Do neighbourhood traffic-related air pollution and socio-economic status moderate the associations of the neighbourhood physical environment with cognitive function? Findings from the AusDiab study.

Disadvantage Greenspace Memory Mid-aged and older adults Processing speed Walkability

Journal

The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500

Informations de publication

Date de publication:
01 Feb 2023
Historique:
received: 17 07 2022
revised: 02 11 2022
accepted: 03 11 2022
pubmed: 12 11 2022
medline: 15 12 2022
entrez: 11 11 2022
Statut: ppublish

Résumé

Characteristics of the neighbourhood environment, including the built and natural environment, area-level socio-economic status (SES) and air pollution, have been linked to cognitive health. However, most studies have focused on single neighbourhood characteristics and have not considered the extent to which the effects of environmental factors may interact. We examined the associations of measures of the neighbourhood built and natural environment, area-level SES and traffic-related air pollution (TRAP) with two cognitive function domains (memory and processing speed), and the extent to which area-level SES and TRAP moderated the associations. We used cross-sectional data from the AusDiab3 study, an Australian cohort study of adults (mean age: 61 years) in 2011-12 (N = 4141) for which geocoded residential addresses were available. Spatial data were used to create composite indices of built environment complexity (population density, intersection density, non-commercial land use mix, commercial land use) and natural environment (parkland and blue spaces). Area-level SES was obtained from national census indices and TRAP was based on estimates of annual average levels of nitrogen dioxide (NO

Identifiants

pubmed: 36368384
pii: S0048-9697(22)07128-5
doi: 10.1016/j.scitotenv.2022.160028
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

160028

Subventions

Organisme : Medical Research Council
ID : MR/T038500/1
Pays : United Kingdom

Informations de copyright

Copyright © 2022 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Ester Cerin (E)

Mary MacKillop Institute for Health Research, Australian Catholic University, 215 Spring St., Melbourne, VIC, Australia; School of Public Health, The University of Hong Kong, 7 Sassoon Rd., Sandy Bay, Hong Kong; Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; Department of Community Medicine, UiT The Artic University of Norway, Tromsø, Norway. Electronic address: ester.cerin@acu.edu.au.

Anthony Barnett (A)

Mary MacKillop Institute for Health Research, Australian Catholic University, 215 Spring St., Melbourne, VIC, Australia.

Yu-Tzu Wu (YT)

Population Health Sciences Institute, Newcastle University, Newcastle NE4 5PL, United Kingdom.

Erika Martino (E)

School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia.

Jonathan E Shaw (JE)

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.

Luke D Knibbs (LD)

Sydney School of Public Health, The University of Sydney, Camperdown, NSW, Australia; Public Health Unit, Sydney Local Health District, Camperdown, NSW, Australia.

Govinda Poudel (G)

Mary MacKillop Institute for Health Research, Australian Catholic University, 215 Spring St., Melbourne, VIC, Australia.

Bin Jalaludin (B)

School of Population Health, University of New South Wales, Randwick, NSW, Australia.

Kaarin J Anstey (KJ)

School of Psychology, University of New South Wales, Randwick, NSW, Australia; Neuroscience Research Australia (NeuRA), Sydney, Australia; UNSW Ageing Futures Institute, Sydney, Australia.

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Classifications MeSH