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Record W3206479165 · doi:10.1016/s2542-5196(21)00235-7

Assessing the association between lifetime exposure to greenspace and early childhood development and the mediation effects of air pollution and noise in Canada: a population-based birth cohort study

2021· article· en· W3206479165 on OpenAlex
Ingrid Jarvis, Zoë Davis, Hind Sbihi, Michael Bräuer, Agatha Czekajlo, Hugh Davies, Sarah E. Gergel, Martin Guhn, Michael Jerrett, Mieke Koehoorn, Tim F. Oberlander, Jason Su, Matilda van den Bosch

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Lancet Planetary Health · 2021
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsLearning PartnershipBC Centre for Disease ControlUniversity of British Columbia
FundersInstitute of Population and Public HealthCanadian Institutes of Health ResearchUniversity of British Columbia
KeywordsMediationPopulationDemographyEnvironmental healthMedicineCohortEarly childhoodCohort studyMultilevel modelGeographyPsychologyStatistics

Abstract

fetched live from OpenAlex

BackgroundExposure to greenspace is associated with improved childhood development, but the pathways behind this relationship are insufficiently understood. Therefore, we aimed to investigate the association between lifetime residential exposure to greenspace and early childhood development and evaluate the extent to which this association is mediated by reductions in traffic-related air pollution and noise.MethodsThis population-based birth cohort study comprised singleton births in Metro Vancouver, BC, Canada, between April 1, 2000, and Dec 31, 2005. Children and mothers had to be registered with the mandatory provincial health insurance programme, Medical Services Plan, and have lived within the study area from the child's birth to the time of outcome assessment. Early childhood development was assessed via teacher ratings on the Early Development Instrument (EDI), and we used the total EDI score as the primary outcome variable. We estimated greenspace using percentage vegetation derived from spectral unmixing of annual Landsat satellite image composites. Lifetime residential exposure to greenspace was estimated as the mean of annual percentage vegetation values within 250 m of participants’ residential postal codes. Multilevel modelling, adjusted for eight covariates, was used to investigate associations between greenspace exposure and EDI scores. We estimated the mediation effects of nitrogen dioxide (NO2), fine particulate matter (PM2·5), and noise levels using causal mediation analyses.FindingsOf the 37 745 children born in Metro Vancouver between April 1, 2000, and Dec 31, 2005, 27 372 were included in our final study sample. In the adjusted model, 1 IQR increase in percentage vegetation was associated with a 0·16 (95% CI 0·04–0·28; p=0·0073) increase in total EDI score, indicating small improvements in early childhood development. We estimated that 97·1% (95% CI 43·0–396·0), 29·5% (12·0–117·0), and 35·2% (17·9–139·0) of the association was mediated through reductions in NO2, PM2·5, and noise, respectively.InterpretationIncreased exposure to residential greenspace might improve childhood development by reducing the adverse developmental effects of traffic-related exposures, especially NO2 air pollution. Our study supports the implementation of healthy urban planning and green infrastructure interventions.FundingCanadian Institutes of Health Research.

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.

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)0.003
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 score0.218
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.299
Teacher spread0.285 · 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