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Record W4404657160 · doi:10.1080/09603123.2024.2426712

Investigating the independent and synergistic associations between neighbourhood greenness and physical activity in relation to perceived mental health among adults in Canada

2024· article· en· W4404657160 on OpenAlexafffundabout
Natalie Doan, Justin J. Lang, Karen Roberts, Taru Manyanga, Daniel Rainham, Colin A. Capaldi, Gregory Butler, Stéphanie A. Prince, Sebastian A. Srugo

Bibliographic record

VenueInternational Journal of Environmental Health Research · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsUniversity of Northern British ColumbiaDalhousie UniversityUniversity of OttawaPublic Health Agency of CanadaUniversity of Waterloo
FundersPublic Health Agency of Canada
KeywordsNeighbourhood (mathematics)Mental healthEnvironmental healthPhysical activityPsychologyGerontologyPhysical healthDemographyGeographyMedicinePsychiatryMathematicsSociologyPhysical therapy

Abstract

fetched live from OpenAlex

The relationships among neighbourhood greenness, physical activity, and mental health are unclear; therefore, we examined the independent and synergistic associations between neighbourhood greenness and self-rated mental health among a nationally representative sample of urban-dwelling adults in Canada (18–79 years) from the 2007–2019 Canadian Health Measures Survey (n = 12,531). We assessed neighbourhood greenness using the Normalized Difference Vegetation Index within a 500-meter radius of participants’ residential postal codes. We measured physical activity using accelerometers and determined adherence to the recommended 150-minutes of moderate-to-vigorous intensity physical activity (MVPA) per week. We used weighted logistic regression models to test whether MVPA guideline adherence was an effect modifier in the association between neighbourhood greenness and self-rated mental health, adjusting for individual and neighbourhood characteristics. Neighbourhood greenness (aOR = 0.89 [0.62, 1.29]) and MVPA adherence (aOR = 1.22 [0.89, 1.69]) were not associated with self-rated mental health, and no interaction were found on the additive (Relative Excess Risk Due to Interaction = -0.45 [−1.24, 0.35], Attributable Proportion = -0.38 [−1.02, 0.26], Synergy Index = 0.28 [0.02, 3.20]) or multiplicative (OR = 0.7 [0.4, 1.3]) scales. Engaging in the recommended amount of MVPA did not change the finding that Canadian adults had similar self-rated mental health regardless of their neighbourhood greenness.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.358
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes3
Has abstractyes

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