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Record W6980089086

The Association of the Built Environment with Body Mass Measures in Survivors of Childhood Brain Tumors and Non-Cancer Controls

2024· dissertation· en· W6980089086 on OpenAlexaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2024
Typedissertation
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsBuilt environmentBody mass indexWalkabilityObesityPercentileValue (mathematics)Prospective cohort studyPoison controlCohort study
DOInot available

Abstract

fetched live from OpenAlex

Background: While the obesity epidemic is impacting children, survivors of childhood brain tumors (SCBT) are particularly vulnerable to obesity-driven cardiometabolic comorbidities. SCBT have excess body fat (adiposity) with similar body mass measures when compared to matched non-cancer controls. The effect of the built environment on the risk of obesity has received relatively limited attention in survivors. Aim & Methods: The aim of this project was to determine the impact of the built environment on body mass index (BMI) percentile, body fat percentage (BF%), waist-to-hip ratio (WHR), and waist-to-height-ratio (WHtR) in SCBT and non-cancer controls. The data for this secondary analysis were derived from participants in the Canadian Study of Determinants of Endometabolic Health in Children (CanDECIDE), a prospective cohort study based at McMaster Children’s Hospital, a tertiary pediatric academic center in Hamilton, Ontario, Canada. The Neighborhood Environment Walkability Scale (NEWS) was used to assess the built environment. Multivariable regression analyses were used to define the predictors of the association. Results: The built environment was not associated with BMI percentile in SCBT and non-cancer controls including residential density (B 0.276, p value 0.436), land use mix diversity (B -0.286, p value 0.301), land use mix access (B 0.004, p value 0.993), street connectivity (B 0.297, p value 0.431), walking/cycling facilities (B 0.185, p value 0.540), neighborhood aesthetics (B 0.270, p value 0.513), safety from traffic (B -0.368, p value 0.418), and safety from crime (B -0.074, p value 0.907). The built environment was also not associated with adiposity measures (BF%: residential density B 0.031, p value 0.851, land use mix diversity B -0.082, p value 0.513, land use mix access B -0.036, p value 0.861, street connectivity B 0.309, p value 0.055, walking/cycling facilities B 0.109, p 0.439, neighborhood aesthetics B 0.127, p value 0.503, safety from traffic B -0.047, p value 0.825, and safety from crime B -0.154, p value 0.601; WHR: residential density B -0.042, p value 0.362, land use mix diversity B 0.043, p value 0.131, land use mix access B -0.028, p value 0.558, street connectivity B -0.044, p value 0.252, walking/cycling facilities B 0.026, p value 0.476, neighborhood aesthetics B 0.062, p value 0.137, safety from traffic B -0.048, p value 0.336, and safety from crime B -0.083, p value 0.239; WHtR: residential density B 0.011, p value 0.865, land use mix diversity B 0.033, p value 0.462, land use mix access B -0.032, p value 0.662, street connectivity B 0.021, p value 0.720, walking/cycling facilities B 0.042, p value 0.493, neighborhood aesthetics B 0.018, p value 0.790, safety from traffic B -0.020, p value 0.789, and safety from crime B -0.086, p value 0.392). Conclusion: The results of this study suggest that the built environment has less of an impact than brain tumors and their treatments on driving body mass and fat mass changes in SCBT. The use of lifestyle interventions may need to be combined with pharmacotherapies in the treatment of obesity in SCBT.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.071
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.207
Teacher spread0.201 · 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 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 routes1
Has abstractyes

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