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- Publisher Website: 10.1016/j.healthplace.2023.103077
- Scopus: eid_2-s2.0-85166471926
- PMID: 37451077
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Article: Characteristics of urban neighbourhood environments and cognitive age in mid-age and older adults
Title | Characteristics of urban neighbourhood environments and cognitive age in mid-age and older adults |
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Authors | |
Keywords | Cognitive age Machine learning Neighbourhood socio-economic status Parkland availability Urban environments |
Issue Date | 1-Sep-2023 |
Publisher | Elsevier |
Citation | Health & Place, 2023, v. 83 How to Cite? |
Abstract | In this cross-sectional study, we examined the extent to which features of the neighbourhood natural, built, and socio-economic environments were related to cognitive age in adults (N = 3418, Mage = 61 years) in Australia. Machine learning estimated an individual's cognitive age from assessments of processing speed, verbal memory, premorbid intelligence. A ’cognitive age gap’ was calculated by subtracting chronological age from predicted cognitive age and was used as a marker of cognitive age. Greater parkland availability and higher neighbourhood socio-economic status were associated with a lower cognitive age gap score in confounder- and mediator-adjusted regression models. Cross-sectional design is a limitation. Living in affluent neighbourhoods with access to parks maybe beneficial for cognitive health, although selection mechanisms may contribute to the findings. |
Persistent Identifier | http://hdl.handle.net/10722/346290 |
ISSN | 2023 Impact Factor: 3.8 2023 SCImago Journal Rankings: 1.276 |
DC Field | Value | Language |
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dc.contributor.author | Soloveva, Maria V | - |
dc.contributor.author | Poudel, Govinda | - |
dc.contributor.author | Barnett, Anthony | - |
dc.contributor.author | Shaw, Jonathan E | - |
dc.contributor.author | Martino, Erika | - |
dc.contributor.author | Knibbs, Luke D | - |
dc.contributor.author | Anstey, Kaarin J | - |
dc.contributor.author | Cerin, Ester | - |
dc.date.accessioned | 2024-09-14T00:30:21Z | - |
dc.date.available | 2024-09-14T00:30:21Z | - |
dc.date.issued | 2023-09-01 | - |
dc.identifier.citation | Health & Place, 2023, v. 83 | - |
dc.identifier.issn | 1353-8292 | - |
dc.identifier.uri | http://hdl.handle.net/10722/346290 | - |
dc.description.abstract | In this cross-sectional study, we examined the extent to which features of the neighbourhood natural, built, and socio-economic environments were related to cognitive age in adults (N = 3418, Mage = 61 years) in Australia. Machine learning estimated an individual's cognitive age from assessments of processing speed, verbal memory, premorbid intelligence. A ’cognitive age gap’ was calculated by subtracting chronological age from predicted cognitive age and was used as a marker of cognitive age. Greater parkland availability and higher neighbourhood socio-economic status were associated with a lower cognitive age gap score in confounder- and mediator-adjusted regression models. Cross-sectional design is a limitation. Living in affluent neighbourhoods with access to parks maybe beneficial for cognitive health, although selection mechanisms may contribute to the findings. | - |
dc.language | eng | - |
dc.publisher | Elsevier | - |
dc.relation.ispartof | Health & Place | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Cognitive age | - |
dc.subject | Machine learning | - |
dc.subject | Neighbourhood socio-economic status | - |
dc.subject | Parkland availability | - |
dc.subject | Urban environments | - |
dc.title | Characteristics of urban neighbourhood environments and cognitive age in mid-age and older adults | - |
dc.type | Article | - |
dc.identifier.doi | 10.1016/j.healthplace.2023.103077 | - |
dc.identifier.pmid | 37451077 | - |
dc.identifier.scopus | eid_2-s2.0-85166471926 | - |
dc.identifier.volume | 83 | - |
dc.identifier.eissn | 1873-2054 | - |
dc.identifier.issnl | 1353-8292 | - |