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Record W4213430288 · doi:10.1210/endrev/bnac005

The Weight of Place: Built Environment Correlates of Obesity and Diabetes

2022· review· en· W4213430288 on OpenAlexafffund
Nicholas A. Howell, Gillian L. Booth

Bibliographic record

VenueEndocrine Reviews · 2022
Typereview
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsSt. Michael's HospitalPublic Health OntarioUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsBuilt environmentObesityEnvironmental healthPhysical activityGerontologyPopulationLevel designActive livingMedicineBiologyEcologyComputer sciencePhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

In recent decades, the prevalence of obesity and diabetes has risen substantially in North America and worldwide. To address these dual epidemics, researchers and policymakers alike have been searching for effective means to promote healthy lifestyles at a population level. As a consequence, there has been a proliferation of research examining how the "built" environment in which we live influences physical activity levels, by promoting active forms of transportation, such as walking and cycling, over passive ones, such as car use. Shifting the transportation choices of local residents may mean that more members of the population can participate in physical activity during their daily routine without structured exercise programs. Increasingly, this line of research has considered the downstream metabolic consequences of the environment in which we live, raising the possibility that "healthier" community designs could help mitigate the rise in obesity and diabetes prevalence. This review discusses the evidence examining the relationship between the built environment, physical activity, and obesity-related diseases. We also consider how other environmental factors may interact with the built environment to influence metabolic health, highlighting challenges in understanding causal relationships in this area of 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.049
GPT teacher head0.334
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations73
Published2022
Admission routes2
Has abstractyes

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