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Record W4210793310 · doi:10.1002/oby.23352

Built environment influences on healthy eating and active living: The NEWPATH study

2022· article· en· W4210793310 on OpenAlexafffund
Lawrence D. Frank, Alexander Bigazzi, Andy Hong, Leia Minaker, Pat Fisher, Kim D. Raine

Bibliographic record

VenueObesity · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversity of AlbertaRegional Municipality of WaterlooUniversity of WaterlooVancouver Community CollegeUniversity of British Columbia
FundersHeart and Stroke Foundation of Canada
KeywordsActive livingHealthy eatingEnvironmental healthMedicineGerontologyPhysical activityFood sciencePhysical medicine and rehabilitationBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: The Neighbourhood Environments in Waterloo: Patterns of Active Transportation and Health (NEWPATH) study examined built environment influences on travel, physical activity, food consumption, and health. This collaboration between researchers and practitioners in health and transportation planning is the first, to our knowledge, to integrate food purchasing, diet, travel, and objectively measured physical activity into a trip-destination protocol. This study simultaneously examines diet and physical activity relationships with BMI and waist circumference (WC). METHODS: Individual diet and travel diary data were linked to objective built-environment measures of walkability and retail food environments. BMI and WC were self-reported (n = 1,160). Some respondents wore accelerometers to objectively measure physical activity (n = 549). Pathways from the built environment through behavior (walking and eating) to BMI and WC were assessed using path analysis. RESULTS: Walkability was associated with lower BMI and WC through physical activity and active travel. Healthy retail food environments were associated with healthy eating and lower BMI and WC, whereas walkability and healthy retail food environments were insignificant (p < 0.05). Walkable neighborhoods had less healthy food environments, but active travel was not associated with healthy eating or caloric intake. CONCLUSIONS: Findings highlight the importance of neighborhood walkability and food environments in shaping physical activity, diet, and obesity.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
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 head0.029
GPT teacher head0.304
Teacher spread0.275 · 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.

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

Citations15
Published2022
Admission routes2
Has abstractyes

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