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Song J, Liang Y, Xu Z, Wu Y, Yan S, Mei L, Sun X, Li Y, Jin X, Yi W, Pan R, Cheng J, Hu W, Su H. Built environment and schizophrenia re-hospitalization risk in China: A cohort study. ENVIRONMENTAL RESEARCH 2023; 227:115816. [PMID: 37003555 DOI: 10.1016/j.envres.2023.115816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 03/13/2023] [Accepted: 03/30/2023] [Indexed: 05/08/2023]
Abstract
BACKGROUND Built environment exposure, characterized by ubiquity and changeability, has the potential to be the prospective target of public health policy. However, little research has been conducted to explore its impact on schizophrenia. This study aimed to investigate the association between built environmentand and schizophrenia rehospitalization by simultaneously considering substantial built environmental exposures. METHODS We recruited eligible schizophrenia patients from Hefei, Anhui Province, China between 2017 and 2019. The main outcome for this study was the time interval until the first recurrent hospital admission occurred within one year after discharge. For each included subject, we estimated the built environment exposures, including population density, walkability, land use mix, green and blue space, public transportation accessibility and road traffic indicator. Lasso (Least Absolute Shrinkage and Selection Operator) analysis was used to select the key variables. Multivariable Cox regression model was applied to obtain hazard ratio (HR) and its corresponding 95% confidence intervals (CI). Further, we also evaluated the joint effects of built environment characteristics on rehospitalization for schizophrenia by Quantile g-computation model. RESULTS A total of 1564 hospitalized schizophrenia patients were enrolled, with 347 patients (22.2%) had a rehospitalization within one-year after discharge. Multivariable Cox regression analysis indicated that the re-hospitalization rate for schizophrenia would be higher in areas with a high population density (HR: 1.10, 95%CI: 1.04-1.16). Nonetheless, compared to the reference (Q1), participants who lived in a neighborhood with the highest walkability and NDVI (Normalized Difference Vegetation Index) (Q4) had a 76% and 47% lower risk of re-hospitalization within one year (HR:0.24, 95%CI: 0.13-0.45; and 0.53, 95%CI:0.32-0.85), respectively. Moreover, quantile-based g-computation analyses revealed that increased walkability and green space significantly eliminated the adverse effects of population density increases on schizophrenia patients, with a HR ratio of 0.61 (95%CI:0.48,0.79) per one quartile change at the same time. CONCLUSION Our study provides scientific evidence for the significant role of built environment in schizophrenia rehospitalization, suggesting that optimizing the built environment is required in designing and building a healthy city.
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Affiliation(s)
- Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, No.81 Meishan Road, Shushan District, Hefei, Anhui, 230031, China; Ecosystem Change and Population Health Research Group, School of Public Health and Social Work, Queensland University of Technology, Australia
| | - Yunfeng Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, No.81 Meishan Road, Shushan District, Hefei, Anhui, 230031, China
| | - Zhiwei Xu
- School of Medicine and Dentistry, Gold Coast Campus, Griffith University, QLD, 4222, Australia
| | - Yudong Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, No.81 Meishan Road, Shushan District, Hefei, Anhui, 230031, China
| | - Shuangshuang Yan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, No.81 Meishan Road, Shushan District, Hefei, Anhui, 230031, China
| | - Lu Mei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, No.81 Meishan Road, Shushan District, Hefei, Anhui, 230031, China
| | - Xiaoni Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, No.81 Meishan Road, Shushan District, Hefei, Anhui, 230031, China
| | - Yuxuan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, No.81 Meishan Road, Shushan District, Hefei, Anhui, 230031, China
| | - Xiaoyu Jin
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, No.81 Meishan Road, Shushan District, Hefei, Anhui, 230031, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, No.81 Meishan Road, Shushan District, Hefei, Anhui, 230031, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, No.81 Meishan Road, Shushan District, Hefei, Anhui, 230031, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, No.81 Meishan Road, Shushan District, Hefei, Anhui, 230031, China
| | - Wenbiao Hu
- Ecosystem Change and Population Health Research Group, School of Public Health and Social Work, Queensland University of Technology, Australia.
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, No.81 Meishan Road, Shushan District, Hefei, Anhui, 230031, China.
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Yu W, Esposito M, Li M, Clarke P, Judd S, Finlay J. Neighborhood 'Disamenities': local barriers and cognitive function among Black and white aging adults. BMC Public Health 2023; 23:197. [PMID: 36717795 PMCID: PMC9885664 DOI: 10.1186/s12889-023-15026-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 01/11/2023] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND This study examined the association between cognitive function and three neighborhood 'disamenities' that may pose local barriers to utilizing community resources and increase risk for cognitive decline. METHOD Using national data from 21,165 urban- and suburban-dwelling Black and white adults (mean age: 67 years) in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study, we assessed global cognitive function through a factor score of five cognitive screening tests. General Additive Mixed Models (GAMM) tested whether residing in areas with more polluting sites, highways, and limited walkability was associated with worse cognitive function. RESULTS Limited walkability and the presence of polluting sites had a significant negative association with cognitive function after controlling for individual and neighborhood factors. CONCLUSION Neighborhood disamenities may be linked to cognitive function among aging residents. Identifying neighborhood factors that pose barriers to accessing community resources may inform upstream policy applications to reduce risk for cognitive decline.
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Affiliation(s)
- Wenshan Yu
- Program in Survey and Data Science, Institute for Social Research, University of Michigan, 426 Thompson Street, Ann Arbor, MI, 48104, USA.
- Social Environment and Health, Survey Research Center, Institute for Social Research, University of Michigan 426 Thompson Street, Ann Arbor, MI, United States, 48104.
| | - Michael Esposito
- Social Environment and Health, Survey Research Center, Institute for Social Research, University of Michigan 426 Thompson Street, Ann Arbor, MI, United States, 48104
- Department of Sociology, Washington University in St. Louis, St. Louis, MO, 63130, USA
| | - Mao Li
- Program in Survey and Data Science, Institute for Social Research, University of Michigan, 426 Thompson Street, Ann Arbor, MI, 48104, USA
- Social Environment and Health, Survey Research Center, Institute for Social Research, University of Michigan 426 Thompson Street, Ann Arbor, MI, United States, 48104
| | - Philippa Clarke
- Social Environment and Health, Survey Research Center, Institute for Social Research, University of Michigan 426 Thompson Street, Ann Arbor, MI, United States, 48104
- Center for Social Epidemiology and Population Health, Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA
| | - Suzanne Judd
- School of Public Health, University of Alabama at Birmingham, 1665 University Blvd, Birmingham, AL, 35233, USA
| | - Jessica Finlay
- Social Environment and Health, Survey Research Center, Institute for Social Research, University of Michigan 426 Thompson Street, Ann Arbor, MI, United States, 48104
- Center for Social Epidemiology and Population Health, Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA
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3
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Kim B, Barrington WE, Dobra A, Rosenberg D, Hurvitz P, Belza B. Mediating role of walking between perceived and objective walkability and cognitive function in older adults. Health Place 2023; 79:102943. [PMID: 36512954 PMCID: PMC9928909 DOI: 10.1016/j.healthplace.2022.102943] [Citation(s) in RCA: 3] [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: 05/26/2022] [Revised: 11/23/2022] [Accepted: 11/24/2022] [Indexed: 12/14/2022]
Abstract
The aim of this study was to examine the role of walking in explaining associations between perceived and objective measures of walkability and cognitive function among older adults. The study employed a cross-sectional design analyzing existing data. Data were obtained from the Adult Changes in Thought Activity Monitor study. Cognitive function and perceived walkability were measured by a survey. Objective walkability was measured using geographic information systems (GIS). Walking was measured using an accelerometer. We tested the mediating relationship based on 1,000 bootstrapped samples. Perceived walkability was associated with a 0.04 point higher cognitive function score through walking (p = 0.006). The mediating relationship accounted for 34% of the total relationship between perceived walkability and cognitive function. Walking did not have a significant indirect relationship on the association between objective walkability and cognitive function. Perceived walkability may be more relevant to walking behavior than objective walkability among older adults. Greater levels of perceived walkability may encourage older adults to undertake more walking, and more walking may in turn improve cognitive function in older adults.
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Affiliation(s)
- Boeun Kim
- School of Nursing, Johns Hopkins University, Baltimore, MD, USA.
| | - Wendy E Barrington
- Child, Family, and Population Health Nursing, University of Washington, Seattle, WA, USA; Health Systems and Population Health Epidemiology, University of Washington, Seattle, WA, USA
| | - Adrian Dobra
- Department of Statistics, University of Washington, Seattle, WA, USA
| | - Dori Rosenberg
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Philip Hurvitz
- Center for Studies in Demography & Ecology, University of Washington, Seattle, WA, USA; Urban Form Lab, University of Washington, Seattle, WA, USA
| | - Basia Belza
- Biobehavioral Nursing and Health Informatics, University of Washington, Seattle, WA, USA
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Residential trajectories across the life course and their association with cognitive functioning in later life. Sci Rep 2022; 12:17004. [PMID: 36220827 PMCID: PMC9553870 DOI: 10.1038/s41598-022-18501-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 08/12/2022] [Indexed: 12/29/2022] Open
Abstract
Previous work has found that later life urban-rural differences in cognitive health can be largely explained by indicators of cognitive reserve such as education or occupation. However, previous research concentrated on residence in limited, specific, periods. This study offers a detailed investigation on the association between urban (vs. rural) residence from birth, and cognitive functioning in older age. Using data from the Survey of Health Ageing and Retirement in Europe we created residential trajectories from birth to survey enrolment with a combination of sequence and cluster analysis. Using mixed-effects models, we investigated the association between residential trajectories in early, mid, and later life and three cognitive functioning outcomes: immediate recall, delayed recall, and verbal fluency. In a sample of 38,165 participants, we found that, even after accounting for differences related to education and occupation, rural (vs. urban) residence in early life remained associated with poorer cognitive performance later in life. This suggests that growing up in rural regions leads to a long-term disadvantage in cognitive functioning. Thus, public health policies should consider that urban-rural inequalities in early life may have long-lasting associations with inequalities in cognitive health in old and very old age.
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Poudel GR, Barnett A, Akram M, Martino E, Knibbs LD, Anstey KJ, Shaw JE, Cerin E. Machine Learning for Prediction of Cognitive Health in Adults Using Sociodemographic, Neighbourhood Environmental, and Lifestyle Factors. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:10977. [PMID: 36078704 PMCID: PMC9517821 DOI: 10.3390/ijerph191710977] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 08/26/2022] [Accepted: 08/31/2022] [Indexed: 06/02/2023]
Abstract
The environment we live in, and our lifestyle within this environment, can shape our cognitive health. We investigated whether sociodemographic, neighbourhood environment, and lifestyle variables can be used to predict cognitive health status in adults. Cross-sectional data from the AusDiab3 study, an Australian cohort study of adults (34-97 years) (n = 4141) was used. Cognitive function was measured using processing speed and memory tests, which were categorized into distinct classes using latent profile analysis. Sociodemographic variables, measures of the built and natural environment estimated using geographic information system data, and physical activity and sedentary behaviours were used as predictors. Machine learning was performed using gradient boosting machine, support vector machine, artificial neural network, and linear models. Sociodemographic variables predicted processing speed (r2 = 0.43) and memory (r2 = 0.20) with good accuracy. Lifestyle factors also accurately predicted processing speed (r2 = 0.29) but weakly predicted memory (r2 = 0.10). Neighbourhood and built environment factors were weak predictors of cognitive function. Sociodemographic (AUC = 0.84) and lifestyle (AUC = 0.78) factors also accurately classified cognitive classes. Sociodemographic and lifestyle variables can predict cognitive function in adults. Machine learning tools are useful for population-level assessment of cognitive health status via readily available and easy-to-collect data.
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Affiliation(s)
- Govinda R. Poudel
- Mary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3065, Australia
| | - Anthony Barnett
- Mary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3065, Australia
| | - Muhammad Akram
- Mary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3065, Australia
| | - Erika Martino
- Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC 3010, Australia
| | - Luke D. Knibbs
- School of Public Health, The University of Sydney, Sydney, NSW 2006, Australia
- Public Health Unit, Sydney Local Health District, Camperdown, NSW 2050, Australia
| | - Kaarin J. Anstey
- School of Psychology, University of New South Wales, Sydney, NSW 2052, Australia
- UNSW Ageing Futures Institute, University of New South Wales, Sydney, NSW 2052, Australia
- Neuroscience Research Australia, Sydney, NSW 2031, Australia
| | - Jonathan E. Shaw
- Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia
| | - Ester Cerin
- Mary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3065, Australia
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Finlay J, Esposito M, Langa KM, Judd S, Clarke P. Cognability: An Ecological Theory of neighborhoods and cognitive aging. Soc Sci Med 2022; 309:115220. [PMID: 35926362 PMCID: PMC9661364 DOI: 10.1016/j.socscimed.2022.115220] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 05/19/2022] [Accepted: 07/13/2022] [Indexed: 11/17/2022]
Abstract
While a growing body of evidence points to potentially modifiable individual risk factors for dementia, the built and social environments in which people develop and navigate cognitive decline are largely overlooked. This paper proposes a new theoretical concept, Cognability, to conceptualize how supportive an area is to cognitive health among aging residents. Cognability incorporates a constellation of both positive and negative neighborhood features related to physical activity, social interaction and cognitive stimulation in later life. We analyzed data from the REasons for Geographic And Racial Differences in Stroke Study, a national sample of older Black and white adults in the United States (n = 21,151; mean age at assessment = 67; data collected 2006-2017). Generalized additive multilevel models examined how cognitive function varied by neighborhood features. Access to civic and social organizations, recreation centers, fast-food and coffee establishments, arts centers, museums, and highways were significantly associated with cognitive function. Race-, gender-, and education-specific models did not yield substantial improvements to the full-model. Our results suggest that the unequal distribution of amenities and hazards across neighborhoods may help account for considerable inequities observed in cognitive health among older adults. Cognability advances ecological theories of aging through an innovative "whole neighborhood" approach. It aims to identify which specific neighborhood features are most protective of cognitive health among aging adults to inform upstream public health initiatives, community interventions, and policy.
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Affiliation(s)
- Jessica Finlay
- Social Environment and Health Program, Institute for Social Research, University of Michigan, 426 Thompson Street, Ann Arbor, MI, 48104, United States; Center for Social Epidemiology and Population Health, Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, United States.
| | - Michael Esposito
- Department of Sociology, Washington University in St. Louis, St. Louis, MO, 63130, United States
| | - Kenneth M Langa
- Department of Internal Medicine, Division of General Medicine, 2800 Plymouth Road, Ann Arbor, MI, 48109, United States
| | - Suzanne Judd
- School of Public Health, University of Alabama at Birmingham, 1665 University Blvd, Birmingham, AL, 35233, United States
| | - Philippa Clarke
- Social Environment and Health Program, Institute for Social Research, University of Michigan, 426 Thompson Street, Ann Arbor, MI, 48104, United States; Center for Social Epidemiology and Population Health, Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, United States
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7
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Cerin E, Barnett A, Shaw JE, Martino E, Knibbs LD, Tham R, Wheeler AJ, Anstey KJ. Urban Neighbourhood Environments, Cardiometabolic Health and Cognitive Function: A National Cross-Sectional Study of Middle-Aged and Older Adults in Australia. TOXICS 2022; 10:23. [PMID: 35051065 PMCID: PMC8779212 DOI: 10.3390/toxics10010023] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 12/28/2021] [Accepted: 01/05/2022] [Indexed: 02/05/2023]
Abstract
Population ageing and urbanisation are global phenomena that call for an understanding of the impacts of features of the urban environment on older adults' cognitive function. Because neighbourhood characteristics that can potentially have opposite effects on cognitive function are interdependent, they need to be considered in conjunction. Using data from an Australian national sample of 4141 adult urban dwellers, we examined the extent to which the associations of interrelated built and natural environment features and ambient air pollution with cognitive function are explained by cardiometabolic risk factors relevant to cognitive health. All examined environmental features were directly and/or indirectly related to cognitive function via other environmental features and/or cardiometabolic risk factors. Findings suggest that dense, interconnected urban environments with access to parks, blue spaces and low levels of air pollution may benefit cognitive health through cardiometabolic risk factors and other mechanisms not captured in this study. This study also highlights the need for a particularly fine-grained characterisation of the built environment in research on cognitive function, which would enable the differentiation of the positive effects of destination-rich neighbourhoods on cognition via participation in cognition-enhancing activities from the negative effects of air pollutants typically present in dense, destination-rich urban areas.
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Affiliation(s)
- Ester Cerin
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3000, Australia; (A.B.); (R.T.); (A.J.W.)
- School of Public Health, The University of Hong Kong, Hong Kong, China
- Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia;
- Department of Community Medicine, UiT the Artic University of Norway, 9019 Tromsø, Norway
| | - Anthony Barnett
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3000, Australia; (A.B.); (R.T.); (A.J.W.)
| | - Jonathan E. Shaw
- Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia;
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
- School of Life Sciences, La Trobe University, Melbourne, VIC 3086, Australia
| | - Erika Martino
- School of Population and Global Health, University of Melbourne, Melbourne, VIC 3053, Australia;
| | - Luke D. Knibbs
- Sydney School of Public Health, The University of Sydney, Camperdown, NSW 2006, Australia;
| | - Rachel Tham
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3000, Australia; (A.B.); (R.T.); (A.J.W.)
| | - Amanda J. Wheeler
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3000, Australia; (A.B.); (R.T.); (A.J.W.)
- Menzies Institute for Medical Research, College of Health and Medicine, University of Tasmania, Hobart, TAS 7000, Australia
| | - Kaarin J. Anstey
- School of Psychology, University of New South Wales, Randwick, NSW 2052, Australia;
- Neuroscience Research Australia (NeuRA), Sydney, NSW 2031, Australia
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Abstract
With the expected rise in Alzheimer's disease and related dementias (ADRD) in the coming decades due to the aging population and a lack of effective disease-modifying treatments, there is a need for preventive strategies that may tap into resilience parameters. A wide array of resilience strategies has been proposed including genetics, socioeconomic status, lifestyle modifications, behavioral changes, and management of comorbid disease. These different strategies can be broadly classified as distinguishing between modifiable and non-modifiable risk factors, some of which can be quantified so that their clinical intervention can be effectively accomplished. A clear shift in research focus from dementia risk to addressing disease resistance and resilience is emerging that has provided new potential therapeutic targets. Here we review and summarize the latest investigations of resilience mechanisms and methods of quantifying resilience for clinical research. These approaches include identifying genetic variants that may help identify novel pathways (e.g., lipid metabolism, cellular trafficking, synaptic function, inflammation) for therapeutic treatments and biomarkers for use in a precision medicine-like regimen. In addition, innovative structural and molecular neuroimaging analyses may assist in detecting and quantifying pathological changes well before the onset of clinical symptoms setting up the possibility of primary and secondary prevention trials. Lastly, we summarize recent studies demonstrating the study of resilience in caregivers of persons living with dementia may have direct and indirect impact on the quality of care and patient outcomes.
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Affiliation(s)
- Mahesh S. Joshi
- Comprehensive Center for Brain Health, Department of Neurology, University of Miami Miller School of Medicine, Boca Raton, FL, USA
| | - James E. Galvin
- Comprehensive Center for Brain Health, Department of Neurology, University of Miami Miller School of Medicine, Boca Raton, FL, USA
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9
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Cerin E, Barnett A, Shaw JE, Martino E, Knibbs LD, Tham R, Wheeler AJ, Anstey KJ. From urban neighbourhood environments to cognitive health: a cross-sectional analysis of the role of physical activity and sedentary behaviours. BMC Public Health 2021; 21:2320. [PMID: 34949175 PMCID: PMC8705462 DOI: 10.1186/s12889-021-12375-3] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 12/05/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND There is a dearth of studies on the effects of the neighbourhood environment on adults' cognitive function. We examined how interrelated aspects of the built and natural neighbourhood environment, including air pollution, correlate with adults' cognitive function, and the roles of physical activity and sedentary behaviours in these associations. METHODS We used data from 4,141 adult urban dwellers who participated in the Australian Diabetes, Obesity and Lifestyle 3 study on socio-demographic characteristics, neighbourhood self-selection, physical activity and sedentary behaviours, and cognitive function. Neighbourhood environmental characteristics included population density, intersection density, non-commercial land use mix, and percentages of commercial land, parkland and blue space, all within 1 km residential buffers. We also calculated annual mean concentrations of NO2 and PM2.5. Generalised additive mixed models informed by directed acyclic graphs were used to estimate the total, direct and indirect effects of environmental attributes on cognitive functions and the joint-significance test was used to examine indirect effects via behaviours. RESULTS In the total effects models, population density and percentage of parkland were positively associated with cognitive function. A positive association of PM2.5 with memory was also observed. All neighbourhood environmental attributes were directly and/or indirectly related to cognitive functions via other environmental attributes and/or physical activity but not sedentary behaviours. Engagement in transportation walking and gardening frequency partially mediated the positive effects of the neighbourhood environment on cognitive function, while frequency of transportation walking mediated the negative effects. CONCLUSIONS In the context of a low-density country like Australia, denser urban environments with access to parkland may benefit residents' cognitive health by providing opportunities for participation in a diversity of activities. A more fine-grained characterisation of the neighbourhood environment may be necessary to tease out the negative and positive impacts of inter-related characteristics of urban neighbourhood environments on cognitive function.
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Affiliation(s)
- Ester Cerin
- Mary MacKillop Institute for Health Research, Australian Catholic University, Level 5, 215 Spring Street, Melbourne, Victoria, 3000, Australia.
- School of Public Health, The University of Hong Kong, 7 Sassoon Rd., Sandy Bay, Hong Kong, Hong Kong, SAR, China.
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.
- Department of Community Medicine, UiT The Artic University of Norway, Tromsø, Norway.
| | - Anthony Barnett
- Mary MacKillop Institute for Health Research, Australian Catholic University, Level 5, 215 Spring Street, Melbourne, Victoria, 3000, Australia
| | - Jonathan E Shaw
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- School of Life Sciences, La Trobe University, Melbourne, VIC, Australia
| | - Erika Martino
- School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
| | - Luke D Knibbs
- School of Public Health, The University of Sydney, Camperdown, NSW, Australia
- Centre for Air Pollution, Energy and Health Research, Glebe, NSW, Australia
| | - Rachel Tham
- Mary MacKillop Institute for Health Research, Australian Catholic University, Level 5, 215 Spring Street, Melbourne, Victoria, 3000, Australia
| | - Amanda J Wheeler
- Mary MacKillop Institute for Health Research, Australian Catholic University, Level 5, 215 Spring Street, Melbourne, Victoria, 3000, Australia
- Menzies Institute for Medical Research, College of Health and Medicine, University of Tasmania, Hobart, TAS, Australia
| | - Kaarin J Anstey
- School of Psychology, University of New South Wales, Randwick, NSW, Australia
- Neuroscience Research Australia (NeuRA), Sydney, Australia
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Bagheri N, Mavoa S, Tabatabaei-Jafari H, Knibbs LD, Coffee NT, Salvador-Carulla L, Anstey KJ. The Impact of Built and Social Environmental Characteristics on Diagnosed and Estimated Future Risk of Dementia. J Alzheimers Dis 2021; 84:621-632. [PMID: 34569946 DOI: 10.3233/jad-210208] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
BACKGROUND Dementia is a major global health challenge and the impact of built and social environments' characteristics on dementia risk have not yet been fully evaluated. OBJECTIVE To investigate associations between built and social environmental characteristics and diagnosed dementia cases and estimated dementia risk. METHODS We recruited 25,511 patients aged 65 and older from family physicians' practices. We calculated a dementia risk score based on risk and protective factors for patients not diagnosed with dementia. Our exposure variables were estimated for each statistical area level 1: social fragmentation, nitrogen dioxide, public open spaces, walkability, socio-economic status, and the length of main roads. We performed a multilevel mixed effect linear regression analysis to allow for the hierarchical nature of the data. RESULTS We found that a one standard deviation (1-SD) increase in NO2 and walkability score was associated with 10% higher odds of any versus no dementia (95% CI: 1%, 21% for NO2 and 0%, 22% for walkability score). For estimated future risk of dementia, a 1-SD increase in social fragmentation and NO2 was associated with a 1% increase in dementia risk (95% CI: 0, 1%). 1-SD increases in public open space and socioeconomic status were associated with 3% (95% CI: 0.95, 0.98) and 1% decreases (95% CI: 0.98, 0.99) in dementia risk, respectively. There was spatial heterogeneity in the pattern of diagnosed dementia and the estimated future risk of dementia. CONCLUSION Associations of neighborhood NO2 level, walkability, public open space, and social fragmentation with diagnosed dementia cases and estimated future risk of dementia were statistically significant, indicating the potential to reduce the risk through changes in built and social environments.
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Affiliation(s)
- Nasser Bagheri
- Centre for Mental Health Research, the Research School of Population Health, the Australian National University, Australia.,The Australian Geospatial Health Lab, Health Research Institute, The University of Canberra, Australia
| | - Suzanne Mavoa
- Melbourne School of Population and Global Health, the University of Melbourne, Australia
| | - Hossein Tabatabaei-Jafari
- Centre for Mental Health Research, the Research School of Population Health, the Australian National University, Australia
| | - Luke D Knibbs
- The School of Public Health, The University of Sydney, Australia
| | - Neil T Coffee
- The Australian Geospatial Health Lab, Health Research Institute, The University of Canberra, Australia
| | - Luis Salvador-Carulla
- Centre for Mental Health Research, the Research School of Population Health, the Australian National University, Australia.,Menzies Centre for Health Policy, Faculty of Medicine and Health, University of Sydney
| | - Kaarin J Anstey
- UNSW Ageing Futures Institute, the University of New South Wales, Australia.,Neuroscience Research Australia, Australia
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11
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Besser LM, Lovasi GS, Michael YL, Garg P, Hirsch JA, Siscovick D, Hurvitz P, Biggs ML, Galvin JE, Bartz TM, Longstreth WT. Associations between neighborhood greenspace and brain imaging measures in non-demented older adults: the Cardiovascular Health Study. Soc Psychiatry Psychiatr Epidemiol 2021; 56:1575-1585. [PMID: 33388800 PMCID: PMC8253869 DOI: 10.1007/s00127-020-02000-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 11/25/2020] [Indexed: 12/12/2022]
Abstract
PURPOSE Greater neighborhood greenspace has been associated with brain health, including better cognition and lower odds of Alzheimer's disease in older adults. We investigated associations between neighborhood greenspace and brain-based magnetic resonance imaging (MRI) measures and potential effect modification by sex or apolipoprotein E genotype (APOE), a risk factor for Alzheimer's disease. METHODS We obtained a sample of non-demented participants 65 years or older (n = 1125) from the longitudinal, population-based Cardiovascular Health Study (CHS). Greenspace data were derived from the National Land Cover Dataset. Adjusted multivariable linear regression estimated associations between neighborhood greenspace five years prior to the MRI and left and right hippocampal volume and 10-point grades of ventricular size and burden of white matter hyperintensity. Interaction terms tested effect modification by APOE genotype and sex. CHS data (1989-1999) were obtained/analyzed in 2020. RESULTS Participants were on average 79 years old [standard deviation (SD) = 4], 58% were female, and 11% were non-white race. Mean neighborhood greenspace was 38% (SD = 28%). Greater proportion of greenspace in the neighborhood five years before MRI was borderline associated with lower ventricle grade (estimate: - 0.30; 95% confidence interval: - 0.61, 0.00). We observed no associations between greenspace and the other MRI outcome measures and no evidence of effect modification by APOE genotype and sex. CONCLUSION This study suggests a possible association between greater greenspace and less ventricular enlargement, a measure reflecting global brain atrophy. If confirmed in other longitudinal cohort studies, interventions and policies to improve community greenspaces may help to maintain brain health in older age.
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Affiliation(s)
- Lilah M Besser
- Institute for Human Health and Disease Intervention, Department of Urban and Regional Planning, Florida Atlantic University, 777 Glades Rd, SO-44, Room 284H, Boca Raton, FL, 33431, USA.
| | - Gina S Lovasi
- Urban Health Collaborative and Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, 19104, USA
| | - Yvonne L Michael
- Department of Epidemiology and Biostatistics, Dornslife School of Public Health, Drexel University, Philadelphia, PA, 19104, USA
| | - Parveen Garg
- Division of Cardiology, Keck School of Medicine, University of Southern California, 1510 San Pablo Street Suite #322, Los Angeles, CA, 90033, USA
| | - Jana A Hirsch
- Urban Health Collaborative and Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, 19104, USA
| | - David Siscovick
- Division of Research, Evaluation, and Policy, The New York Academy of Medicine, New York, NY, 10029, USA
| | - Phil Hurvitz
- Center for Studies in Demography and Ecology and Urban Form Lab, University of Washington, Seattle, WA, 98195, USA
| | - Mary L Biggs
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - James E Galvin
- Comprehensive Center for Brain Health, Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL, 33136, USA
| | - Traci M Bartz
- Department of Biostatistics, University of Washington, Seattle, WA, 98195, USA
| | - W T Longstreth
- Departments of Neurology and Epidemiology, University of Washington, Seattle, WA, 98195-9775, USA
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12
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Methods to Address Self-Selection and Reverse Causation in Studies of Neighborhood Environments and Brain Health. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18126484. [PMID: 34208454 PMCID: PMC8296350 DOI: 10.3390/ijerph18126484] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Revised: 06/11/2021] [Accepted: 06/13/2021] [Indexed: 11/17/2022]
Abstract
Preliminary evidence suggests that neighborhood environments, such as socioeconomic disadvantage, pedestrian and physical activity infrastructure, and availability of neighborhood destinations (e.g., parks), may be associated with late-life cognitive functioning and risk of Alzheimer’s disease and related disorders (ADRD). The supposition is that these neighborhood characteristics are associated with factors such as mental health, environmental exposures, health behaviors, and social determinants of health that in turn promote or diminish cognitive reserve and resilience in later life. However, observed associations may be biased by self-selection or reverse causation, such as when individuals with better cognition move to denser neighborhoods because they prefer many destinations within walking distance of home, or when individuals with deteriorating health choose residences offering health services in neighborhoods in rural or suburban areas (e.g., assisted living). Research on neighborhood environments and ADRD has typically focused on late-life brain health outcomes, which makes it difficult to disentangle true associations from associations that result from reverse causality. In this paper, we review study designs and methods to help reduce bias due to reverse causality and self-selection, while drawing attention to the unique aspects of these approaches when conducting research on neighborhoods and brain aging.
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Cerin E, Yin S, Choi WK, Ngan W, Tham R, Barnett A. Development of Measures of Perceived Neighborhood Environmental Attributes Influencing, and Perceived Barriers to Engagement in, Healthy Behaviors for Older Chinese Immigrants to Australia. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18094531. [PMID: 33923306 PMCID: PMC8123107 DOI: 10.3390/ijerph18094531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 04/20/2021] [Accepted: 04/22/2021] [Indexed: 11/16/2022]
Abstract
Environmental correlates, barriers, and facilitators of physical activity, healthy eating, and socializing are understudied in older immigrants to developed countries. This study developed/adapted and validated measures of perceived barriers and neighborhood environmental characteristics related to these health-enhancing behaviors appropriate for older Chinese immigrants to Australia and similar Western countries. Older Chinese immigrants living in Melbourne (Australia) were recruited from neighborhoods varying in walkability and percentage of Chinese residents. Versions of the Neighborhood Environment for Healthy Aging–Chinese Immigrants to Australia (NEHA-CIA) questionnaire (20 subscales) and the Perceived Barriers to Health-Enhancing Behaviors questionnaire (four subscales) were developed from extant validated scales and information collected in formative qualitative research. Thirty-one participants took part in cognitive interviews aimed to pilot-test and refine the questionnaires. The modified questionnaires were administered to 52 participants twice, two weeks apart. Test-retest reliability (intraclass correlation coefficients), internal consistency (Cronbach’s α), and construct validity (associations with theoretically-relevant constructs) were examined. Most items and subscales of both questionnaires had good test-retest reliability and internal consistency, while the NEHA-CIA also showed good construct validity. Future studies need to further examine the construct validity of the questionnaire of perceived barriers and determine the factorial validity of both measures on large representative samples.
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Affiliation(s)
- Ester Cerin
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3000, Australia; (W.K.C.); (R.T.); (A.B.)
- School of Public Health, The University of Hong Kong, Pokfulam, Hong Kong, China
- Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia
- Correspondence: ; Tel.: +61-3-9230-8260
| | - Shiyuan Yin
- School of Exercise and Nutrition Science, Deakin University, Burwood, VIC 3125, Australia; (S.Y.); (W.N.)
| | - Wing Ka Choi
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3000, Australia; (W.K.C.); (R.T.); (A.B.)
| | - Winsfred Ngan
- School of Exercise and Nutrition Science, Deakin University, Burwood, VIC 3125, Australia; (S.Y.); (W.N.)
| | - Rachel Tham
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3000, Australia; (W.K.C.); (R.T.); (A.B.)
| | - Anthony Barnett
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3000, Australia; (W.K.C.); (R.T.); (A.B.)
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14
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Kim R, Park S, Yoo D, Jun JS, Jeon B. Association of Physical Activity and APOE Genotype With Longitudinal Cognitive Change in Early Parkinson Disease. Neurology 2021; 96:e2429-e2437. [PMID: 33790041 DOI: 10.1212/wnl.0000000000011852] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Accepted: 02/10/2021] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To determine whether greater physical activity could modify the negative association of APOE ε4 with longitudinal cognitive changes in early Parkinson disease (PD) and to uncover the disease-specific mechanism for explaining such benefits of physical activity. METHODS We used data from the Parkinson's Progression Markers Initiative cohort. Because self-reported physical activity, measured by the Physical Activity Scale of the Elderly, was initiated at 2 years after enrollment, this longitudinal analysis was based on assessments performed at years 2, 3, and 4. Cognitive function was measured annually with the Montreal Cognitive Assessment (MoCA). Dopamine transporter (DAT) imaging was performed at years 2 and 4. We assessed the interactive associations between physical activity and the APOE ε4 allele on the longitudinal changes in MoCA scores and striatal DAT activities. RESULTS A total of 173 patients with early PD (age 63.3 ± 10.0 years, 27% APOE ε4 carriers) were included. The APOE ε4 allele showed a steeper rate of cognitive decline than the non-APOE ε4 allele (estimate -1.33, 95% confidence interval [CI] -2.12 to -0.47, p = 0.002). However, there was a significant interaction between physical activity and APOE ε4 such that higher physical activity was related to slower APOE ε4-related cognitive decline (estimate 0.007, 95% CI 0.003-0.011, p = 0.001). No significant interaction was found between physical activity and the APOE ε4 allele regarding the change in striatal DAT activities. CONCLUSION Increased physical activity attenuated APOE ε4-related vulnerability to early cognitive decline in patients with PD. This protective effect did not appear to be mediated by striatal dopaminergic function. TRIAL REGISTRATION INFORMATION ClinicalTrials.gov Identifier: NCT01141023. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that increased physical activity was associated with decreased APOE ε4-related early cognitive decline in patients with PD.
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Affiliation(s)
- Ryul Kim
- From the Department of Neurology (R.K.), Inha University Hospital, Incheon; Department of Neurology (S.P.), School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu; Department of Neurology (D.Y.), Kyung Hee University Hospital; Department of Neurology (J.-S.J.), Kangnam Sacred Heart Hospital, Hallym University College of Medicine; and Department of Neurology (B.J.), College of Medicine, Seoul National University Hospital, Korea
| | - Sangmin Park
- From the Department of Neurology (R.K.), Inha University Hospital, Incheon; Department of Neurology (S.P.), School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu; Department of Neurology (D.Y.), Kyung Hee University Hospital; Department of Neurology (J.-S.J.), Kangnam Sacred Heart Hospital, Hallym University College of Medicine; and Department of Neurology (B.J.), College of Medicine, Seoul National University Hospital, Korea
| | - Dallah Yoo
- From the Department of Neurology (R.K.), Inha University Hospital, Incheon; Department of Neurology (S.P.), School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu; Department of Neurology (D.Y.), Kyung Hee University Hospital; Department of Neurology (J.-S.J.), Kangnam Sacred Heart Hospital, Hallym University College of Medicine; and Department of Neurology (B.J.), College of Medicine, Seoul National University Hospital, Korea
| | - Jin-Sun Jun
- From the Department of Neurology (R.K.), Inha University Hospital, Incheon; Department of Neurology (S.P.), School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu; Department of Neurology (D.Y.), Kyung Hee University Hospital; Department of Neurology (J.-S.J.), Kangnam Sacred Heart Hospital, Hallym University College of Medicine; and Department of Neurology (B.J.), College of Medicine, Seoul National University Hospital, Korea.
| | - Beomseok Jeon
- From the Department of Neurology (R.K.), Inha University Hospital, Incheon; Department of Neurology (S.P.), School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu; Department of Neurology (D.Y.), Kyung Hee University Hospital; Department of Neurology (J.-S.J.), Kangnam Sacred Heart Hospital, Hallym University College of Medicine; and Department of Neurology (B.J.), College of Medicine, Seoul National University Hospital, Korea
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15
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de Frutos-Lucas J, Cuesta P, López-Sanz D, Peral-Suárez Á, Cuadrado-Soto E, Ramírez-Toraño F, Brown BM, Serrano JM, Laws SM, Rodríguez-Rojo IC, Verdejo-Román J, Bruña R, Delgado-Losada ML, Barabash A, López-Sobaler AM, López-Higes R, Marcos A, Maestú F. The relationship between physical activity, apolipoprotein E ε4 carriage, and brain health. Alzheimers Res Ther 2020; 12:48. [PMID: 32331531 PMCID: PMC7183121 DOI: 10.1186/s13195-020-00608-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2020] [Accepted: 03/30/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND Neuronal hyperexcitability and hypersynchrony have been described as key features of neurophysiological dysfunctions in the Alzheimer's disease (AD) continuum. Conversely, physical activity (PA) has been associated with improved brain health and reduced AD risk. However, there is controversy regarding whether AD genetic risk (in terms of APOE ε4 carriage) modulates these relationships. The utilization of multiple outcome measures within one sample may strengthen our understanding of this complex phenomenon. METHOD The relationship between PA and functional connectivity (FC) was examined in a sample of 107 healthy older adults using magnetoencephalography. Additionally, we explored whether ε4 carriage modulates this association. The correlation between FC and brain structural integrity, cognition, and mood was also investigated. RESULTS A relationship between higher PA and decreased FC (hyposynchrony) in the left temporal lobe was observed among all individuals (across the whole sample, in ε4 carriers, and in ε4 non-carriers), but its effects manifest differently according to genetic risk. In ε4 carriers, we report an association between this region-specific FC profile and preserved brain structure (greater gray matter volumes and higher integrity of white matter tracts). In this group, decreased FC also correlated with reduced anxiety levels. In ε4 non-carriers, this profile is associated with improved cognition (working and episodic memory). CONCLUSIONS PA could mitigate the increase in FC (hypersynchronization) that characterizes preclinical AD, being beneficial for all individuals, especially ε4 carriers.
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Affiliation(s)
- Jaisalmer de Frutos-Lucas
- Biological and Health Psychology Department, School of Psychology, Universidad Autonoma de Madrid, 28049, Madrid, Spain.
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain.
- Collaborative Genomics Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia.
| | - Pablo Cuesta
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Department of Industrial Engineering & IUNE, Universidad de La Laguna, 38200, San Cristobal de la Laguna, Tenerife, Spain
| | - David López-Sanz
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Department of Psychobiology and Methodology in Behavioral Sciences, School of Education, Universidad Complutense de Madrid, 28040, Madrid, Spain
| | - África Peral-Suárez
- Departamento de Nutricion y Ciencia de los Alimentos, Facultad de Farmacia, Universidad Complutense de Madrid, 28040, Madrid, Spain
| | - Esther Cuadrado-Soto
- Departamento de Nutricion y Ciencia de los Alimentos, Facultad de Farmacia, Universidad Complutense de Madrid, 28040, Madrid, Spain
| | - Federico Ramírez-Toraño
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
| | - Belinda M Brown
- Discipline of Exercise Science, College of Science, Health, Engineering and Education, Murdoch University, Murdoch, Western Australia, 6150, Australia
| | - Juan M Serrano
- Biological and Health Psychology Department, School of Psychology, Universidad Autonoma de Madrid, 28049, Madrid, Spain
| | - Simon M Laws
- Collaborative Genomics Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia
- School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, Western Australia, 6102, Australia
| | - Inmaculada C Rodríguez-Rojo
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Centro Universitario Villanueva, Facultad de Psicología, 28034, Madrid, Spain
| | - Juan Verdejo-Román
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
- Mind, Brain and Behavior Research Center (CIMCYC), Universidad de Granada, 18071, Granada, Spain
| | - Ricardo Bruña
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
- Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), 28029, Madrid, Spain
| | - Maria L Delgado-Losada
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
| | - Ana Barabash
- Endocrinology and Nutrition Department, Hospital Clinico San Carlos and Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, 28040, Madrid, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas, 28040, Madrid, Spain
| | - Ana M López-Sobaler
- Departamento de Nutricion y Ciencia de los Alimentos, Facultad de Farmacia, Universidad Complutense de Madrid, 28040, Madrid, Spain
| | - Ramón López-Higes
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
| | - Alberto Marcos
- Neurology Department, Hospital Clinico San Carlos and Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, 28040, Madrid, Spain
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
- Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), 28029, Madrid, Spain
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Cerin E, Barnett A, Chaix B, Nieuwenhuijsen MJ, Caeyenberghs K, Jalaludin B, Sugiyama T, Sallis JF, Lautenschlager NT, Ni MY, Poudel G, Donaire-Gonzalez D, Tham R, Wheeler AJ, Knibbs L, Tian L, Chan YK, Dunstan DW, Carver A, Anstey KJ. International Mind, Activities and Urban Places (iMAP) study: methods of a cohort study on environmental and lifestyle influences on brain and cognitive health. BMJ Open 2020; 10:e036607. [PMID: 32193278 PMCID: PMC7202706 DOI: 10.1136/bmjopen-2019-036607] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
INTRODUCTION Numerous studies have found associations between characteristics of urban environments and risk factors for dementia and cognitive decline, such as physical inactivity and obesity. However, the contribution of urban environments to brain and cognitive health has been seldom examined directly. This cohort study investigates the extent to which and how a wide range of characteristics of urban environments influence brain and cognitive health via lifestyle behaviours in mid-aged and older adults in three cities across three continents. METHODS AND ANALYSIS Participants aged 50-79 years and living in preselected areas stratified by walkability, air pollution and socioeconomic status are being recruited in Melbourne (Australia), Barcelona (Spain) and Hong Kong (China) (n=1800 total; 600 per site). Two assessments taken 24 months apart will capture changes in brain and cognitive health. Cognitive function is gauged with a battery of eight standardised tests. Brain health is assessed using MRI scans in a subset of participants. Information on participants' visited locations is collected via an interactive web-based mapping application and smartphone geolocation data. Environmental characteristics of visited locations, including the built and natural environments and their by-products (e.g., air pollution), are assessed using geographical information systems, online environmental audits and self-reports. Data on travel and lifestyle behaviours (e.g., physical and social activities) and participants' characteristics (e.g., sociodemographics) are collected using objective and/or self-report measures. ETHICS AND DISSEMINATION The study has been approved by the Human Research Ethics Committee of the Australian Catholic University, the Institutional Review Board of the University of Hong Kong and the Parc de Salut Mar Clinical Research Ethics Committee of the Government of Catalonia. Results will be communicated through standard scientific channels. Methods will be made freely available via a study-dedicated website. TRIAL REGISTRATION NUMBER ACTRN12619000817145.
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Affiliation(s)
- Ester Cerin
- Mary MacKillop Inst Health Res, Australian Catholic University, Melbourne, Victoria, Australia
- School of Public Health, University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Anthony Barnett
- Mary MacKillop Inst Health Res, Australian Catholic University, Melbourne, Victoria, Australia
| | - Basile Chaix
- INSERM, Institut Pierre Louis d'Épidémiologie et de Santé Publique, Sorbonne Université, Paris, Île-de-France, France
| | | | - Karen Caeyenberghs
- Cognitive Neurosciences Unit, Deakin University, Burwood, Victoria, Australia
| | - Bin Jalaludin
- Population Health Intelligence, Healthy People and Places Unit, South Western Sydney Local Health District, Sydney, New South Wales, Australia
| | - Takemi Sugiyama
- Mary MacKillop Inst Health Res, Australian Catholic University, Melbourne, Victoria, Australia
- Centre for Urban Transitions, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - James F Sallis
- Mary MacKillop Inst Health Res, Australian Catholic University, Melbourne, Victoria, Australia
- Department of Family Medicine and Public Health, University of California San Diego, La Jolla, California, USA
| | | | - Michael Y Ni
- School of Public Health, University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Govinda Poudel
- Mary MacKillop Inst Health Res, Australian Catholic University, Melbourne, Victoria, Australia
| | - David Donaire-Gonzalez
- Mary MacKillop Inst Health Res, Australian Catholic University, Melbourne, Victoria, Australia
| | - Rachel Tham
- Mary MacKillop Inst Health Res, Australian Catholic University, Melbourne, Victoria, Australia
| | - Amanda J Wheeler
- Mary MacKillop Inst Health Res, Australian Catholic University, Melbourne, Victoria, Australia
| | - Luke Knibbs
- School of Public Health, The University of Queensland, Herston, Queensland, Australia
| | - Linwei Tian
- School of Public Health, University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Yih-Kai Chan
- Mary MacKillop Inst Health Res, Australian Catholic University, Melbourne, Victoria, Australia
| | - David W Dunstan
- Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Alison Carver
- Mary MacKillop Inst Health Res, Australian Catholic University, Melbourne, Victoria, Australia
| | - Kaarin J Anstey
- UNSW Ageing Futures Institute and School of Psychology, University of New South Wales, Sydney, New South Wales, Australia
- Neuroscience Research Australia, Randwick, New South Wales, Australia
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17
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Cerin E. Building the evidence for an ecological model of cognitive health. Health Place 2019; 60:102206. [PMID: 31797770 DOI: 10.1016/j.healthplace.2019.102206] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Accepted: 09/10/2019] [Indexed: 10/25/2022]
Abstract
This is a commentary on Besser and colleagues' article "Associations between neighbourhood built environment and cognition vary by apolipoprotein E genotype: Multi-Ethnic Study on Atherosclerosis" published in Health & Place. Unlike previous studies, the authors found significant environment-cognition associations in apolipoprotein E (APOE) ε2 carriers and no significant associations in ε4 carriers. This commentary discusses the possible reasons for these findings and, in doing so, proposes an ecological model of cognitive health. The model highlights the importance of accounting for multiple environmental influences including the built and natural environment and air and noise pollution indicators. It also stresses the importance of studying the underlying biological mechanisms explaining differences in environment-cognition associations across APOE genotype categories.
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Affiliation(s)
- Ester Cerin
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia; School of Public Health, The University of Hong Kong, Hong Kong, China.
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18
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Besser L, Galvin JE, Rodriguez D, Seeman T, Kukull W, Rapp SR, Smith J. Associations between neighborhood built environment and cognition vary by apolipoprotein E genotype: Multi-Ethnic Study of Atherosclerosis. Health Place 2019; 60:102188. [PMID: 31797769 PMCID: PMC6901106 DOI: 10.1016/j.healthplace.2019.102188] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Revised: 07/26/2019] [Accepted: 08/07/2019] [Indexed: 01/02/2023]
Abstract
We examined whether neighborhood built environment (BE) and cognition associations in older adults vary by apolipoprotein E (APOE) genotype, a genetic risk factor for Alzheimer's disease (AD). We conducted a cross-sectional analysis of 4091 participants. Neighborhood characteristics included social and walking destination density (SDD, WDD), intersection density, and proportion of land dedicated to retail. Individuals were categorized as APOE ε2 (lower AD risk), APOE ε4 (higher AD risk), or APOE ε3 carriers. Among APOE ε2 carriers, greater proportion of land dedicated to retail was associated with better global cognition, and greater SDD, WDD, intersection density, and proportion of land dedicated to retail was associated with better processing speed. These associations were not observed in APOE ε3 or ε4 carriers. APOE ε2 carriers may be more susceptible to the potentially beneficial effects of denser neighborhood BEs on cognition; however, longitudinal studies are needed.
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Affiliation(s)
- Lilah Besser
- School of Urban and Regional Planning, Institute for Human Health and Disease Intervention, Florida Atlantic University, 777 Glades Rd, SO-284H, Boca Raton, FL, 33431, USA.
| | - James E Galvin
- Charles E. Schmidt College of Medicine, Florida Atlantic University, 777 Glades Rd, ME-104, First Floor, Boca Raton, FL, 33431, USA.
| | - Daniel Rodriguez
- Department of City and Regional Planning, College of Environmental Design, Office 313B, Wurster Hall #1820, University of California, Berkeley, CA, 94720-1820, USA.
| | - Teresa Seeman
- David Geffen School of Medicine, University of California Los Angeles, 10945 Le Conte Avenue, Suite 2339 (PVUB Uberroth Building), Los Angeles, CA, 90095, USA.
| | - Walter Kukull
- National Alzheimer's Coordinating Center, Department of Epidemiology, University of Washington, 4311 11th Avenue NE, Suite 300, Seattle, WA, 98105, USA.
| | - Stephen R Rapp
- Departments of Psychiatry and Behavioral Medicine & Public Health Sciences, Wake Forest School of Medicine, 791 Jonestown Road, Winston-Salem, NC, 27103, USA.
| | - Jennifer Smith
- Department of Epidemiology, University of Michigan, 1415 Washington Heights, Room 2631, Ann Arbor, MI, 48109-2029, USA.
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Padgham M, Boeing G, Cooley D, Tierney N, Sumner M, Phan TG, Beare R. An Introduction to Software Tools, Data, and Services for Geospatial Analysis of Stroke Services. Front Neurol 2019; 10:743. [PMID: 31440197 PMCID: PMC6693386 DOI: 10.3389/fneur.2019.00743] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2019] [Accepted: 06/25/2019] [Indexed: 12/01/2022] Open
Abstract
Background: There is interest in the use geospatial data for development of acute stroke services given the importance of timely access to acute reperfusion therapy. This paper aims to introduce clinicians and citizen scientists to the possibilities offered by open source softwares (R and Python) for analyzing geospatial data. It is hoped that this introduction will stimulate interest in the field as well as generate ideas for improving stroke services. Method: Instructions on installation of libraries for R and Python, source codes and links to census data are provided in a notebook format to enhance experience with running the software. The code illustrates different aspects of using geospatial analysis: (1) creation of choropleth (thematic) map which depicts estimate of stroke cases per post codes; (2) use of map to help define service regions for rehabilitation after stroke. Results: Choropleth map showing estimate of stroke per post codes and service boundary map for rehabilitation after stroke. Conclusions The examples in this article illustrate the use of a range of components that underpin geospatial analysis. By providing an accessible introduction to these areas, clinicians and researchers can create code to answer clinically relevant questions on topics such as service delivery and service demand.
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Affiliation(s)
| | - Geoff Boeing
- School of Public Policy and Urban Affairs, Northeastern University, Boston, MA, United States
| | | | - Nicholas Tierney
- Department of Econometrics and Business Statistics, Monash University, Melbourne, VIC, Australia
| | - Michael Sumner
- Australian Antarctic Division, Department of the Environment and Energy, Kingston, TAS, Australia
| | - Thanh G Phan
- Clinical Trials Imaging and Informatics Division of Stroke and Aging Research Group, Monash University, Melbourne, VIC, Australia.,Stroke Unit, Monash Medical Centre, Melbourne, VIC, Australia
| | - Richard Beare
- Department of Medicine, Monash University, Melbourne, VIC, Australia.,Developmental Imaging, Murdoch Children's Research Institute, Melbourne, VIC, Australia
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20
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de Frutos-Lucas J, López-Sanz D, Zuluaga P, Rodríguez-Rojo IC, Luna R, López ME, Delgado-Losada ML, Marcos A, Barabash A, López-Higes R, Maestú F, Fernández A. Physical activity effects on the individual alpha peak frequency of older adults with and without genetic risk factors for Alzheimer’s Disease: A MEG study. Clin Neurophysiol 2018; 129:1981-1989. [DOI: 10.1016/j.clinph.2018.06.026] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2018] [Revised: 05/29/2018] [Accepted: 06/25/2018] [Indexed: 11/30/2022]
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21
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Barnett DW, Barnett A, Nathan A, Van Cauwenberg J, Cerin E. Built environmental correlates of older adults' total physical activity and walking: a systematic review and meta-analysis. Int J Behav Nutr Phys Act 2017; 14:103. [PMID: 28784183 PMCID: PMC5547528 DOI: 10.1186/s12966-017-0558-z] [Citation(s) in RCA: 369] [Impact Index Per Article: 52.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2017] [Accepted: 07/31/2017] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND Identifying attributes of the built environment associated with health-enhancing levels of physical activity (PA) in older adults (≥65 years old) has the potential to inform interventions supporting healthy and active ageing. The aim of this study was to first systematically review and quantify findings on built environmental correlates of older adults' PA, and second, investigate differences by type of PA and environmental attribute measurement. METHODS One hundred articles from peer-reviewed and grey literature examining built environmental attributes related to total PA met inclusion criteria and relevant information was extracted. Findings were meta-analysed and weighted by article quality and sample size and then stratified by PA and environmental measurement method. Associations (p < .05) were found in relation to 26 individual built environmental attributes across six categories (walkability, residential density/urbanisation, street connectivity, access to/availability of destinations and services, infrastructure and streetscape, and safety) and total PA and walking specifically. Reported individual- and environmental-level moderators were also examined. RESULTS Positive environmental correlates of PA, ranked by strength of evidence, were: walkability (p < .001), safety from crime (p < .001), overall access to destinations and services (p < .001), recreational facilities (p < .001), parks/public open space (p = .002) and shops/commercial destinations (p = .006), greenery and aesthetically pleasing scenery (p = .004), walk-friendly infrastructure (p = .009), and access to public transport (p = .016). There were 26 individual differences in the number of significant associations when the type of PA and environmental measurement method was considered. No consistent moderating effects on the association between built environmental attributes and PA were found. CONCLUSIONS Safe, walkable, and aesthetically pleasing neighbourhoods, with access to overall and specific destinations and services positively influenced older adults' PA participation. However, when considering the environmental attributes that were sufficiently studied (i.e., in ≥5 separate findings), the strength of evidence of associations of specific categories of environment attributes with PA differed across PA and environmental measurement types. Future research should be mindful of these differences in findings and identify the underlying mechanisms. Higher quality research is also needed.
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Affiliation(s)
- David W. Barnett
- Institute for Health and Ageing, Australian Catholic University, Level 6, 215 Spring Street, Melbourne, VIC 3000 Australia
| | - Anthony Barnett
- Institute for Health and Ageing, Australian Catholic University, Level 6, 215 Spring Street, Melbourne, VIC 3000 Australia
| | - Andrea Nathan
- Institute for Health and Ageing, Australian Catholic University, Level 6, 215 Spring Street, Melbourne, VIC 3000 Australia
| | - Jelle Van Cauwenberg
- Department of Public Health, Ghent University, De Pintelaan 185, 9000 Ghent, Belgium
- Research Foundation Flanders, Egmontstraat 5, 1000 Brussels, Belgium
| | - Ester Cerin
- Institute for Health and Ageing, Australian Catholic University, Level 6, 215 Spring Street, Melbourne, VIC 3000 Australia
- School of Public Health, The University of Hong Kong, 7 Sassoon Road, Pokfulam, Hong Kong, Special Administrative Region China
- Baker IDI Heart and Diabetes Institute, 75 Commercial Road, Melbourne, VIC 3004 Australia
| | - on behalf of the Council on Environment and Physical Activity (CEPA) – Older Adults working group
- Institute for Health and Ageing, Australian Catholic University, Level 6, 215 Spring Street, Melbourne, VIC 3000 Australia
- Department of Public Health, Ghent University, De Pintelaan 185, 9000 Ghent, Belgium
- Research Foundation Flanders, Egmontstraat 5, 1000 Brussels, Belgium
- School of Public Health, The University of Hong Kong, 7 Sassoon Road, Pokfulam, Hong Kong, Special Administrative Region China
- Baker IDI Heart and Diabetes Institute, 75 Commercial Road, Melbourne, VIC 3004 Australia
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22
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Barnett DW, Barnett A, Nathan A, Van Cauwenberg J, Cerin E. Built environmental correlates of older adults' total physical activity and walking: a systematic review and meta-analysis. Int J Behav Nutr Phys Act 2017. [PMID: 28784183 DOI: 10.1186/sl2966-017-0558-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/20/2023] Open
Abstract
BACKGROUND Identifying attributes of the built environment associated with health-enhancing levels of physical activity (PA) in older adults (≥65 years old) has the potential to inform interventions supporting healthy and active ageing. The aim of this study was to first systematically review and quantify findings on built environmental correlates of older adults' PA, and second, investigate differences by type of PA and environmental attribute measurement. METHODS One hundred articles from peer-reviewed and grey literature examining built environmental attributes related to total PA met inclusion criteria and relevant information was extracted. Findings were meta-analysed and weighted by article quality and sample size and then stratified by PA and environmental measurement method. Associations (p < .05) were found in relation to 26 individual built environmental attributes across six categories (walkability, residential density/urbanisation, street connectivity, access to/availability of destinations and services, infrastructure and streetscape, and safety) and total PA and walking specifically. Reported individual- and environmental-level moderators were also examined. RESULTS Positive environmental correlates of PA, ranked by strength of evidence, were: walkability (p < .001), safety from crime (p < .001), overall access to destinations and services (p < .001), recreational facilities (p < .001), parks/public open space (p = .002) and shops/commercial destinations (p = .006), greenery and aesthetically pleasing scenery (p = .004), walk-friendly infrastructure (p = .009), and access to public transport (p = .016). There were 26 individual differences in the number of significant associations when the type of PA and environmental measurement method was considered. No consistent moderating effects on the association between built environmental attributes and PA were found. CONCLUSIONS Safe, walkable, and aesthetically pleasing neighbourhoods, with access to overall and specific destinations and services positively influenced older adults' PA participation. However, when considering the environmental attributes that were sufficiently studied (i.e., in ≥5 separate findings), the strength of evidence of associations of specific categories of environment attributes with PA differed across PA and environmental measurement types. Future research should be mindful of these differences in findings and identify the underlying mechanisms. Higher quality research is also needed.
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Affiliation(s)
- David W Barnett
- Institute for Health and Ageing, Australian Catholic University, Level 6, 215 Spring Street, Melbourne, VIC, 3000, Australia
| | - Anthony Barnett
- Institute for Health and Ageing, Australian Catholic University, Level 6, 215 Spring Street, Melbourne, VIC, 3000, Australia
| | - Andrea Nathan
- Institute for Health and Ageing, Australian Catholic University, Level 6, 215 Spring Street, Melbourne, VIC, 3000, Australia
| | - Jelle Van Cauwenberg
- Department of Public Health, Ghent University, De Pintelaan 185, 9000, Ghent, Belgium
- Research Foundation Flanders, Egmontstraat 5, 1000, Brussels, Belgium
| | - Ester Cerin
- Institute for Health and Ageing, Australian Catholic University, Level 6, 215 Spring Street, Melbourne, VIC, 3000, Australia.
- School of Public Health, The University of Hong Kong, 7 Sassoon Road, Pokfulam, Hong Kong, Special Administrative Region, China.
- Baker IDI Heart and Diabetes Institute, 75 Commercial Road, Melbourne, VIC, 3004, Australia.
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23
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Wörn J, Ellwardt L, Aartsen M, Huisman M. Cognitive functioning among Dutch older adults: Do neighborhood socioeconomic status and urbanity matter? Soc Sci Med 2017. [PMID: 28647643 DOI: 10.1016/j.socscimed.2017.05.052] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Positive associations of neighborhood socioeconomic characteristics and older adults' cognitive functioning have been demonstrated in previous studies, but overall results have been mixed and evidence from European countries and particularly the Netherlands is scarce. We investigated the effects of socioeconomic status (SES) and urbanity of neighborhoods on four domains of cognitive functioning in a sample of 985 Dutch older adults aged 65-88 years from the Longitudinal Aging Study Amsterdam. Besides cross-sectional level differences in general cognitive functioning, processing speed, problem solving and memory, we examined cognitive decline over a period of six years. Growth models in a multilevel framework were used to simultaneously assess levels and decline of cognitive functioning. In models not adjusting for individual SES, we found some evidence of higher levels of cognitive functioning in neighborhoods with a higher SES. In the same models, urbanity generally showed positive or inversely U-shaped associations with levels of cognitive functioning. Overall, effects of neighborhood urbanity remained significant when adjusting for individual SES. In contrast, level differences by neighborhood SES were largely explained by the respondents' individual SES. This suggests that neighborhood SES does not influence levels of cognitive functioning beyond the fact that individuals with a similar SES tend to self-select into neighborhoods with a corresponding SES. No evidence of systematically faster decline in neighborhoods with lower SES or lower degrees of urbanity was found. The findings suggest that neighborhood SES has no independent effect on older adults cognitive functioning in the Netherlands. Furthermore, the study reveals that neighborhood urbanity should be considered a determinant of cognitive functioning. This finding is in line with theoretical approaches that assume beneficial effects of exposure to complex environments on cognitive functioning. We encourage further investigations into the effect of urbanity in other contexts before drawing firm conclusions.
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Affiliation(s)
- Jonathan Wörn
- University of Cologne, Research Training Group SOCLIFE, Albertus-Magnus-Platz, 50923 Cologne, Germany; University of Cologne, Institute of Sociology and Social Psychology, Albertus-Magnus-Platz, 50923 Cologne, Germany.
| | - Lea Ellwardt
- University of Cologne, Institute of Sociology and Social Psychology, Albertus-Magnus-Platz, 50923 Cologne, Germany.
| | - Marja Aartsen
- Oslo and Akershus University College of Applied Sciences, Norwegian Social Research, P.O. Box 4 St. Olavs Plass, 0130 Oslo, Norway.
| | - Martijn Huisman
- VU University Amsterdam, Medical Center, Department of Epidemiology and Biostatistics, P.O. Box 7057, 1007 MB Amsterdam, The Netherlands; VU University Amsterdam, Department of Sociology, De Boelelaan 1081, 1081 HV Amsterdam, The Netherlands.
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