzed in a multilevel accelerated longitudinal design, with models adjusted for a variety of covariates. RESULTS A lower PEF score was associated with lower cognitive performance for each domain as well as a lower global cognitive score. These associations remained statistically significant after adjusting for all covariates Q4 vs Q1 verbal fluency: unstandardized coefficient B = -3.15; numeracy: B = -0.52; memory: B = -0.64; global cognitive score B = -2.65, all p < .001). However, the PEF score was not found to be associated with the rate of decline for either of the cognitive outcomes. CONCLUSIONS In this large multi-national longitudinal study, the PEF score was independently associated with lower levels of cognitive functions, but it did not predict a future decline. The results suggest that pre-existing differences in lung functions are responsible for variability in cognitive functions and that these differences remained stable across aging.
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Affiliation(s)
- Albert J Ksinan
- RECETOX, Faculty of Science, Masaryk University, Brno, Czech Republic.
| | - Andrea Dalecká
- RECETOX, Faculty of Science, Masaryk University, Brno, Czech Republic
| | - Tatyana Court
- RECETOX, Faculty of Science, Masaryk University, Brno, Czech Republic
| | - Hynek Pikhart
- RECETOX, Faculty of Science, Masaryk University, Brno, Czech Republic; Department of Epidemiology & Public Health, University College London, Institute of Epidemiology and Health Care, London, UK
| | - Martin Bobák
- RECETOX, Faculty of Science, Masaryk University, Brno, Czech Republic; Department of Epidemiology & Public Health, University College London, Institute of Epidemiology and Health Care, London, UK
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Wang J, Liang X, Qiu Q, Yan F, Fang Y, Shen C, Wang H, Chen Y, Xiao S, Yue L, Li X. Cognitive trajectories in older adults and the role of depressive symptoms: A 7-year follow-up study. Asian J Psychiatr 2024; 95:104007. [PMID: 38520944 DOI: 10.1016/j.ajp.2024.104007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 01/06/2024] [Accepted: 03/16/2024] [Indexed: 03/25/2024]
Abstract
OBJECTIVES To examine different trajectories of cognitive changes in elderly adults and explore the mediating role of depressive symptoms. DESIGN A 7-year, community-based, prospective cohort study. SETTING The downtown neighborhood of Shanghai, China. PARTICIPANTS A cohort of 394 older adults, with an average age of 71.8 years, was recruited in 2015 and has been reassessed every two years until 2021. METHODS Latent Class Growth Analysis was used to model aging trajectories and Linear Mixed-Effect Models for Repeated Measures were used to estimate the least squares mean changes of cognition between subjects with depression (DEP+) and without (DEP-) across all visits. RESULTS Three cognitive trajectories were identified: the "successful aging" (SA) trajectory had the best and most consistent performance (n=229, 55.9%); the "normal aging" (NA) trajectory showed lower but stable cognition (n=141, 37.3%); while the "cognitive decline" (CD) trajectory displayed poor and declining cognition (n=24, 6.8%). Depressive symptoms were found to be influential across all trajectories. In the CD trajectory, the MoCA scores of the DEP+ group increased in within-group comparisons and were significantly higher than those of the DEP- group at visits 1 and 3 in between-group comparisons. A similar trend was observed in the NA trajectory, though it did not reach statistical significance. CONCLUSIONS Our research suggests that mild and decreasing depressive symptoms can be a reversible factor that might slow down the irreversible cognitive decline in the elderly. Therefore, we suggest that even mild depressive symptoms in the elderly should be monitored and detected.
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Affiliation(s)
- Jianjun Wang
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai 200030, China; Department of Neurology and Psychology, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen 518000, China
| | - Xiao Liang
- Shanghai Xuhui District Mental Health Center, Shanghai 200232, China
| | - Qi Qiu
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Feng Yan
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Yuan Fang
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Changyi Shen
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Huijuan Wang
- Shanghai Jingan District Mental Health Center, Shanghai 200040, China
| | - Yuming Chen
- Shanghai Jingan District Mental Health Center, Shanghai 200040, China
| | - Shifu Xiao
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Ling Yue
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai 200030, China.
| | - Xia Li
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai 200030, China.
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Rodrigues EA, Christie GJ, Cosco T, Farzan F, Sixsmith A, Moreno S. A Subtype Perspective on Cognitive Trajectories in Healthy Aging. Brain Sci 2024; 14:351. [PMID: 38672003 PMCID: PMC11048421 DOI: 10.3390/brainsci14040351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2024] [Revised: 03/25/2024] [Accepted: 03/30/2024] [Indexed: 04/28/2024] Open
Abstract
Cognitive aging is a complex and dynamic process characterized by changes due to genetics and environmental factors, including lifestyle choices and environmental exposure, which contribute to the heterogeneity observed in cognitive outcomes. This heterogeneity is particularly pronounced among older adults, with some individuals maintaining stable cognitive function while others experience complex, non-linear changes, making it difficult to identify meaningful decline accurately. Current research methods range from population-level modeling to individual-specific assessments. In this work, we review these methodologies and propose that population subtyping should be considered as a viable alternative. This approach relies on early individual-specific detection methods that can lead to an improved understanding of changes in individual cognitive trajectories. The improved understanding of cognitive trajectories through population subtyping can lead to the identification of meaningful changes and the determination of timely, effective interventions. This approach can aid in informing policy decisions and in developing targeted interventions that promote cognitive health, ultimately contributing to a more personalized understanding of the aging process within society and reducing the burden on healthcare systems.
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Affiliation(s)
- Emma A. Rodrigues
- School of Interactive Arts and Technology, Simon Fraser University, Surrey, BC V3T 0A3, Canada
| | | | - Theodore Cosco
- Department of Gerontology, Simon Fraser University, Vancouver, BC V6B 5K3, Canada
| | - Faranak Farzan
- School of Mechatronics and Systems Engineering, Simon Fraser University, Surrey, BC V3T 0A3, Canada
| | - Andrew Sixsmith
- Department of Gerontology, Simon Fraser University, Vancouver, BC V6B 5K3, Canada
| | - Sylvain Moreno
- School of Interactive Arts and Technology, Simon Fraser University, Surrey, BC V3T 0A3, Canada
- Circle Innovation, Simon Fraser University, Surrey, BC V3T 0A3, Canada
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Lobo E, Gracia-García P, Lobo A. Longitudinal trajectories of cognitive aging. Curr Opin Psychiatry 2024; 37:123-129. [PMID: 38226551 DOI: 10.1097/yco.0000000000000918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/17/2024]
Abstract
PURPOSE OF REVIEW This review summarizes recent evidence related to the cognitive trajectories of aging, the factors associated with the different trajectories, and the effect of sex on cognitive decline. RECENT FINDINGS Trajectories of cognitive aging identified in different studies vary in number, in the proportion of individuals falling into each of the classes and in the predictors of class membership. Trajectories observed include types with 'rapid decline', those with 'gradual decline' and those with 'maintenance of high level' of cognitive performance. Predictors of decline and predictors of maintenance of cognitive performance may be different. While factors such as education were in general associated with high performance, and reversely with low performance, other factors, such as depression were predictors only for some groups, particularly the declining ones. Sex differences in cognitive trajectories and the associated predictive factors have also been identified. SUMMARY The findings on education may be particularly important in populations with low educational level, especially among women and the findings on depression have special interest in preventing cognitive decline in women. Further work is required to explain intriguing inconsistencies observed in the literature.
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Affiliation(s)
- Elena Lobo
- Department of Preventive Medicine and Public Health, Universidad de Zaragoza
- Instituto de Investigación Sanitaria de Aragón (IIS Aragón), Zaragoza
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Ministry of Science and Innovation, Madrid
| | - Patricia Gracia-García
- Instituto de Investigación Sanitaria de Aragón (IIS Aragón), Zaragoza
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Ministry of Science and Innovation, Madrid
- Department of Medicine and Psychiatry, Universidad de Zaragoza
- Psychiatry Service, Hospital Universitario Miguel Servet, Zaragoza, Spain
| | - Antonio Lobo
- Instituto de Investigación Sanitaria de Aragón (IIS Aragón), Zaragoza
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Ministry of Science and Innovation, Madrid
- Department of Medicine and Psychiatry, Universidad de Zaragoza
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Rajendrakumar AL, Arbeev KG, Bagley O, Yashin AI, Ukraintseva S. The SNP rs6859 in NECTIN2 gene is associated with underlying heterogeneous trajectories of cognitive changes in older adults. BMC Neurol 2024; 24:78. [PMID: 38408961 PMCID: PMC10898142 DOI: 10.1186/s12883-024-03577-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 02/20/2024] [Indexed: 02/28/2024] Open
Abstract
BACKGROUND Functional decline associated with dementia, including in Alzheimer's disease (AD), is not uniform across individuals, and respective heterogeneity is not yet fully explained. Such heterogeneity may in part be related to genetic variability among individuals. In this study, we investigated whether the SNP rs6859 in nectin cell adhesion molecule 2 (NECTIN2) gene (a major risk factor for AD) influences trajectories of cognitive decline in older participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). METHODS We retrospectively analyzed records on 1310 participants from the ADNI database for the multivariate analysis. We used longitudinal measures of Mini-Mental State Examination (MMSE) scores in participants, who were cognitively normal, or having AD, or other cognitive deficits to investigate the trajectories of cognitive changes. Multiple linear regression, linear mixed models and latent class analyses were conducted to investigate the association of the SNP rs6859 with MMSE. RESULTS The regression coefficient per one allele dose of the SNP rs6859 was independently associated with MMSE in both cross-sectional (-2.23, p < 0.01) and linear mixed models (-2.26, p < 0.01) analyses. The latent class model with three distinct subgroups (class 1: stable and gradual decline, class 2: intermediate and late decline, and class 3: lowest and irregular) performed best in the posterior classification, 42.67% (n = 559), 21.45% (n = 281), 35.88% (n = 470) were classified as class 1, class 2, and class 3. In the heterogeneous linear mixed model, the regression coefficient per one allele dose of rs6859 - A risk allele was significantly associated with MMSE class 1 and class 2 memberships and related decline; Class 1 (-2.28, 95% CI: -4.05, -0.50, p < 0.05), Class 2 (-5.56, 95% CI: -9.61, -1.51, p < 0.01) and Class 3 (-0.37, 95% CI: -1.62, 0.87, p = 0.55). CONCLUSIONS This study found statistical evidence supporting the classification of three latent subclass groups representing complex MMSE trajectories in the ADNI cohort. The SNP rs6859 can be suggested as a candidate genetic predictor of variation in modeling MMSE trajectory, as well as for identifying latent classes with higher baseline MMSE. Functional studies may help further elucidate this relationship.
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Affiliation(s)
- Aravind Lathika Rajendrakumar
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27708-0408, USA
| | - Konstantin G Arbeev
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27708-0408, USA.
| | - Olivia Bagley
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27708-0408, USA
| | - Anatoliy I Yashin
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27708-0408, USA
| | - Svetlana Ukraintseva
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27708-0408, USA
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10
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Jardim NYV, Bento-Torres NVO, Tomás AM, da Costa VO, Bento-Torres J, Picanço-Diniz CW. Unexpected cognitive similarities between older adults and young people: Scores variability and cognitive performances. Arch Gerontol Geriatr 2024; 117:105206. [PMID: 37742393 DOI: 10.1016/j.archger.2023.105206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 09/13/2023] [Accepted: 09/17/2023] [Indexed: 09/26/2023]
Abstract
BACKGROUND Increased interindividual variability in cognitive performance during aging has been proposed as an indicator of cognitive reserve. OBJECTIVE To determine if interindividual variability performance in episodic memory (PAL), working memory (SWM), reaction time (RTI), and sustained attention (RVP) could differentiate clusters of differential cognitive performance in healthy young and older adults and search for cognitive tests that most contribute to these differential performances. METHODS We employed hierarchical cluster and canonical discriminant function analyses of cognitive scores using the Cambridge Neuropsychological Test Automated Battery (CANTAB) to identify cognitive variability in older and young adults using the coefficient of variability of cognitive performances between and within groups. We also analyzed potential influences of age, education, and physical activity. RESULTS Cluster analysis distinguished groups with differential cognitive performance and correlation analysis revealed coefficient of variability and cognitive performance associations. The greater the coefficient of variability the poorer was cognitive performance in RTI but not in PAL and SWM. Older adults showed diverse trajectories of cognitive decline, and better education or higher percentage of physically active individuals exhibited better cognitive performance in both older and young adults. CONCLUSION PAL and SWM are the most sensitive tests to investigate the wide age range encompassing older and young adults. In older adults' intragroup analysis PAL showed greater discriminatory capacity, indicating its potential for clinical applications late in life. Our data underscore the importance of studying variability as a tool for early detection of subtle cognitive declines and for interpreting results that deviate from normality.
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Affiliation(s)
- Naina Yuki Vieira Jardim
- Neurodegeneration and Infection Research Laboratory, Institute of Biological Science, João de Barros Barreto University Hospital, Federal University of Pará, Belém, 66073 005, Brazil
| | - Natáli Valim Oliver Bento-Torres
- Neurodegeneration and Infection Research Laboratory, Institute of Biological Science, João de Barros Barreto University Hospital, Federal University of Pará, Belém, 66073 005, Brazil; Graduate Program in Human Movement Sciences, Federal University of Pará, Belém, 66075-110, Brazil.
| | - Alessandra Mendonça Tomás
- Neurodegeneration and Infection Research Laboratory, Institute of Biological Science, João de Barros Barreto University Hospital, Federal University of Pará, Belém, 66073 005, Brazil
| | - Victor Oliveira da Costa
- Neurodegeneration and Infection Research Laboratory, Institute of Biological Science, João de Barros Barreto University Hospital, Federal University of Pará, Belém, 66073 005, Brazil
| | - João Bento-Torres
- Neurodegeneration and Infection Research Laboratory, Institute of Biological Science, João de Barros Barreto University Hospital, Federal University of Pará, Belém, 66073 005, Brazil; Graduate Program in Human Movement Sciences, Federal University of Pará, Belém, 66075-110, Brazil
| | - Cristovam Wanderley Picanço-Diniz
- Neurodegeneration and Infection Research Laboratory, Institute of Biological Science, João de Barros Barreto University Hospital, Federal University of Pará, Belém, 66073 005, Brazil
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11
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Nicolini P, Malfatto G, Lucchi T. Heart Rate Variability and Cognition: A Narrative Systematic Review of Longitudinal Studies. J Clin Med 2024; 13:280. [PMID: 38202287 PMCID: PMC10780278 DOI: 10.3390/jcm13010280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 12/23/2023] [Accepted: 12/27/2023] [Indexed: 01/12/2024] Open
Abstract
BACKGROUND Heart rate variability (HRV) is a reliable and convenient method to assess autonomic function. Cross-sectional studies have established a link between HRV and cognition. Longitudinal studies are an emerging area of research with important clinical implications in terms of the predictive value of HRV for future cognition and in terms of the potential causal relationship between HRV and cognition. However, they have not yet been the objective of a systematic review. Therefore, the aim of this systematic review was to investigate the association between HRV and cognition in longitudinal studies. METHODS The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The Embase, PsycINFO and PubMed databases were searched from the earliest available date to 26 June 2023. Studies were included if they involved adult human subjects and evaluated the longitudinal association between HRV and cognition. The risk of bias was assessed with the Newcastle-Ottawa Scale for Cohort Studies. The results were presented narratively. RESULTS Of 14,359 records screened, 12 studies were included in this systematic review, with a total of 24,390 participants. Two thirds of the studies were published from 2020 onwards. All studies found a longitudinal relationship between HRV and cognition. There was a consistent association between higher parasympathetic nervous system (PNS) activity and better cognition, and some association between higher sympathetic nervous system activity and worse cognition. Also, higher PNS activity persistently predicted better executive functioning, while data on episodic memory and language were more scant and/or controversial. CONCLUSIONS Our results support the role of HRV as a biomarker of future cognition and, potentially, as a therapeutic target to improve cognition. They will need confirmation by further, more comprehensive studies also including unequivocal non-HRV sympathetic measures and meta-analyses.
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Affiliation(s)
- Paola Nicolini
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Geriatric Unit, Internal Medicine Department, 20122 Milan, Italy;
| | - Gabriella Malfatto
- Istituto Auxologico Italiano IRCCS, Department of Cardiovascular, Neural and Metabolic Sciences, Ospedale San Luca, 20149 Milan, Italy;
| | - Tiziano Lucchi
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Geriatric Unit, Internal Medicine Department, 20122 Milan, Italy;
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12
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Yuan Y, Peng C, Burr JA, Lapane KL. Frailty, cognitive impairment, and depressive symptoms in Chinese older adults: an eight-year multi-trajectory analysis. BMC Geriatr 2023; 23:843. [PMID: 38087208 PMCID: PMC10717397 DOI: 10.1186/s12877-023-04554-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 12/01/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Frailty, cognitive impairment, and depressive symptoms are closely interrelated conditions in the aging population. However, limited research has longitudinally analyzed the concurrent trajectories of these three prominent conditions in older adults in China. This study aimed to explore the eight-year trajectories of frailty, cognitive impairment, and depressive symptoms, and to identify individual-level and structural-level factors associated with the trajectories. METHODS Four waves of data from the China Health and Retirement Longitudinal Study (2011-2018) were used to identify 6,106 eligible older adults. The main measures included frailty by the frailty index constructed using 30 indicators, cognitive impairment by the summary score of immediate and delayed word recall, figure drawing, serial subtraction, and orientation, and depressive symptoms by the Center for Epidemiologic Studies Depression Scale. Multi-trajectory models identified the trajectories of frailty, cognitive impairment, and depressive symptoms over time. Multinomial logistic regression was employed to estimate the associations between individual-level capital factors and one structural factor (hukou and geographic residency) with the identified trajectories, adjusting for demographic characteristics. RESULTS Four trajectories emerged: (1) worsening frailty, worsening cognitive impairment, depression (14.0%); (2) declining pre-frailty, declining cognition, borderline depression (20.0%); (3) pre-frailty, worsening cognitive impairment, no depression (29.3%); and (4) physically robust, declining cognition, no depression (36.7%). Using the "physically robust, declining cognition, no depression" as the reference, not working, no social activity participant, worse childhood family financial situation, and poorer adult health were most strongly associated with the "worsening frailty, worsening cognitive impairment, depression" trajectory; worse health during childhood had the highest association with the "declining pre-frailty, declining cognition, borderline depression" trajectory; less education, lower household consumption, and rural hukou had the greatest association with the increased likelihood of the "pre-frailty, worsening cognitive impairment, no depression" trajectory. CONCLUSIONS Findings could inform the understanding of the interrelationship of frailty, cognitive impairment, and depressive symptoms in older adults in China and may help practitioners detect adults at risk for adverse trajectories to implement strategies for proper care.
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Affiliation(s)
- Yiyang Yuan
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, 368 Plantation Street, 01605, Worcester, MA, USA.
| | - Changmin Peng
- Department of Gerontology, University of Massachusetts Boston, Boston, MA, USA
| | - Jeffrey A Burr
- Department of Gerontology, University of Massachusetts Boston, Boston, MA, USA
| | - Kate L Lapane
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, 368 Plantation Street, 01605, Worcester, MA, USA
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13
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Du L, Hermann BP, Jonaitis EM, Cody KA, Rivera-Rivera L, Rowley H, Field A, Eisenmenger L, Christian BT, Betthauser TJ, Larget B, Chappell R, Janelidze S, Hansson O, Johnson SC, Langhough R. Harnessing cognitive trajectory clusterings to examine subclinical decline risk factors. Brain Commun 2023; 5:fcad333. [PMID: 38107504 PMCID: PMC10724051 DOI: 10.1093/braincomms/fcad333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 10/23/2023] [Accepted: 11/30/2023] [Indexed: 12/19/2023] Open
Abstract
Cognitive decline in Alzheimer's disease and other dementias typically begins long before clinical impairment. Identifying people experiencing subclinical decline may facilitate earlier intervention. This study developed cognitive trajectory clusters using longitudinally based random slope and change point parameter estimates from a Preclinical Alzheimer's disease Cognitive Composite and examined how baseline and most recently available clinical/health-related characteristics, cognitive statuses and biomarkers for Alzheimer's disease and vascular disease varied across these cognitive clusters. Data were drawn from the Wisconsin Registry for Alzheimer's Prevention, a longitudinal cohort study of adults from late midlife, enriched for a parental history of Alzheimer's disease and without dementia at baseline. Participants who were cognitively unimpaired at the baseline visit with ≥3 cognitive visits were included in trajectory modelling (n = 1068). The following biomarker data were available for subsets: positron emission tomography amyloid (amyloid: n = 367; [11C]Pittsburgh compound B (PiB): global PiB distribution volume ratio); positron emission tomography tau (tau: n = 321; [18F]MK-6240: primary regions of interest meta-temporal composite); MRI neurodegeneration (neurodegeneration: n = 581; hippocampal volume and global brain atrophy); T2 fluid-attenuated inversion recovery MRI white matter ischaemic lesion volumes (vascular: white matter hyperintensities; n = 419); and plasma pTau217 (n = 165). Posterior median estimate person-level change points, slopes' pre- and post-change point and estimated outcome (intercepts) at change point for cognitive composite were extracted from Bayesian Bent-Line Regression modelling and used to characterize cognitive trajectory groups (K-means clustering). A common method was used to identify amyloid/tau/neurodegeneration/vascular biomarker thresholds. We compared demographics, last visit cognitive status, health-related factors and amyloid/tau/neurodegeneration/vascular biomarkers across the cognitive groups using ANOVA, Kruskal-Wallis, χ2, and Fisher's exact tests. Mean (standard deviation) baseline and last cognitive assessment ages were 58.4 (6.4) and 66.6 (6.6) years, respectively. Cluster analysis identified three cognitive trajectory groups representing steep, n = 77 (7.2%); intermediate, n = 446 (41.8%); and minimal, n = 545 (51.0%) cognitive decline. The steep decline group was older, had more females, APOE e4 carriers and mild cognitive impairment/dementia at last visit; it also showed worse self-reported general health-related and vascular risk factors and higher amyloid, tau, neurodegeneration and white matter hyperintensity positive proportions at last visit. Subtle cognitive decline was consistently evident in the steep decline group and was associated with generally worse health. In addition, cognitive trajectory groups differed on aetiology-informative biomarkers and risk factors, suggesting an intimate link between preclinical cognitive patterns and amyloid/tau/neurodegeneration/vascular biomarker differences in late middle-aged adults. The result explains some of the heterogeneity in cognitive performance within cognitively unimpaired late middle-aged adults.
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Affiliation(s)
- Lianlian Du
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Bruce P Hermann
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Neurology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53705, USA
| | - Erin M Jonaitis
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Karly Alex Cody
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Leonardo Rivera-Rivera
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53705, USA
| | - Howard Rowley
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Aaron Field
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Laura Eisenmenger
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Bradley T Christian
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53705, USA
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Tobey J Betthauser
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Bret Larget
- Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Rick Chappell
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA
| | | | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, Lund 205 02, Sweden
| | - Sterling C Johnson
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Rebecca Langhough
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
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14
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Lim S, Yoo E, Hong I, Park JH. Age-specific findings on lifestyle and trajectories of cognitive function from the Korean Longitudinal Study of Aging. Epidemiol Health 2023; 45:e2023098. [PMID: 37946412 PMCID: PMC10876444 DOI: 10.4178/epih.e2023098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 10/15/2023] [Indexed: 11/12/2023] Open
Abstract
OBJECTIVES Few longitudinal studies have explored age-related differences in the relationship between lifestyle factors and cognitive decline. This study investigated lifestyle factors at baseline that slow the longitudinal rate of cognitive decline in young-old (55-64 years), middle-old (65-74 years), and old-old (75+ years) individuals. METHODS We conducted an 11-year follow-up that included 6,189 older adults from the Korean Longitudinal Study of Aging, which is a cohort study of community-dwelling older Koreans. Lifestyle factors, including physical activity, social activity (SA), smoking, and alcohol consumption were assessed at baseline. Cognitive function was measured at 2-year intervals over 11 years. Latent growth modeling and multi-group analysis were performed. RESULTS The influence of lifestyle factors on the rate of cognitive decline differed by age. Smoking at baseline (-0.05; 95% confidence interval [CI], -0.11 to -0.00, per study wave) accelerated cognitive decline in young-old individuals, whereas frequent participation in SA at baseline (0.02; 95% CI, 0.01 to 0.03, per study wave) decelerated cognitive decline in middle-old individuals. None of the lifestyle factors in this study decelerated cognitive decline in old-old individuals. CONCLUSIONS Cognitive strategies based on modifiable lifestyle factors such as smoking cessation in young-old individuals and frequent SA participation in middle-old age individuals may have great potential for preventing cognitive decline. Because the influence of lifestyle factors varied by age group, age-specific approaches are recommended to promote cognitive health.
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Affiliation(s)
- Seungju Lim
- Department of Occupational Therapy, Graduate School, Yonsei University, Wonju,
Korea
| | - Eunyoung Yoo
- Department of Occupational Therapy, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju,
Korea
| | - Ickpyo Hong
- Department of Occupational Therapy, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju,
Korea
| | - Ji-Hyuk Park
- Department of Occupational Therapy, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju,
Korea
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15
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Sarant J, Lemke U, Giroud N, Scherpiet S, Weinstein B. Promoting hearing and cognitive health in audiologic rehabilitation for the well-being of older adults. Int J Audiol 2023:1-11. [PMID: 37850919 DOI: 10.1080/14992027.2023.2260099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 09/12/2023] [Indexed: 10/19/2023]
Abstract
OBJECTIVE With our aging population, an increasing number of older adults with hearing loss have cognitive decline. Hearing care practitioners have an important role in supporting healthy aging and should be knowledgeable about cognitive decline and associated management strategies to maximize successful hearing intervention. METHODS A review of current research and expert opinion. RESULTS This article outlines the association between hearing loss and cognitive decline/dementia, hypothesized mechanisms underlying this, and considers current research into the effects of hearing intervention on cognitive decline. Cognition into old age, cognitive impairment, dementia, and how to recognize cognitive decline that is not part of normal aging are described. Screening of older asymptomatic adults for cognitive decline and practical suggestions for the delivery of person-centered hearing care are discussed. Holistic management goals, personhood, and person-centered care in hearing care management are considered for older adults with normal cognitive aging through to dementia. A case study illustrates important skills and potential management methods. Prevention strategies for managing hearing and cognitive health and function through to older age, and strategies to maximize successful hearing aid use are provided. CONCLUSION This article provides evidence-based recommendations for hearing care professionals supporting older clients to maximize well-being through the cognitive trajectory.
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Affiliation(s)
- Julia Sarant
- Department of Audiology and Speech Pathology, The University of Melbourne, Melbourne, Victoria, Australia
| | | | - Nathalie Giroud
- Zurich Center for Linguistics, University of Zurich, Zurich, Switzerland
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16
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Westrick AC, Langa KM, Eastman M, Ospina-Romero M, Mullins MA, Kobayashi LC. Functional aging trajectories of older cancer survivors: a latent growth analysis of the US Health and Retirement Study. J Cancer Surviv 2023; 17:1499-1509. [PMID: 35218520 PMCID: PMC9411262 DOI: 10.1007/s11764-022-01185-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 02/09/2022] [Indexed: 11/28/2022]
Abstract
PURPOSE We aimed to identify prototypical functional aging trajectories of US cancer survivors aged 50 and older, overall and stratified by sociodemographic and health-related characteristics. METHODS Data were from 2986 survivors of a first incident cancer diagnosis (except non-melanoma skin cancer) after age 50 in the population representative U.S. Health and Retirement Study from 1998-2016. Cancer diagnoses, episodic memory function, and activity of daily living (ADL) limitations were assessed at biennial study interviews. Using time of cancer diagnosis as the baseline, we used group-based trajectory modeling to identify trajectories of memory function and ADL limitations following diagnosis. RESULTS We identified five memory loss trajectories (high: 8.4%; medium-high: 18.3%; medium-low: 21.5%; low: 25.5%; and, very low: 26.2%), and four ADL limitation trajectories (high/increasing limitations: 18.7%; medium limitations: 18.7%; low limitations: 8.14%; no limitations: 60.0). The high memory loss and high/increasing ADL limitation trajectories were both characterized by older age, being female (52% for memory, 58.9% for ADL), having lower pre-cancer memory scores, and a higher prevalence of pre-cancer comorbidities including stroke (30.9% for memory and 29.7% for ADL), hypertension (64.7% for memory and 69.8 for ADL), and depressive symptoms. In joint analyses, we found that generally those with higher memory were more likely to have fewer ADL limitations and vice versa. CONCLUSION Older cancer survivors experience heterogeneous trajectories of functional aging that are largely characterized by comorbidities prior to diagnosis. IMPLICATION FOR CANCER SURVIVORS Results can help identify older cancer survivors at increased risk for accelerated functional decline.
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Affiliation(s)
- Ashly C Westrick
- Center for Social Epidemiology and Population Health, Department of Epidemiology, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI, 48109, USA.
| | - Kenneth M Langa
- Institute for Healthcare Policy and Innovations, University of Michigan, Ann Arbor, Michigan, USA
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, USA
- Institute for Social Research, University of Michigan, Ann Arbor, Michigan, USA
- Veterans Affairs Center for Clinical Management Research, Ann Arbor, Michigan, USA
| | - Marisa Eastman
- Center for Social Epidemiology and Population Health, Department of Epidemiology, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI, 48109, USA
| | - Monica Ospina-Romero
- Department of Pathology and Laboratory Medicine, University of Wisconsin, Ann Arbor, USA
| | - Megan A Mullins
- Center for Improving Patient and Population Health, University of Michigan, Ann Arbor, MI, USA
- Cancer Control and Population Sciences Program, Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA
| | - Lindsay C Kobayashi
- Center for Social Epidemiology and Population Health, Department of Epidemiology, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI, 48109, USA
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17
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Lobo E, Lobo A, Gracia-García P, López-Antón R, Saz P, De la Cámara C. Sex Differences in Longitudinal Trajectories of Cognitive Aging in Zaragoza, Spain. Am J Geriatr Psychiatry 2023; 31:796-807. [PMID: 37169710 DOI: 10.1016/j.jagp.2023.04.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 04/19/2023] [Accepted: 04/19/2023] [Indexed: 05/13/2023]
Abstract
OBJECTIVES The objective of this study was to document the longitudinal trajectories of cognitive aging in a sample of cognitively healthy subjects of 55 years or older. The following differences between men and women were hypothesized: 1) in the cognitive loss through aging, 2) in the distinct trajectories identified; and 3) in the predictors associated with the identified trajectories. DESIGN AND SETTING A 4-wave, population-based study in Zaragoza, Spain (1994-2006). PARTICIPANTS A total of 2,403 individuals aged 55+ years, cognitively healthy at baseline. MEASUREMENTS All participants had at least three measurements with the Mini-Mental State Examination (MMSE). Validated Spanish versions of international instruments were used for assessment. Random effects linear panel regression model for analyzing differences by sex in MMSE scores through aging were performed, and growth mixture models (GMM) applied independently for each sex for modeling the longitudinal cognitive trajectories. RESULTS Women showed lower mean MMSE scores in all phases and significantly higher loss in the MMSE from phases 2 to 3 and 3 to 4. The best fitting age-adjusted model of the cognitive trajectories was a 4-class GMM in men and a 3-class in women. Education was a predictor of cognitive trajectories in both men and women. Dependence on iADLs and alcohol status were predictors only for men, and depression and diabetes only for women. CONCLUSIONS The identified differences by sex in cognitive trajectories and their associated factors suggest that men and women may require a different strategy when addressing cognitive aging.
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Affiliation(s)
- Elena Lobo
- Department of Preventive Medicine and Public Health (EL), Universidad de Zaragoza, Zaragoza, Spain; Instituto de Investigación Sanitaria de Aragón (IIS Aragón) (EL, AL, RLA, PS, PGG, CDC) Zaragoza, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM) (EL PGG, RLA, CDC), Ministry of Science and Innovation, Madrid, Spain
| | - Antonio Lobo
- Instituto de Investigación Sanitaria de Aragón (IIS Aragón) (EL, AL, RLA, PS, PGG, CDC) Zaragoza, Spain; Department of Medicine and Psychiatry (AL, PGG, PS, CDC), Universidad de Zaragoza, Zaragoza, Spain.
| | - Patricia Gracia-García
- Instituto de Investigación Sanitaria de Aragón (IIS Aragón) (EL, AL, RLA, PS, PGG, CDC) Zaragoza, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM) (EL PGG, RLA, CDC), Ministry of Science and Innovation, Madrid, Spain; Department of Medicine and Psychiatry (AL, PGG, PS, CDC), Universidad de Zaragoza, Zaragoza, Spain; Psychiatry Service (PGG), Hospital Universitario Miguel Servet, Zaragoza, Spain
| | - Raúl López-Antón
- Instituto de Investigación Sanitaria de Aragón (IIS Aragón) (EL, AL, RLA, PS, PGG, CDC) Zaragoza, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM) (EL PGG, RLA, CDC), Ministry of Science and Innovation, Madrid, Spain; Department of Sociology and Psychology (RLA), Universidad de Zaragoza, Zaragoza, Spain
| | - Pedro Saz
- Instituto de Investigación Sanitaria de Aragón (IIS Aragón) (EL, AL, RLA, PS, PGG, CDC) Zaragoza, Spain; Department of Medicine and Psychiatry (AL, PGG, PS, CDC), Universidad de Zaragoza, Zaragoza, Spain
| | - Concepción De la Cámara
- Instituto de Investigación Sanitaria de Aragón (IIS Aragón) (EL, AL, RLA, PS, PGG, CDC) Zaragoza, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM) (EL PGG, RLA, CDC), Ministry of Science and Innovation, Madrid, Spain; Department of Medicine and Psychiatry (AL, PGG, PS, CDC), Universidad de Zaragoza, Zaragoza, Spain; Psychiatry Service (CDC), Hospital Clínico Universitario, Zaragoza, Spain
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18
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Rodrigues EA, Moreno S. Conceptualizing healthy cognitive aging: the role of time and variability. Front Hum Neurosci 2023; 17:1240630. [PMID: 37780962 PMCID: PMC10533921 DOI: 10.3389/fnhum.2023.1240630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 08/28/2023] [Indexed: 10/03/2023] Open
Abstract
The interest in healthy cognitive aging (HCA) has increased substantially over the past decade. Researchers are interested in exploring how health can be promoted and cognitive decline mitigated when pathology is not present. Identifying the necessary strategies is crucial as the gradual accumulation of small declines can lead to negative effects on quality of life over time. However, the conceptualization of HCA is not agreed upon. In fact, authors often turn to the use of traditional pathology screeners in the context of HCA because of their clear threshold results and their wide use in the different fields. This leads to the assumption that individuals are either cognitively unhealthy and therefore may have some form of dementia or are dementia-free and cognitively healthy. We believe that this view is an overly simplistic approach to the understanding of the aging process. In this work, we explore how HCA has been defined and conceptualized within the different fields. We further discuss how time and variability are key concepts that are often missing when studying HCA and propose a definition that aims to unify the findings from the multidisciplinary research that studies HCA and simplify the translation of knowledge. Incorporating these two novel dimensions to the study of HCA has already been proposed methodologically but has yet been discussed at the conceptual level. We believe that the proposed new approach will allow the identification of individual factors that cause changes in cognitive health and will help build new cognitive health strategies and mitigate further declines.
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Affiliation(s)
- Emma A. Rodrigues
- School of Interactive Arts and Technology, Simon Fraser University, Surrey, BC, Canada
| | - Sylvain Moreno
- School of Interactive Arts and Technology, Simon Fraser University, Surrey, BC, Canada
- Circle Innovation, Vancouver, BC, Canada
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19
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Moreno S, Rodrigues E, Farzan F. The theory of orchid and dandelion offers a new subtyping framework for cognitive aging. Aging (Albany NY) 2023; 15:6627-6628. [PMID: 37517086 PMCID: PMC10415542 DOI: 10.18632/aging.204955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 04/24/2023] [Indexed: 08/01/2023]
Affiliation(s)
- Sylvain Moreno
- School of Interactive Arts and Technology, Simon Fraser University, Surrey, BC, Canada
| | - Emma Rodrigues
- School of Interactive Arts and Technology, Simon Fraser University, Surrey, BC, Canada
| | - Faranak Farzan
- School of Interactive Arts and Technology, Simon Fraser University, Surrey, BC, Canada
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20
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Corley J, Conte F, Harris SE, Taylor AM, Redmond P, Russ TC, Deary IJ, Cox SR. Predictors of longitudinal cognitive ageing from age 70 to 82 including APOE e4 status, early-life and lifestyle factors: the Lothian Birth Cohort 1936. Mol Psychiatry 2023; 28:1256-1271. [PMID: 36481934 PMCID: PMC10005946 DOI: 10.1038/s41380-022-01900-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 11/17/2022] [Accepted: 11/21/2022] [Indexed: 12/13/2022]
Abstract
Discovering why some people's cognitive abilities decline more than others is a key challenge for cognitive ageing research. The most effective strategy may be to address multiple risk factors from across the life-course simultaneously in relation to robust longitudinal cognitive data. We conducted a 12-year follow-up of 1091 (at age 70) men and women from the longitudinal Lothian Birth Cohort 1936 study. Comprehensive repeated cognitive measures of visuospatial ability, processing speed, memory, verbal ability, and a general cognitive factor were collected over five assessments (age 70, 73, 76, 79, and 82 years) and analysed using multivariate latent growth curve modelling. Fifteen life-course variables were used to predict variation in cognitive ability levels at age 70 and cognitive slopes from age 70 to 82. Only APOE e4 carrier status was found to be reliably informative of general- and domain-specific cognitive decline, despite there being many life-course correlates of cognitive level at age 70. APOE e4 carriers had significantly steeper slopes across all three fluid cognitive domains compared with non-carriers, especially for memory (β = -0.234, p < 0.001) and general cognitive function (β = -0.246, p < 0.001), denoting a widening gap in cognitive functioning with increasing age. Our findings suggest that when many other candidate predictors of cognitive ageing slope are entered en masse, their unique contributions account for relatively small proportions of variance, beyond variation in APOE e4 status. We conclude that APOE e4 status is important for identifying those at greater risk for accelerated cognitive ageing, even among ostensibly healthy individuals.
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Affiliation(s)
- Janie Corley
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK.
| | - Federica Conte
- Department of Psychology, University of Milano-Bicocca, Milan, Italy
| | - Sarah E Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Adele M Taylor
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Paul Redmond
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Tom C Russ
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Simon R Cox
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
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21
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Wu Z, Woods RL, Chong TT, Orchard SG, Shah RC, Wolfe R, Storey E, Sheets KM, Murray AM, McNeil JJ, Ryan J. Grip strength, gait speed, and trajectories of cognitive function in community-dwelling older adults: A prospective study. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12388. [PMID: 36815873 PMCID: PMC9927855 DOI: 10.1002/dad2.12388] [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: 05/24/2022] [Revised: 10/08/2022] [Accepted: 11/22/2022] [Indexed: 02/16/2023]
Abstract
Introduction This study investigated whether grip strength and gait speed predict cognitive aging trajectories and examined potential sex-specific associations. Methods Community-dwelling older adults (n = 19,114) were followed for up to 7 years, with regular assessment of global function, episodic memory, psychomotor speed, and executive function. Group-based multi-trajectory modeling identified joint cognitive trajectories. Multinomial logistic regression examined the association of grip strength and gait speed at baseline with cognitive trajectories. Results High performers (14.3%, n = 2298) and low performers (4.0%, n = 642) were compared to the average performers (21.8%, n = 3492). Grip strength and gait speed were positively associated with high performance and negatively with low performance (P-values < 0.01). The association between grip strength and high performance was stronger in women (interaction P < 0.001), while gait speed was a stronger predictor of low performance in men (interaction P < 0.05). Discussion Grip strength and gait speed are associated with cognitive trajectories in older age, but with sex differences. Highlights There is inter-individual variability in late-life cognitive trajectories.Grip strength and gait speed predicted cognitive trajectories in older age.However, sex-specific associations were identified.In women, grip strength strongly predicted high, compared to average, trajectory.In men, gait speed was a stronger predictor of low cognitive performance trajectory.
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Affiliation(s)
- Zimu Wu
- School of Public Health and Preventive MedicineMonash UniversityMelbourneVictoriaAustralia
| | - Robyn L. Woods
- School of Public Health and Preventive MedicineMonash UniversityMelbourneVictoriaAustralia
| | - Trevor T.‐J. Chong
- Turner Institute for Brain and Mental HealthMonash UniversityMelbourneVictoriaAustralia,Department of NeurologyAlfred HealthMelbourneVictoriaAustralia,Department of Clinical NeurosciencesSt Vincent's HospitalMelbourneVictoriaAustralia
| | - Suzanne G. Orchard
- School of Public Health and Preventive MedicineMonash UniversityMelbourneVictoriaAustralia
| | - Raj C. Shah
- Department of Family Medicine and Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
| | - Rory Wolfe
- School of Public Health and Preventive MedicineMonash UniversityMelbourneVictoriaAustralia
| | - Elsdon Storey
- School of Public Health and Preventive MedicineMonash UniversityMelbourneVictoriaAustralia
| | - Kerry M. Sheets
- Department of MedicineDivision of Geriatric and Palliative MedicineHennepin HealthcareMinneapolisMinnesotaUSA
| | - Anne M. Murray
- Berman Center for Outcomes and Clinical ResearchMinneapolisMinnesotaUSA
| | - John J. McNeil
- School of Public Health and Preventive MedicineMonash UniversityMelbourneVictoriaAustralia
| | - Joanne Ryan
- School of Public Health and Preventive MedicineMonash UniversityMelbourneVictoriaAustralia
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Vasiliadis HM, Pitrou I, Grenier S, Berbiche D, Hudon C. Psychological Distress, Cognition, and Functional Disability Trajectory Profiles of Aging in Primary Care Older Adults. Clin Gerontol 2023; 46:819-831. [PMID: 35387578 DOI: 10.1080/07317115.2022.2060158] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
OBJECTIVES To identify profiles of aging by combining psychological distress, cognition and functional disability, and their associated factors. METHODS Data were drawn from the Étude sur la Santé des Aînés-Services study and included 1585 older adults. Sociodemographic, psychosocial, lifestyle and health factors were informed from structured interviews. Group-based multi-trajectory modeling and multinomial logistic regression were used to identify aging profiles and correlates. Sampling weights were applied to account for the sampling plan. RESULTS The weighted sample size was 1591. Three trajectories were identified: a favorable (79.0%), intermediate (14.5%), and severe scenario (6.5%). Factors associated with the severe scenario were older age, male gender, lower education, the presence of anxiety disorders, low physical activity, and smoking. Membership in the intermediate scenario was associated with daily hassles, physical disorders, anxiety and depression, antidepressant/psychotherapy use, low physical activity, and no alcohol use. High social support was protective against less favorable profiles. CONCLUSIONS Symptoms of anxiety and depression and high burden of physical disorders were associated with less favorable trajectories. Modifiable lifestyle factors have a significant effect on healthy aging. CLINICAL IMPLICATIONS Assessment and management of anxio-depressive symptoms are important in older adults. Clinical interventions including access to psychotherapy and promotion of healthier lifestyles should be considered.
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Affiliation(s)
- Helen-Maria Vasiliadis
- Faculty of Medicine and Health Sciences, University of Sherbrooke, Charles-Le Moyne Research Center, Longueuil, Quebec, Canada
| | - Isabelle Pitrou
- Faculty of Medicine and Health Sciences, University of Sherbrooke, Charles-Le Moyne Research Center, Longueuil, Quebec, Canada
| | - Sébastien Grenier
- Department of Psychology, University of Montreal, Centre de recherche de l'Institut universitaire de gériatrie de Montréal (CRIUGM), Montréal, Quebec, Canada
| | - Djamal Berbiche
- Faculty of Medicine and Health Sciences, University of Sherbrooke, Charles-Le Moyne Research Center, Longueuil, Quebec, Canada
| | - Carol Hudon
- School of Psychology (Laval University), CERVO Brain Research Centre, and VITAM Research Centre, Quebec, Quebec, Canada
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Zhang B, Hu M, Sun Y, Lin Y, Zhu C. Associations Between the Prevalence, Treatment, Control of Hypertension and Cognitive Trajectories Among Chinese Middle-Aged and Older Adults. Am J Geriatr Psychiatry 2022; 30:1123-1134. [PMID: 35466016 DOI: 10.1016/j.jagp.2022.03.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 03/26/2022] [Accepted: 03/27/2022] [Indexed: 01/25/2023]
Abstract
OBJECTIVE To investigate the associations between the prevalence, treatment, control of hypertension, and trajectories of cognitive performance among Chinese middle-aged and older adults. DESIGN An 8-year longitudinal study. SETTING China. PARTICIPANTS Chinese middle-aged and older adults. MEASUREMENTS Data from the China Health and Retirement Longitudinal Study were utilized. Group-based trajectory modeling was performed to identify heterogeneous trajectories of episodic memory and executive function. Multinomial logistic regression models were established to examine the relationships between hypertension status and cognitive trajectories, stratified by sex. RESULTS Three episodic memory trajectories and four executive function trajectories were identified in males and females. Hypertension prevalence was associated with worse episodic memory and executive function trajectories in females. Compared with treated hypertensives, untreated hypertensives were more likely to have worse executive function trajectories, both in males and females. Among male treated hypertensives, those with uncontrolled blood pressure (BP) had worse episodic memory trajectories compared with their counterparts with controlled at standard targets, while females with uncontrolled BP demonstrated worse executive function trajectories compared with females controlled at standard targets. There was basically no significant difference in cognitive trajectory memberships between individuals with controlled hypertension corresponding to intensive or standard BP targets. CONCLUSIONS The prevalence of hypertension was associated with worse cognitive trajectories, and the treatment and control of hypertension were related to more favorable cognitive trajectories. Intensive BP control target was not associated with additional benefit beyond the recognized protective effect of standard BP targets on cognitive trajectories.
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Affiliation(s)
- Baiyang Zhang
- Department of epidemiology and health statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Meijing Hu
- Department of epidemiology and health statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yue Sun
- Department of epidemiology and health statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yidie Lin
- Department of epidemiology and health statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Cairong Zhu
- Department of epidemiology and health statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
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What Do We Know about Social and Non-Social Factors Influencing the Pathway from Cognitive Health to Dementia? A Systematic Review of Reviews. Brain Sci 2022; 12:brainsci12091214. [PMID: 36138950 PMCID: PMC9497077 DOI: 10.3390/brainsci12091214] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 09/03/2022] [Accepted: 09/05/2022] [Indexed: 11/21/2022] Open
Abstract
The heterogeneous and multi-factorial nature of dementia requires the consideration of all health aspects when predicting the risk of its development and planning strategies for its prevention. This systematic review of reviews provides a comprehensive synthesis of those factors associated with cognition in the context of dementia, identifying the role of social aspects and evidencing knowledge gaps in this area of research. Systematic reviews and meta-analyses from 2009–2021 were searched for within Medline, PsycINFO, CINAHL Complete, Cochrane, and Epistemonikos. Reviewers independently screened, reviewed, and assessed the records, following the PRISMA-2020 guidelines. From 314 included studies, 624 cognitive-related factors were identified, most of them risk factors (61.2%), mainly belonging to the group of ‘somatic comorbidities’ (cardiovascular disease and diabetes) and ‘genetic predispositions’. The protective factors (20%) were mainly related to lifestyle, pointing to the Mediterranean diet, regular physical activity, and cognitively stimulating activities. Social factors constituted 9.6% of all identified factors. Research on biological and medical factors dominates the reviewed literature. Greater social support and frequent contact may confer some protection against cognitive decline and dementia by delaying its onset or reducing the overall risk; however, overall, our findings are inconsistent. Further research is needed in the fields of lifestyle, psychology, social health, and the protective factors against cognitive decline and dementia.
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Han C, An J, Chan P. Effects of cognitive ageing trajectories on multiple adverse outcomes among Chinese community-dwelling elderly population. BMC Geriatr 2022; 22:692. [PMID: 35996087 PMCID: PMC9396872 DOI: 10.1186/s12877-022-03387-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 08/02/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Whether cognitive ageing trajectory is related to common functional deficits independent of initial cognitive function remains inconclusive. We aimed to explore the adverse health effect and potential predictive factors of distinct cognitive trajectories among Chinese older adults. METHODS Three thousand five hundred eighty-one community-dwelling older adults who completed three consecutive cognitive function examinations with the Mini-Mental State Examination (MMSE) over 5 years and were without cognitive impairment at enrollment were included. A group-based trajectory model was used to estimate cognitive ageing trajectories. Multivariable-adjusted odds ratio (OR) and 95% confidence intervals (CI) were computed with logistic regression models to identify potential baseline determinants and health effect of cognitive trajectories on various adverse outcomes. RESULTS Two distinct cognitive ageing trajectories were identified with about 5.3% of the study participants ascribed to the rapidly decreasing group. Subjects with rapidly decreasing cognition showed significantly higher odds (OR, 95%CI) of experiencing frailty (4.04, 2.77-5.86), falls (2.01, 1.05-3.70), balance impairment (4.20, 2.75-6.38), high fall risk (5.66, 2.67-11.77) based on the Tinetti total score, disability in activities of daily living (1.76, 1.19-2.56), disability in instrumental activities of daily living (1.52, 1.05-2.19), and motor cognitive risk syndrome (2.24, 1.23-3.98) compared with their steadily decreasing counterparts. Individuals with older age, low education level, no marriage, high score of rapid eye movement behavior disorders, poor physical and cognitive function at baseline were more predisposed to an accelerated cognitive decline. CONCLUSIONS Faster cognitive decline was independently associated with higher risk of multiple adverse events. Our findings put more emphasis on a routine and constant surveillance of cognitive function among community-dwelling older adults.
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Affiliation(s)
- Chao Han
- National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Jing An
- National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Piu Chan
- National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital of Capital Medical University, Beijing, China. .,Department of Neurobiology, Neurology and Geriatrics, Beijing Institute of Geriatrics, Clinical Center for Parkinson's Disease, Key Laboratories for Neurodegenerative Diseases of the Ministry of Education; Beijing Key Laboratory for Parkinson's Disease, Parkinson Disease Center of Beijing Institute for Brain Disorders, Advanced Innovative Center for Human Brain Protection, Xuanwu Hospital of Capital Medical University, 45 Changchun Road, Beijing, 100053, China.
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26
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Wu Z, Woods RL, Chong TTJ, Orchard SG, McNeil JJ, Shah RC, Wolfe R, Murray AM, Storey E, Ryan J. Potential modifiable factors associated with late-life cognitive trajectories. Front Neurol 2022; 13:950644. [PMID: 35989918 PMCID: PMC9381981 DOI: 10.3389/fneur.2022.950644] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 07/11/2022] [Indexed: 11/19/2022] Open
Abstract
Objective There is variability across individuals in cognitive aging. To investigate the associations of several modifiable factors with high and low cognitive performance. Methods Data came from 17,724 community-dwelling individuals aged 65-98 years. Global cognition, verbal fluency, episodic memory, and psychomotor speed were assessed over up to seven years. Group-based multi-trajectory modeling identified distinct cognitive trajectories. Structural equation modeling examined the direct/indirect associations of social/behavioral factors and several chronic conditions with cognitive trajectories. Results Seven trajectory subgroups were identified. In the structural equation modeling we compared two subgroups-participants with the highest (14.2%) and lowest (4.1%) cognitive performance with the average subgroup. Lower education, never alcohol intake, and frailty directly predicted increased risk of low performance, and decreased likelihood of high performance. Hypertension (RR: 0.69, 95%CI: 0.60-0.80), obesity (RR: 0.84, 95%CI: 0.73-0.97), diabetes (RR: 0.69, 95%CI: 0.56-0.86) and depression (RR: 0.68, 95%CI: 0.54-0.85) only predicted lower likelihood of high cognitive performance, while dyslipidemia was only associated with low performance (RR: 1.30, 95%CI: 1.07-1.57). Living alone predicted increased risk of low cognitive performance and several comorbidities. Smoking did not predict cognitive trajectories but was associated with increased risk of diabetes, obesity and frailty. Findings were similar when examining the direct associations between modifiable risk factors and all seven cognitive subgroups. Conclusions Although several modifiable factors were associated with high performance, and reversely with low performance, this was not observed for obesity, hypertension and dyslipidemia. Further, health behaviors may affect cognitive function indirectly, via geriatric conditions. This indicates that strategies to promote healthy cognitive aging, may be distinct from those targeting dementia prevention.
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Affiliation(s)
- Zimu Wu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Robyn L. Woods
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Trevor T. -J. Chong
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia,Department of Neurology, Alfred Health, Melbourne, VIC, Australia,Department of Clinical Neurosciences, St Vincent's Hospital, Melbourne, VIC, Australia
| | - Suzanne G. Orchard
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - John J. McNeil
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Raj C. Shah
- Department of Family Medicine and Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, United States
| | - Rory Wolfe
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Anne M. Murray
- Berman Center for Outcomes and Clinical Research, Hennepin Healthcare Research Institute, Minneapolis, MN, United States
| | - Elsdon Storey
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Joanne Ryan
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia,*Correspondence: Joanne Ryan
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D'Amico D, Amestoy ME, Fiocco AJ. The mediating role of allostatic load in the relationship between early life adversity and cognitive function across the adult lifespan. Psychoneuroendocrinology 2022; 141:105761. [PMID: 35429700 DOI: 10.1016/j.psyneuen.2022.105761] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 03/31/2022] [Accepted: 04/03/2022] [Indexed: 01/16/2023]
Abstract
Early life adversity is consequential for poor cognitive health in mid to late-life. Early life adversity is associated with higher allostatic load, a biological indicator of physiological dysregulation due to cumulative wear-and-tear from chronic stress. Higher allostatic load is also associated with poorer cognitive function across the lifespan. To date, a paucity of research has examined allostatic load as a mechanism through which early life adversity impacts cognition in adulthood. Using cross-sectional data from the Midlife in the United States (MIDUS) Study, the objective of the current study was to investigate the mediating role of allostatic load in the relationship between early life adversity and cognitive performance (global cognition, episodic memory, executive function) among middle-aged and older adults without cognitive impairment (n = 1541, Mage=53 ± 12, 53% female). Early life adversity was measured retrospectively using the Childhood Trauma Questionnaire. Allostatic load was composed of 20 biomarker proxies of neuroendocrine, metabolic, inflammatory, and cardiovascular systems, stratified by sex. Cognitive performance was evaluated using a battery of standardized neuropsychological tests. Controlling for age, education, and race, allostatic load significantly mediated the relationship between early life adversity and global cognition (ß=-0.01, 95%CI [-0.01,-0.001]), and early life adversity and executive function (ß=-0.01, 95%CI [-0.01,-0.001]), but not episodic memory. Findings did not change after controlling for lifestyle behaviours and current depression. Consistent with the biopsychosocial lifespan model of cognitive aging, findings suggest that early life adversity may become biologically embedded over time to negatively impact cognitive function in later adulthood in a domain-specific manner.
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Affiliation(s)
- Danielle D'Amico
- Institute for Stress and Wellbeing Research, Department of Psychology, Ryerson University, Canada
| | - Maya E Amestoy
- Graduate Department of Psychological Clinical Science, University of Toronto Scarborough, Canada
| | - Alexandra J Fiocco
- Institute for Stress and Wellbeing Research, Department of Psychology, Ryerson University, Canada.
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Wu Z, Woods RL, Chong TTJ, Orchard SG, Shah RC, Wolfe R, Storey E, Sheets KM, Murray AM, McNeil JJ, Ryan J. Cognitive Trajectories in Community-Dwelling Older Adults and Incident Dementia, Disability and Death: A 10-Year Longitudinal Study. Front Med (Lausanne) 2022; 9:917254. [PMID: 35833102 PMCID: PMC9271785 DOI: 10.3389/fmed.2022.917254] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Accepted: 05/30/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectiveThe inter-individual variability in cognitive changes may be early indicators of major health events. We aimed to determine whether late-life cognitive trajectories were associated with incident dementia, persistent physical disability and all-cause mortality.MethodsData came from a cohort of older community-dwelling individuals aged 70 years or above in Australia and the United States. Global cognition, verbal fluency, episodic memory and psychomotor speed were assessed regularly at up to seven waves between 2010 and 2017. Dementia, disability in activities of daily living, and death were adjudicated between 2017 and 2020. Latent classes of cognitive trajectories over seven years were determined using group-based trajectory modeling. Multivariable logistic regression was used for the prospective associations between cognitive trajectories and these outcomes.ResultsCognitive trajectories were defined for 16,174 participants (mean age: 78.9 years; 56.7% female) who were alive and without incident dementia or disability by 2017, among which 14,655 participants were included in the association analysis. Between three and five trajectory classes were identified depending on the cognitive test. Cognitive trajectories were strongly associated with the risk of dementia. For example, compared to those in the highest-functioning trajectory, the worst performers of episodic memory had a 37-fold increased risk of dementia (95% CI: 17.23–82.64). The lowest trajectories of both global cognition and episodic memory also predicted increased mortality risk (OR: 1.80, 95% CI: 1.28–2.52; OR: 1.61, 95% CI: 1.09–2.36, respectively), while only slow psychomotor speed was marginally associated with physical disability (OR: 2.39, 95% CI: 0.99–5.77).ConclusionsIn older individuals, cognitive trajectories appear to be early indicators of clinically relevant health outcomes. Systematic cognitive assessments as part of routine geriatric evaluation may facilitate early identification and interventions for those individuals at highest risk.
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Affiliation(s)
- Zimu Wu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Robyn L. Woods
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Trevor T. J. Chong
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
- Department of Neurology, Alfred Health, Melbourne, VIC, Australia
- Department of Clinical Neurosciences, St Vincent's Hospital, Melbourne, VIC, Australia
| | - Suzanne G. Orchard
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Raj C. Shah
- Department of Family Medicine and Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, United States
| | - Rory Wolfe
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Elsdon Storey
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Kerry M. Sheets
- Division of Geriatrics and Palliative Medicine, Department of Medicine, Hennepin Healthcare, Minneapolis, MN, United States
| | - Anne M. Murray
- Berman Center for Outcomes and Clinical Research, Hennepin Healthcare Research Institute, Minneapolis, MN, United States
| | - John J. McNeil
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Joanne Ryan
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- *Correspondence: Joanne Ryan
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Ziegler DA, Anguera JA, Gallen CL, Hsu WY, Wais PE, Gazzaley A. Leveraging technology to personalize cognitive enhancement methods in aging. NATURE AGING 2022; 2:475-483. [PMID: 35873177 PMCID: PMC9302894 DOI: 10.1038/s43587-022-00237-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
As population aging advances at an increasing rate, efforts to help people maintain or improve cognitive function late in life are critical. Although some studies have shown promise, the question of whether cognitive training is an effective tool for improving general cognitive ability remains incompletely explored, and study results to date have been inconsistent. Most approaches to cognitive enhancement in older adults have taken a 'one size fits all' tack, as opposed to tailoring interventions to the specific needs of individuals. In this Perspective, we argue that modern technology has the potential to enable large-scale trials of public health interventions to enhance cognition in older adults in a personalized manner. Technology-based cognitive interventions that rely on closed-loop systems can be tailored to individuals in real time and have the potential for global testing, extending their reach to large and diverse populations of older adults. We propose that the future of cognitive enhancement in older adults will rely on harnessing new technologies in scientifically informed ways.
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Affiliation(s)
- David A. Ziegler
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
- Neuroscape, University of California San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
- Correspondence should be addressed to David A. Ziegler or Adam Gazzaley. ;
| | - Joaquin A. Anguera
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
- Neuroscape, University of California San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
| | - Courtney L. Gallen
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
- Neuroscape, University of California San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Wan-Yu Hsu
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Peter E. Wais
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
- Neuroscape, University of California San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Adam Gazzaley
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
- Neuroscape, University of California San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
- Department of Physiology, University of California San Francisco, San Francisco, CA, USA
- Correspondence should be addressed to David A. Ziegler or Adam Gazzaley. ;
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Cainelli E, Vedovelli L, Gregori D, Suppiej A, Padalino M, Cogo P, Bisiacchi P. Embrace the Complexity: Agnostic Evaluation of Children’s Neuropsychological Performances Reveals Hidden Neurodevelopment Patterns. CHILDREN 2022; 9:children9060775. [PMID: 35740712 PMCID: PMC9221792 DOI: 10.3390/children9060775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 05/02/2022] [Accepted: 05/23/2022] [Indexed: 11/16/2022]
Abstract
The most common adverse pre/perinatal events have a great impact on neurodevelopment, with avalanche effects on academic performance, occupational status, and quality of life. Although the injury process starts early, the effects may become evident much later, when life starts to pose more challenging demands. In the present work, we want to address the impact of early insults from an evolutionary perspective by performing unsupervised cluster analysis. We fed all available data, but not the group identification, into the algorithm for 114 children aged 5–10 years, with different adverse medical conditions: healthy (n = 30), premature (n = 28), neonatal hypoxic-ischemic encephalopathy (n = 28), and congenital heart disease (n = 28). We measured general intelligence and many neuropsychological domains (language, attention, memory, executive functions, and social skills). We found three emerging groups that identify children with multiple impairments (cluster 3), children with variable neuropsychological profiles but in the normal range (cluster 2), and children with adequate profiles and good performance in IQ and executive functions (cluster 1). Our analysis divided our patients by severity levels rather than by identifying specific neuropsychological phenotypes, suggesting different developmental trajectories that are characterized by good resilience to early stressful events with adequate development or by pervasive vulnerability to neurodevelopmental disorders.
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Affiliation(s)
- Elisa Cainelli
- Department of General Psychology, University of Padova, 35131 Padova, Italy;
- Correspondence:
| | - Luca Vedovelli
- Unit of Biostatistics, Epidemiology, and Public Health, Department of Cardiac, Thoracic, Vascular and Public Health Sciences, University of Padova, 35131 Padova, Italy; (L.V.); (D.G.)
| | - Dario Gregori
- Unit of Biostatistics, Epidemiology, and Public Health, Department of Cardiac, Thoracic, Vascular and Public Health Sciences, University of Padova, 35131 Padova, Italy; (L.V.); (D.G.)
| | - Agnese Suppiej
- Department of Medical Sciences, Pediatric Section, University of Ferrara, 44121 Ferrara, Italy;
| | - Massimo Padalino
- Pediatric and Congenital Cardiovascular Surgery Unit, Department of Cardiac, Thoracic, and Vascular Sciences, Padova University Hospital, 35128 Padova, Italy;
| | - Paola Cogo
- Clinica Pediatrica, Department of Medicine, University Hospital Santa Maria della Misericordia, University of Udine, 33100 Udine, Italy;
| | - Patrizia Bisiacchi
- Department of General Psychology, University of Padova, 35131 Padova, Italy;
- Padova Neuroscience Center (PNC), University of Padova, 35129 Padova, Italy
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31
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Yuan Y, Lapane KL, Tjia J, Baek J, Liu SH, Ulbricht CM. Trajectories of physical frailty and cognitive impairment in older adults in United States nursing homes. BMC Geriatr 2022; 22:339. [PMID: 35439970 PMCID: PMC9017032 DOI: 10.1186/s12877-022-03012-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 03/29/2022] [Indexed: 12/04/2022] Open
Abstract
Background U.S. nursing homes provide long-term care to over 1.2 million older adults, 60% of whom were physically frail and 68% had moderate or severe cognitive impairment. Limited research has examined the longitudinal experience of these two conditions in older nursing home residents. Methods This national longitudinal study included newly-admitted non-skilled nursing care older residents who had Minimum Data Set (MDS) 3.0 (2014–16) assessments at admission, 3 months, and 6 months (n = 266,001). Physical frailty was measured by FRAIL-NH and cognitive impairment by the Brief Interview for Mental Status. Separate sets of group-based trajectory models were fitted to identify the trajectories of physical frailty and trajectories of cognitive impairment, and to estimate the association between older residents’ characteristics at admission with each set of trajectories. A dual trajectory model was used to quantify the association between the physical frailty trajectories and cognitive impairment trajectories. Results Over the course of the first six months post-admission, five physical frailty trajectories [“Consistently Frail” (prevalence: 53.0%), “Consistently Pre-frail” (29.0%), “Worsening Frailty” (7.6%), “Improving Frailty” (5.5%), and “Consistently Robust” (4.8%)] and three cognitive impairment trajectories [“Consistently Severe Cognitive Impairment” (35.5%), “Consistently Moderate Cognitive Impairment” (31.8%), “Consistently Intact/Mild Cognitive Impairment” (32.7%)] were identified. One in five older residents simultaneously followed the trajectories of “Consistently Frail” and “Consistently Severe Cognitive Impairment”. Characteristics associated with higher odds of the “Improving Frailty”, “Worsening Frailty”, “Consistently Pre-frail” and “Consistently Frail” trajectories included greater at-admission cognitive impairment, age ≥ 85 years, admitted from acute hospitals, cardiovascular/metabolic diagnoses, neurological diagnoses, hip or other fractures, and presence of pain. Characteristics associated with higher odds of the “Consistently Moderate Cognitive Impairment” and “Consistently Severe Cognitive Impairment” included worse at-admission physical frailty, neurological diagnoses, hip fracture, and receipt of antipsychotics. Conclusions Findings provided information regarding the trajectories of physical frailty, the trajectories of cognitive impairment, the association between the two sets of trajectories, and their association with residents’ characteristics in older adults’ first six months post-admission to U.S. nursing homes. Understanding the trajectory that the residents would most likely follow may provide information to develop a comprehensive care approach tailored to their specific healthcare goals. Supplementary Information The online version contains supplementary material available at 10.1186/s12877-022-03012-8.
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Affiliation(s)
- Yiyang Yuan
- Clinical and Population Health Research PhD Program, Graduate School of Biomedical Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA. .,Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA.
| | - Kate L Lapane
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Jennifer Tjia
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Jonggyu Baek
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Shao-Hsien Liu
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Christine M Ulbricht
- Formerly: Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA.,Currently: National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
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32
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Wu Y, Jia M, Xiang C, Lin S, Jiang Z, Fang Y. Predicting the long-term cognitive trajectories using machine learning approaches: A Chinese nationwide longitudinal database. Psychiatry Res 2022; 310:114434. [PMID: 35172247 DOI: 10.1016/j.psychres.2022.114434] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 01/19/2022] [Accepted: 02/05/2022] [Indexed: 12/25/2022]
Abstract
OBJECTIVES This study aimed to explore the long-term cognitive trajectories and its' determinants, and construct prediction models for identifying high-risk populations with unfavorable cognitive trajectories. METHODS This study included 3502 older adults aged 65-105 years at their first observations in a 16-year longitudinal cohort study. Cognitive function was measured by the Chinese version Mini Mental State Examination. The heterogeneity of cognitive function was identified through mixed growth model. Machine learning algorithms, namely regularized logistic regression (r-LR), support vector machine (SVM), random forest (RF), and super learner (SL) were used to predict cognitive trajectories. Discrimination and calibration metrics were used for performance evaluation. RESULTS Two distinct trajectories were identified according to the changes of MMSE scores: intact cognitive functioning (93.6%), and dementia (6.4%). Older age, female gender, Han ethnicity, having no schooling, rural residents, low-frequency leisure activities, and low baseline BADL score were associated with a rapid decline in cognitive function. r-LR, SVM, and SL performed well in predicting cognitive trajectories (Sensitivity: 0.73, G-mean: 0.65). Age and psychological well-being were key predictors. CONCLUSION Two cognitive trajectories were identified among older Chinese, and the identified key factors could be targeted for constructing early risk prediction models.
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Affiliation(s)
- Yafei Wu
- The State Key Laboratory of Molecular Vaccine and Molecular Diagnostics, School of Public Health, Xiamen University, Xiang' an Nan Road, Xiang' an District, Xiamen, Fujian, China; National Institute for Data Science in Health and Medicine, Xiamen University, China; Key Laboratory of Health Technology Assessment of Fujian Province, School of Public Health, Xiamen University, China
| | - Maoni Jia
- The State Key Laboratory of Molecular Vaccine and Molecular Diagnostics, School of Public Health, Xiamen University, Xiang' an Nan Road, Xiang' an District, Xiamen, Fujian, China; Key Laboratory of Health Technology Assessment of Fujian Province, School of Public Health, Xiamen University, China
| | - Chaoyi Xiang
- The State Key Laboratory of Molecular Vaccine and Molecular Diagnostics, School of Public Health, Xiamen University, Xiang' an Nan Road, Xiang' an District, Xiamen, Fujian, China; Key Laboratory of Health Technology Assessment of Fujian Province, School of Public Health, Xiamen University, China
| | - Shaowu Lin
- The State Key Laboratory of Molecular Vaccine and Molecular Diagnostics, School of Public Health, Xiamen University, Xiang' an Nan Road, Xiang' an District, Xiamen, Fujian, China; National Institute for Data Science in Health and Medicine, Xiamen University, China; Key Laboratory of Health Technology Assessment of Fujian Province, School of Public Health, Xiamen University, China
| | - Zhongquan Jiang
- The State Key Laboratory of Molecular Vaccine and Molecular Diagnostics, School of Public Health, Xiamen University, Xiang' an Nan Road, Xiang' an District, Xiamen, Fujian, China
| | - Ya Fang
- The State Key Laboratory of Molecular Vaccine and Molecular Diagnostics, School of Public Health, Xiamen University, Xiang' an Nan Road, Xiang' an District, Xiamen, Fujian, China; National Institute for Data Science in Health and Medicine, Xiamen University, China; Key Laboratory of Health Technology Assessment of Fujian Province, School of Public Health, Xiamen University, China.
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33
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Nishi SK, Babio N, Gómez-Martínez C, Martínez-González MÁ, Ros E, Corella D, Castañer O, Martínez JA, Alonso-Gómez ÁM, Wärnberg J, Vioque J, Romaguera D, López-Miranda J, Estruch R, Tinahones FJ, Lapetra J, Serra-Majem JL, Bueno-Cavanillas A, Tur JA, Martín Sánchez V, Pintó X, Delgado-Rodríguez M, Matía-Martín P, Vidal J, Vázquez C, Daimiel L, Razquin C, Coltell O, Becerra-Tomás N, De La Torre Fornell R, Abete I, Sorto-Sanchez C, Barón-López FJ, Signes-Pastor AJ, Konieczna J, Garcia-Rios A, Casas R, Gomez-Perez AM, Santos-Lozano JM, García-Arellano A, Guillem-Saiz P, Ni J, Trinidad Soria-Florido M, Zulet MÁ, Vaquero-Luna J, Toledo E, Fitó M, Salas-Salvadó J. Mediterranean, DASH, and MIND Dietary Patterns and Cognitive Function: The 2-Year Longitudinal Changes in an Older Spanish Cohort. Front Aging Neurosci 2021; 13:782067. [PMID: 34966270 PMCID: PMC8710807 DOI: 10.3389/fnagi.2021.782067] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 11/08/2021] [Indexed: 01/10/2023] Open
Abstract
Background and Aims: Plant-forward dietary patterns have been associated with cardiometabolic health benefits, which, in turn, have been related to cognitive performance with inconsistent findings. The objective of this study was to examine the relationship between baseline adherence to three a priori dietary patterns (Mediterranean, DASH, and MIND diets) with 2-year changes in cognitive performance in older adults with overweight or obesity and high cardiovascular disease risk. Methods: A prospective cohort analysis was conducted within the PREDIMED-Plus trial, involving 6,647 men and women aged 55-75 years with overweight or obesity and metabolic syndrome. Using a validated, semiquantitative 143-item food frequency questionnaire completed at baseline, the dietary pattern adherence scores were calculated. An extensive neuropsychological test battery was administered at baseline and 2-year follow-up. Multivariable-adjusted linear regression models were used to assess associations between 2-year changes in cognitive function z-scores across tertiles of baseline adherence to the a priori dietary patterns. Results: Adherence to the Mediterranean diet at baseline was associated with 2-year changes in the general cognitive screening Mini-Mental State Examination (MMSE, β: 0.070; 95% CI: 0.014, 0.175, P-trend = 0.011), and two executive function-related assessments: the Trail Making Tests Part A (TMT-A, β: -0.054; 95% CI: -0.110, - 0.002, P-trend = 0.047) and Part B (TMT-B, β: -0.079; 95% CI: -0.134, -0.024, P-trend = 0.004). Adherence to the MIND diet was associated with the backward recall Digit Span Test assessment of working memory (DST-B, β: 0.058; 95% CI: 0.002, 0.114, P-trend = 0.045). However, higher adherence to the DASH dietary pattern was not associated with better cognitive function over a period of 2 years. Conclusion: In older Spanish individuals with overweight or obesity and at high cardiovascular disease risk, higher baseline adherence to the Mediterranean dietary pattern may be associated with better cognitive performance than lower adherence over a period of 2 years.
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Affiliation(s)
- Stephanie K. Nishi
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, and Hospital Universitari San Joan de Reus, Unitat de Nutrició Humana, Reus, Spain
- Institut d’Investigació Sanitária Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Toronto 3D (Diet, Digestive Tract and Disease) Knowledge Synthesis and Clinical Trials Unit, Toronto, ON, Canada
- Clinical Nutrition and Risk Factor Modification Centre, St. Michael’s Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Nancy Babio
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, and Hospital Universitari San Joan de Reus, Unitat de Nutrició Humana, Reus, Spain
- Institut d’Investigació Sanitária Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
| | - Carlos Gómez-Martínez
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, and Hospital Universitari San Joan de Reus, Unitat de Nutrició Humana, Reus, Spain
- Institut d’Investigació Sanitária Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Miguel Ángel Martínez-González
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Emilio Ros
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Endocrinology and Nutrition, Lipid Clinic, Institut d’Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, Barcelona, Spain
| | - Dolores Corella
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Olga Castañer
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d’Investigació Médica (IMIM), Barcelona, Spain
| | - J. Alfredo Martínez
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, University of Navarra, IdiSNA, Pamplona, Spain
- Precision Nutrition and Cardiometabolic Health Program, IMDEA Food, CEI UAM + CSIC, Madrid, Spain
| | - Ángel M. Alonso-Gómez
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Bioaraba Health Research Institute, Cardiovascular, Respiratory and Metabolic Area, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain
| | - Julia Wärnberg
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- EpiPHAAN Research Group, School of Health Sciences, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, Málaga, Spain
| | - Jesús Vioque
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- Instituto de Investigación Sanitaria y Biomédica de Alicante, Universidad Miguel Hernández (ISABIAL-UMH), Alicante, Spain
| | - Dora Romaguera
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Health Research Institute of the Balearic Islands (IdISBa), Palma de Mallorca, Spain
| | - José López-Miranda
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, Cordoba, Spain
| | - Ramon Estruch
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Internal Medicine, Institut d’Investigacions Biomédiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Francisco J. Tinahones
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Endocrinology, Virgen de la Victoria Hospital, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, Málaga, Spain
| | - José Lapetra
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Family Medicine, Research Unit, Distrito Sanitario Atención Primaria Sevilla, Seville, Spain
| | - J. Luís Serra-Majem
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Research Institute of Biomedical and Health Sciences (IUIBS), University of Las Palmas de Gran Canaria and Centro Hospitalario Universitario Insular Materno Infantil (CHUIMI), Canarian Health Service, Las Palmas de Gran Canaria, Spain
| | - Aurora Bueno-Cavanillas
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain
- Instituto de Investigación Biosanitaria ibs, GRANADA, Granada, Spain
| | - Josep A. Tur
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Research Group on Community Nutrition and Oxidative Stress, University of Balearic Islands, Palma de Mallorca, Spain
| | - Vicente Martín Sánchez
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- Institute of Biomedicine (IBIOMED), University of León, León, Spain
| | - Xavier Pintó
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Lipids and Vascular Risk Unit, Internal Medicine, Hospital Universitario de Bellvitge, Hospitalet de Llobregat, Barcelona, Spain
| | - Miguel Delgado-Rodríguez
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- Division of Preventive Medicine, Faculty of Medicine, University of Jaén, Jaén, Spain
| | - Pilar Matía-Martín
- Department of Endocrinology and Nutrition, Instituto de Investigación Sanitaria Hospital Clínico San Carlos (IdISSC), Madrid, Spain
| | - Josep Vidal
- CIBER Diabetes y Enfermedades Metabólicas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Endocrinology, Institut d’ Investigacions Biomédiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Clotilde Vázquez
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Endocrinology and Nutrition, Hospital Fundación Jimenez Díaz, Instituto de Investigaciones Biomédicas IISFJD, University Autonoma, Madrid, Spain
| | - Lidia Daimiel
- Nutritional Control of the Epigenome Group, Precision Nutrition and Obesity Program, IMDEA Food, CEI UAM + CSIC, Madrid, Spain
| | - Cristina Razquin
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
| | - Oscar Coltell
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Computer Languages and Systems, Universitat Jaume I, Castellon, Spain
| | - Nerea Becerra-Tomás
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, and Hospital Universitari San Joan de Reus, Unitat de Nutrició Humana, Reus, Spain
- Institut d’Investigació Sanitária Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Rafael De La Torre Fornell
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Integrative Pharmacology and Systems Neurosciences, Instituto Hospital del Mar de Investigaciones Médicas (IMIM), Barcelona, Spain
| | - Itziar Abete
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, University of Navarra, IdiSNA, Pamplona, Spain
| | - Carolina Sorto-Sanchez
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Bioaraba Health Research Institute, Cardiovascular, Respiratory and Metabolic Area, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain
| | - Francisco Javier Barón-López
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- EpiPHAAN Research Group, School of Health Sciences, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, Málaga, Spain
| | - Antonio José Signes-Pastor
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- Instituto de Investigación Sanitaria y Biomédica de Alicante, Universidad Miguel Hernández (ISABIAL-UMH), Alicante, Spain
| | - Jadwiga Konieczna
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Health Research Institute of the Balearic Islands (IdISBa), Palma de Mallorca, Spain
| | - Antonio Garcia-Rios
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, Cordoba, Spain
| | - Rosa Casas
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Internal Medicine, Institut d’Investigacions Biomédiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Ana Maria Gomez-Perez
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Endocrinology, Virgen de la Victoria Hospital, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, Málaga, Spain
| | - José Manuel Santos-Lozano
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Family Medicine, Research Unit, Distrito Sanitario Atención Primaria Sevilla, Seville, Spain
| | - Ana García-Arellano
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Endocrinology, Virgen de la Victoria Hospital, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, Málaga, Spain
| | - Patricia Guillem-Saiz
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Jiaqi Ni
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, and Hospital Universitari San Joan de Reus, Unitat de Nutrició Humana, Reus, Spain
- Institut d’Investigació Sanitária Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | | | - M. Ángeles Zulet
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, University of Navarra, IdiSNA, Pamplona, Spain
| | - Jessica Vaquero-Luna
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Bioaraba Health Research Institute, Cardiovascular, Respiratory and Metabolic Area, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain
| | - Estefanía Toledo
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
| | - Montserrat Fitó
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d’Investigació Médica (IMIM), Barcelona, Spain
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, and Hospital Universitari San Joan de Reus, Unitat de Nutrició Humana, Reus, Spain
- Institut d’Investigació Sanitária Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
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Keins S, Abramson JR, Castello JP, Pasi M, Charidimou A, Kourkoulis C, DiPucchio Z, Schwab K, Anderson CD, Gurol ME, Greenberg SM, Rosand J, Viswanathan A, Biffi A. Latent profile analysis of cognitive decline and depressive symptoms after intracerebral hemorrhage. BMC Neurol 2021; 21:481. [PMID: 34893031 PMCID: PMC8662844 DOI: 10.1186/s12883-021-02508-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 11/22/2021] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Cognitive impairment and depressive symptoms are highly prevalent after Intracerebral Hemorrhage (ICH). We leveraged Latent Profile Analysis (LPA) to identify profiles for cognitive decline and depression onset after ICH. We also investigated differences in clinical, genetic and neuroimaging characteristics across patients' profiles. METHODS We analyzed data from the ICH study conducted at Massachusetts General Hospital between January 1998 and December 2019. We collected information from electronical health records, follow-up interviews, CT and MRI imaging, and APOE genotype. We conducted LPA and multinomial logistic regression analyses to: 1) identify distinct profiles for cognitive decline and depression onset after ICH; 2) identify clinical, neuroimaging and genetic factors predicting individuals' likelihood to express a specific profile. RESULTS We followed 784 ICH survivors for a median of 45.8 months. We identified four distinct profiles in cognitive and depressive symptoms after ICH: low depression and dementia risk, early-onset depression and dementia, late-onset depression and dementia, high depression with low dementia risk. Cerebral small vessel disease severity and APOE genotype were specifically associated with the late-onset profile (both p < 0.05). Acute hematoma characteristics (size, intraventricular extension) and functional disability were specifically associated with the early-onset profile (all p < 0.05). CONCLUSION We identified four distinct profiles for cognitive and depressive symptoms after ICH, each displaying specific associations with individual patients' clinical, genetic and neuroimaging data. These associations reflect separate biological mechanisms influencing dementia and depression risk after ICH. Our findings support employing LPA in future ICH studies, and is likely applicable to stroke survivors at large.
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Affiliation(s)
- Sophia Keins
- Department of Neurology, Massachusetts General Hospital, 100 Cambridge Street - Room 2064, Boston, MA, 02114, USA.,Hemorrhagic Stroke Research Program, Massachusetts General Hospital, Boston, MA, USA.,Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA.,Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Jessica R Abramson
- Department of Neurology, Massachusetts General Hospital, 100 Cambridge Street - Room 2064, Boston, MA, 02114, USA.,Hemorrhagic Stroke Research Program, Massachusetts General Hospital, Boston, MA, USA.,Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Juan Pablo Castello
- Department of Neurology, Massachusetts General Hospital, 100 Cambridge Street - Room 2064, Boston, MA, 02114, USA.,Hemorrhagic Stroke Research Program, Massachusetts General Hospital, Boston, MA, USA.,Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
| | - Marco Pasi
- Department of Neurology, Massachusetts General Hospital, 100 Cambridge Street - Room 2064, Boston, MA, 02114, USA.,Univ.Lille, Inserm, CHU Lille, U 1172 - LilNCog - Lille Neuroscience and Cognition, F-59000, Lille, France
| | - Andreas Charidimou
- Department of Neurology, Massachusetts General Hospital, 100 Cambridge Street - Room 2064, Boston, MA, 02114, USA.,Hemorrhagic Stroke Research Program, Massachusetts General Hospital, Boston, MA, USA
| | - Christina Kourkoulis
- Department of Neurology, Massachusetts General Hospital, 100 Cambridge Street - Room 2064, Boston, MA, 02114, USA.,Hemorrhagic Stroke Research Program, Massachusetts General Hospital, Boston, MA, USA.,Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Zora DiPucchio
- Department of Neurology, Massachusetts General Hospital, 100 Cambridge Street - Room 2064, Boston, MA, 02114, USA.,Hemorrhagic Stroke Research Program, Massachusetts General Hospital, Boston, MA, USA
| | - Kristin Schwab
- Department of Neurology, Massachusetts General Hospital, 100 Cambridge Street - Room 2064, Boston, MA, 02114, USA.,Hemorrhagic Stroke Research Program, Massachusetts General Hospital, Boston, MA, USA
| | - Christopher D Anderson
- Department of Neurology, Massachusetts General Hospital, 100 Cambridge Street - Room 2064, Boston, MA, 02114, USA.,Hemorrhagic Stroke Research Program, Massachusetts General Hospital, Boston, MA, USA.,Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - M Edip Gurol
- Department of Neurology, Massachusetts General Hospital, 100 Cambridge Street - Room 2064, Boston, MA, 02114, USA.,Hemorrhagic Stroke Research Program, Massachusetts General Hospital, Boston, MA, USA
| | - Steven M Greenberg
- Department of Neurology, Massachusetts General Hospital, 100 Cambridge Street - Room 2064, Boston, MA, 02114, USA.,Hemorrhagic Stroke Research Program, Massachusetts General Hospital, Boston, MA, USA
| | - Jonathan Rosand
- Department of Neurology, Massachusetts General Hospital, 100 Cambridge Street - Room 2064, Boston, MA, 02114, USA.,Hemorrhagic Stroke Research Program, Massachusetts General Hospital, Boston, MA, USA.,Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Anand Viswanathan
- Department of Neurology, Massachusetts General Hospital, 100 Cambridge Street - Room 2064, Boston, MA, 02114, USA.,Hemorrhagic Stroke Research Program, Massachusetts General Hospital, Boston, MA, USA
| | - Alessandro Biffi
- Department of Neurology, Massachusetts General Hospital, 100 Cambridge Street - Room 2064, Boston, MA, 02114, USA. .,Hemorrhagic Stroke Research Program, Massachusetts General Hospital, Boston, MA, USA. .,Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA. .,Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.
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Freedman VA, Bandeen-Roche K, Cornman JC, Spillman BC, Kasper JD, Wolff JL. Incident Care Trajectories for Older Adults with and without Dementia. J Gerontol B Psychol Sci Soc Sci 2021; 77:S21-S30. [PMID: 34893835 DOI: 10.1093/geronb/gbab185] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Indexed: 11/12/2022] Open
Abstract
OBJECTIVE Despite cross-sectional evidence that persons living with dementia receive disproportionate hours of care, studies of how care intensity progresses over time and differs for those living with and without dementia have been lacking. METHODS We used the 2011-2018 National Health and Aging Trends Study to estimate growth mixture models to identify incident care hour trajectories ("classes") among older adults (N=1,780). RESULTS We identified four incident care hour classes: "Low, stable," "High, increasing," "24/7 then high, stable," and "Low then resolved." The high-intensity classes had the highest proportions of care recipients with dementia and accounted for nearly half of that group. Older adults with dementia were 3-4 times as likely as other older adults to experience one of the two high-intensity trajectories. A substantial proportion of the 4 in 10 older adults with dementia who were predicted to be in the "Low, stable" class lived in residential care settings. DISCUSSION Information on how family caregiving is likely to evolve over time in terms of care hours may help older adults with and without dementia, the family members, friends, and paid individuals who care for them, as well as their health care providers assess and plan for future care needs.
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Wang X, Younan D, Petkus AJ, Beavers DP, Espeland MA, Chui HC, Resnick SM, Gatz M, Kaufman JD, Wellenius GA, Whitsel EA, Manson JE, Chen JC. Ambient Air Pollution and Long-Term Trajectories of Episodic Memory Decline among Older Women in the WHIMS-ECHO Cohort. ENVIRONMENTAL HEALTH PERSPECTIVES 2021; 129:97009. [PMID: 34516296 PMCID: PMC8437247 DOI: 10.1289/ehp7668] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/13/2020] [Revised: 08/17/2021] [Accepted: 08/19/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Episodic memory decline varies by age and underlying neuropathology. Whether ambient air pollution contributes to the heterogeneity of episodic memory decline in older populations remains unclear. OBJECTIVES We estimated associations between air pollution exposures and episodic memory decline according to pollutant, exposure time window, age, and latent class subgroups defined by episodic memory trajectories. METHODS Participants were from the Women's Health Initiative Memory Study-Epidemiology of Cognitive Health Outcomes. Older women (n = 2,056 ; 74-92 years of age) completed annual (2008-2018) episodic memory assessments using the telephone-based California Verbal Learning Test (CVLT). We estimated 3-y average fine particulate matter [PM with an aerodynamic diameter of ≤ 2.5 μ m (PM 2.5 )] and nitrogen dioxide (NO 2 ) exposures at baseline and 10 y earlier (recent and remote exposures, respectively), using regionalized national universal kriging. Separate latent class mixed models were used to estimate associations between interquartile range increases in exposures and CVLT trajectories in women ≤ 80 and > 80 years of age , adjusting for covariates. RESULTS Two latent classes were identified for women ≤ 80 years of age (n = 828 ), "slow-decliners" {slope = - 0.12 / y [95% confidence interval (CI): - 0.23 , - 0.01 ] and "fast-decliners" [slope = - 1.79 / y (95% CI: - 2.08 , - 1.50 )]}. In the slow-decliner class, but not the fast-decliner class, PM 2.5 exposures were associated with a greater decline in CVLT scores over time, with a stronger association for recent vs. remote exposures [- 0.16 / y (95% CI: - 2.08 , - 0.03 ) per 2.88 μ g / m 3 and - 0.11 / y (95% CI: - 0.22 , 0.01) per 3.27 μ g / m 3 , respectively]. Among women ≥ 80 years of age (n = 1,128 ), the largest latent class comprised "steady-decliners" [slope = - 1.35 / y (95% CI: - 1.53 , - 1.17 )], whereas the second class, "cognitively resilient", had no decline in CVLT on average. PM 2.5 was not associated with episodic memory decline in either class. A 6.25 -ppb increase in recent NO 2 was associated with nonsignificant acceleration of episodic memory decline in the ≤ 80 -y-old fast-decliner class [- 0.21 / y (95% CI: - 0.45 , 0.04)], and in the > 80 -y-old cognitively resilient class [- 0.10 / y (95% CI: - 0.24 , 0.03)] and steady-decliner class [- 0.11 / y (95% CI: - 0.27 , 0.05)]. Associations with recent NO 2 exposure in women > 80 years of age were stronger and statistically significant when 267 women with incident probable dementia were excluded [e.g., - 0.12 / y (95% CI: - 0.22 , - 0.02 ) for the cognitively resilient class]. In contrast with changes in CVLT over time, there were no associations between exposures and CVLT scores during follow-up in any subgroup. DISCUSSION In a community-dwelling U.S. population of older women, associations between late-life exposure to ambient air pollution and episodic memory decline varied by age-related cognitive trajectories, exposure time windows, and pollutants. https://doi.org/10.1289/EHP7668.
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Affiliation(s)
- Xinhui Wang
- Department of Neurology, University of Southern California, Los Angeles, California, USA
| | - Diana Younan
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, USA
| | - Andrew J. Petkus
- Department of Neurology, University of Southern California, Los Angeles, California, USA
| | - Daniel P. Beavers
- Department of Biostatistics and Data Sciences, Wake Forest School of Medicine, Wake Forest University, Winston-Salem, North Carolina, USA
| | - Mark A. Espeland
- Department of Biostatistics and Data Sciences, Wake Forest School of Medicine, Wake Forest University, Winston-Salem, North Carolina, USA
| | - Helena C. Chui
- Department of Neurology, University of Southern California, Los Angeles, California, USA
| | - Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Department of Health and Human Services, Baltimore, Maryland, USA
| | - Margaret Gatz
- Center for Economic and Social Research, University of Southern California, Los Angeles, California, USA
| | - Joel D. Kaufman
- Departments of Environmental & Occupational Health Sciences, Medicine (General Internal Medicine), and Epidemiology, University of Washington, Seattle, Washington, USA
| | - Gregory A. Wellenius
- Department of Environmental Health, Boston University, Boston, Massachusetts, USA
| | - Eric A. Whitsel
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - JoAnn E. Manson
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Jiu-Chiuan Chen
- Department of Neurology, University of Southern California, Los Angeles, California, USA
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, USA
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Sweigart B, Andersen SL, Gurinovich A, Cosentino S, Schupf N, Perls TT, Sebastiani P. APOE E2/E2 Is Associated with Slower Rate of Cognitive Decline with Age. J Alzheimers Dis 2021; 83:853-860. [PMID: 34366332 DOI: 10.3233/jad-201205] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
BACKGROUND The E4 allele of the APOE gene is known to be associated with cognitive impairment. However, a limited number of studies have examined the association between the E2 allele and longitudinal changes of cognitive function. OBJECTIVE To determine whether rates of cognitive change differ in carriers of the APOE E2 allele compared to other genotypes. METHODS We conducted a secondary analysis of data from two ongoing longitudinal cohort studies, the Long Life Family Study (LLFS) and New England Centenarian Study (NECS). We included participants who had APOE genotyping data, data from longitudinal administrations of the Telephone Interview for Cognitive Status (TICS), and age, sex, and education available. We assessed whether cognitive change as measured by rate of decline in TICS score differed among people with different APOE genotypes. We used a hierarchical mixed effect model with APOE genotypes, their interactions with age, and potential confounders. RESULTS After adjusting for sex and education, in carriers of the common E3/E3 genotype, TICS score decreased by 0.15 points per year of age. In those with the E2/E2 genotype, TICS score decreased by 0.05 points per year of age, a significantly slower rate of decline (p = 0.017). We observed no protective effect of the E2/E3 genotype on cognitive decline. CONCLUSION These results suggest a protective effect of the E2/E2 genotype on a measure of global cognitive function.
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Affiliation(s)
- Benjamin Sweigart
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Stacy L Andersen
- Geriatrics Section, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Anastasia Gurinovich
- Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA
| | - Stephanie Cosentino
- Cognitive Neuroscience Division of the Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA.,Gertrude H. Sergievsky Center, Columbia University, New York, NY, USA
| | - Nicole Schupf
- Cognitive Neuroscience Division of the Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA.,Gertrude H. Sergievsky Center, Columbia University, New York, NY, USA
| | - Thomas T Perls
- Geriatrics Section, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Paola Sebastiani
- Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA
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Lobo E, Gracia-García P, Lobo A, Saz P, De-la-Cámara C. Differences in Trajectories and Predictive Factors of Cognition over Time in a Sample of Cognitively Healthy Adults, in Zaragoza, Spain. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:7092. [PMID: 34281039 PMCID: PMC8297330 DOI: 10.3390/ijerph18137092] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Revised: 06/28/2021] [Accepted: 06/30/2021] [Indexed: 11/16/2022]
Abstract
Great inter-individual variability has been reported in the maintenance of cognitive function in aging. We examined this heterogeneity by modeling cognitive trajectories in a population-based longitudinal study of adults aged 55+ years. We hypothesized that (1) distinct classes of cognitive trajectories would be found, and (2) between-class differences in associated factors would be observed. The sample comprised 2403 cognitively healthy individuals from the Zaragoza Dementia and Depression (ZARADEMP) project, who had at least three measurements of the Mini-Mental State Examination (MMSE) in a 12-year follow-up. Longitudinal changes in cognitive functioning were modeled using growth mixture models (GMM) in the data. The best-fitting age-adjusted model showed 3 distinct trajectories, with 1-high-to-moderate (21.2% of participants), 2-moderate-stable (67.5%) and, 3-low-and-declining (9.9%) cognitive function over time, respectively. Compared with the reference 2-trajectory, the association of education and depression was significantly different in trajectories 1 and 3. Instrumental activities of daily living (iADLs) were only associated with the declining trajectory. This suggests that intervention strategies should be tailored specifically to individuals with different trajectories of cognitive aging, and intervention strategies designed to maintain cognitive function might be different from those to prevent decline. A stable cognitive performance ('successful cognitive aging') rather than a mild decline, might be more 'normal' than generally expected.
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Affiliation(s)
- Elena Lobo
- Department of Preventive Medicine and Public Health, Universidad de Zaragoza, 50009 Zaragoza, Spain
- Instituto de Investigación Sanitaria de Aragón (IIS Aragón), 50009 Zaragoza, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Ministry of Science and Innovation, 28029 Madrid, Spain
| | - Patricia Gracia-García
- Instituto de Investigación Sanitaria de Aragón (IIS Aragón), 50009 Zaragoza, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Ministry of Science and Innovation, 28029 Madrid, Spain
- Psychiatry Service, Hospital Universitario Miguel Servet, 50009 Zaragoza, Spain
- Department of Medicine and Psychiatry, Universidad de Zaragoza, 50009 Zaragoza, Spain
| | - Antonio Lobo
- Instituto de Investigación Sanitaria de Aragón (IIS Aragón), 50009 Zaragoza, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Ministry of Science and Innovation, 28029 Madrid, Spain
- Department of Medicine and Psychiatry, Universidad de Zaragoza, 50009 Zaragoza, Spain
| | - Pedro Saz
- Instituto de Investigación Sanitaria de Aragón (IIS Aragón), 50009 Zaragoza, Spain
- Department of Medicine and Psychiatry, Universidad de Zaragoza, 50009 Zaragoza, Spain
| | - Concepción De-la-Cámara
- Instituto de Investigación Sanitaria de Aragón (IIS Aragón), 50009 Zaragoza, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Ministry of Science and Innovation, 28029 Madrid, Spain
- Department of Medicine and Psychiatry, Universidad de Zaragoza, 50009 Zaragoza, Spain
- Psychiatry Service, Hospital Clínico Universitario, 50009 Zaragoza, Spain
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Wu Z, Woods RL, Wolfe R, Storey E, Chong TTJ, Shah RC, Orchard SG, McNeil JJ, Murray AM, Ryan J. Trajectories of cognitive function in community-dwelling older adults: A longitudinal study of population heterogeneity. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2021; 13:e12180. [PMID: 33969173 PMCID: PMC8088593 DOI: 10.1002/dad2.12180] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 03/01/2021] [Indexed: 11/20/2022]
Abstract
INTRODUCTION This study aimed to investigate cognitive aging trajectories, the associated sociodemographic characteristics, and the association of these trajectories with dementia. METHODS Generally healthy older adults (n = 19,114) were followed for up to 7 years, with regular cognitive assessments. Group-based trajectory modeling identified distinct cognitive trajectories. RESULTS Four to seven trajectories were identified per cognitive domain. Stable trajectories were observed across domains. Improvement in verbal fluency and minor psychomotor slowing were common. Substantial decline in global cognition and episodic memory were observed in a small proportion of individuals. Older, less educated participants and men were more common in lower-functioning trajectories (p < .001). The highest proportions of dementia cases were in trajectories with major decline in global cognition (56.9%) and memory (33.2%). DISCUSSION Inter-individual variability in cognitive trajectories was observed across all domains. Some individuals appear resilient to cognitive decline even with advancing age. Further research into factors promoting cognitive resilience is needed.
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Affiliation(s)
- Zimu Wu
- School of Public Health and Preventive MedicineMonash UniversityMelbourneAustralia
| | - Robyn L. Woods
- School of Public Health and Preventive MedicineMonash UniversityMelbourneAustralia
| | - Rory Wolfe
- School of Public Health and Preventive MedicineMonash UniversityMelbourneAustralia
| | - Elsdon Storey
- School of Public Health and Preventive MedicineMonash UniversityMelbourneAustralia
| | - Trevor T. J. Chong
- Turner Institute for Brain and Mental HealthMonash UniversityMelbourneAustralia
- Department of NeurologyAlfred HealthMelbourneAustralia
- Department of Clinical NeurosciencesSt. Vincent's HospitalMelbourneAustralia
| | - Raj C. Shah
- Department of Family Medicine and Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
| | - Suzanne G. Orchard
- School of Public Health and Preventive MedicineMonash UniversityMelbourneAustralia
| | - John J. McNeil
- School of Public Health and Preventive MedicineMonash UniversityMelbourneAustralia
| | - Anne M. Murray
- Berman Center for Outcomes and Clinical ResearchMinneapolisMinnesotaUSA
| | - Joanne Ryan
- School of Public Health and Preventive MedicineMonash UniversityMelbourneAustralia
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Nishi SK, Babio N, Gómez-Martínez C, Martínez-González MÁ, Ros E, Corella D, Castañer O, Martínez JA, Alonso-Gómez ÁM, Wärnberg J, Vioque J, Romaguera D, López-Miranda J, Estruch R, Tinahones FJ, Lapetra J, Serra-Majem JL, Bueno-Cavanillas A, Tur JA, Martín Sánchez V, Pintó X, Delgado-Rodríguez M, Matía-Martín P, Vidal J, Vázquez C, Daimiel L, Razquin C, Coltell O, Becerra-Tomás N, De La Torre Fornell R, Abete I, Sorto-Sanchez C, Barón-López FJ, Signes-Pastor AJ, Konieczna J, Garcia-Rios A, Casas R, Gomez-Perez AM, Santos-Lozano JM, García-Arellano A, Guillem-Saiz P, Ni J, Trinidad Soria-Florido M, Zulet MÁ, Vaquero-Luna J, Toledo E, Fitó M, Salas-Salvadó J. Mediterranean, DASH, and MIND Dietary Patterns and Cognitive Function: The 2-Year Longitudinal Changes in an Older Spanish Cohort. Front Aging Neurosci 2021. [PMID: 34966270 DOI: 10.3389/fnagi.2021.782067/full] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/26/2023] Open
Abstract
Background and Aims: Plant-forward dietary patterns have been associated with cardiometabolic health benefits, which, in turn, have been related to cognitive performance with inconsistent findings. The objective of this study was to examine the relationship between baseline adherence to three a priori dietary patterns (Mediterranean, DASH, and MIND diets) with 2-year changes in cognitive performance in older adults with overweight or obesity and high cardiovascular disease risk. Methods: A prospective cohort analysis was conducted within the PREDIMED-Plus trial, involving 6,647 men and women aged 55-75 years with overweight or obesity and metabolic syndrome. Using a validated, semiquantitative 143-item food frequency questionnaire completed at baseline, the dietary pattern adherence scores were calculated. An extensive neuropsychological test battery was administered at baseline and 2-year follow-up. Multivariable-adjusted linear regression models were used to assess associations between 2-year changes in cognitive function z-scores across tertiles of baseline adherence to the a priori dietary patterns. Results: Adherence to the Mediterranean diet at baseline was associated with 2-year changes in the general cognitive screening Mini-Mental State Examination (MMSE, β: 0.070; 95% CI: 0.014, 0.175, P-trend = 0.011), and two executive function-related assessments: the Trail Making Tests Part A (TMT-A, β: -0.054; 95% CI: -0.110, - 0.002, P-trend = 0.047) and Part B (TMT-B, β: -0.079; 95% CI: -0.134, -0.024, P-trend = 0.004). Adherence to the MIND diet was associated with the backward recall Digit Span Test assessment of working memory (DST-B, β: 0.058; 95% CI: 0.002, 0.114, P-trend = 0.045). However, higher adherence to the DASH dietary pattern was not associated with better cognitive function over a period of 2 years. Conclusion: In older Spanish individuals with overweight or obesity and at high cardiovascular disease risk, higher baseline adherence to the Mediterranean dietary pattern may be associated with better cognitive performance than lower adherence over a period of 2 years.
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Affiliation(s)
- Stephanie K Nishi
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, and Hospital Universitari San Joan de Reus, Unitat de Nutrició Humana, Reus, Spain
- Institut d'Investigació Sanitária Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Toronto 3D (Diet, Digestive Tract and Disease) Knowledge Synthesis and Clinical Trials Unit, Toronto, ON, Canada
- Clinical Nutrition and Risk Factor Modification Centre, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Nancy Babio
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, and Hospital Universitari San Joan de Reus, Unitat de Nutrició Humana, Reus, Spain
- Institut d'Investigació Sanitária Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
| | - Carlos Gómez-Martínez
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, and Hospital Universitari San Joan de Reus, Unitat de Nutrició Humana, Reus, Spain
- Institut d'Investigació Sanitária Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Miguel Ángel Martínez-González
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Emilio Ros
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Endocrinology and Nutrition, Lipid Clinic, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, Barcelona, Spain
| | - Dolores Corella
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Olga Castañer
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d'Investigació Médica (IMIM), Barcelona, Spain
| | - J Alfredo Martínez
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, University of Navarra, IdiSNA, Pamplona, Spain
- Precision Nutrition and Cardiometabolic Health Program, IMDEA Food, CEI UAM + CSIC, Madrid, Spain
| | - Ángel M Alonso-Gómez
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Bioaraba Health Research Institute, Cardiovascular, Respiratory and Metabolic Area, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain
| | - Julia Wärnberg
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- EpiPHAAN Research Group, School of Health Sciences, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, Málaga, Spain
| | - Jesús Vioque
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- Instituto de Investigación Sanitaria y Biomédica de Alicante, Universidad Miguel Hernández (ISABIAL-UMH), Alicante, Spain
| | - Dora Romaguera
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Health Research Institute of the Balearic Islands (IdISBa), Palma de Mallorca, Spain
| | - José López-Miranda
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, Cordoba, Spain
| | - Ramon Estruch
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Internal Medicine, Institut d'Investigacions Biomédiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Francisco J Tinahones
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Endocrinology, Virgen de la Victoria Hospital, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, Málaga, Spain
| | - José Lapetra
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Family Medicine, Research Unit, Distrito Sanitario Atención Primaria Sevilla, Seville, Spain
| | - J Luís Serra-Majem
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Research Institute of Biomedical and Health Sciences (IUIBS), University of Las Palmas de Gran Canaria and Centro Hospitalario Universitario Insular Materno Infantil (CHUIMI), Canarian Health Service, Las Palmas de Gran Canaria, Spain
| | - Aurora Bueno-Cavanillas
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain
- Instituto de Investigación Biosanitaria ibs, GRANADA, Granada, Spain
| | - Josep A Tur
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Research Group on Community Nutrition and Oxidative Stress, University of Balearic Islands, Palma de Mallorca, Spain
| | - Vicente Martín Sánchez
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- Institute of Biomedicine (IBIOMED), University of León, León, Spain
| | - Xavier Pintó
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Lipids and Vascular Risk Unit, Internal Medicine, Hospital Universitario de Bellvitge, Hospitalet de Llobregat, Barcelona, Spain
| | - Miguel Delgado-Rodríguez
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- Division of Preventive Medicine, Faculty of Medicine, University of Jaén, Jaén, Spain
| | - Pilar Matía-Martín
- Department of Endocrinology and Nutrition, Instituto de Investigación Sanitaria Hospital Clínico San Carlos (IdISSC), Madrid, Spain
| | - Josep Vidal
- CIBER Diabetes y Enfermedades Metabólicas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Endocrinology, Institut d' Investigacions Biomédiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Clotilde Vázquez
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Endocrinology and Nutrition, Hospital Fundación Jimenez Díaz, Instituto de Investigaciones Biomédicas IISFJD, University Autonoma, Madrid, Spain
| | - Lidia Daimiel
- Nutritional Control of the Epigenome Group, Precision Nutrition and Obesity Program, IMDEA Food, CEI UAM + CSIC, Madrid, Spain
| | - Cristina Razquin
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
| | - Oscar Coltell
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Computer Languages and Systems, Universitat Jaume I, Castellon, Spain
| | - Nerea Becerra-Tomás
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, and Hospital Universitari San Joan de Reus, Unitat de Nutrició Humana, Reus, Spain
- Institut d'Investigació Sanitária Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Rafael De La Torre Fornell
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Integrative Pharmacology and Systems Neurosciences, Instituto Hospital del Mar de Investigaciones Médicas (IMIM), Barcelona, Spain
| | - Itziar Abete
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, University of Navarra, IdiSNA, Pamplona, Spain
| | - Carolina Sorto-Sanchez
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Bioaraba Health Research Institute, Cardiovascular, Respiratory and Metabolic Area, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain
| | - Francisco Javier Barón-López
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- EpiPHAAN Research Group, School of Health Sciences, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, Málaga, Spain
| | - Antonio José Signes-Pastor
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- Instituto de Investigación Sanitaria y Biomédica de Alicante, Universidad Miguel Hernández (ISABIAL-UMH), Alicante, Spain
| | - Jadwiga Konieczna
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Health Research Institute of the Balearic Islands (IdISBa), Palma de Mallorca, Spain
| | - Antonio Garcia-Rios
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, Cordoba, Spain
| | - Rosa Casas
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Internal Medicine, Institut d'Investigacions Biomédiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Ana Maria Gomez-Perez
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Endocrinology, Virgen de la Victoria Hospital, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, Málaga, Spain
| | - José Manuel Santos-Lozano
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Family Medicine, Research Unit, Distrito Sanitario Atención Primaria Sevilla, Seville, Spain
| | - Ana García-Arellano
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Endocrinology, Virgen de la Victoria Hospital, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, Málaga, Spain
| | - Patricia Guillem-Saiz
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Jiaqi Ni
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, and Hospital Universitari San Joan de Reus, Unitat de Nutrició Humana, Reus, Spain
- Institut d'Investigació Sanitária Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | | | - M Ángeles Zulet
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, University of Navarra, IdiSNA, Pamplona, Spain
| | - Jessica Vaquero-Luna
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Bioaraba Health Research Institute, Cardiovascular, Respiratory and Metabolic Area, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain
| | - Estefanía Toledo
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
| | - Montserrat Fitó
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d'Investigació Médica (IMIM), Barcelona, Spain
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, and Hospital Universitari San Joan de Reus, Unitat de Nutrició Humana, Reus, Spain
- Institut d'Investigació Sanitária Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
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