Neighborhood characteristics in relation to diet, physical activity and overweight of Canadian children
Bibliographic record
Abstract
BACKGROUND: Neighborhood infrastructure may provide an important opportunity to prevent overweight among children. In the present study we investigated whether access to shops for modestly priced fresh produce, access to parks and playgrounds, access to recreational facilities and neighborhood safety are related to children's diet, physical and sedentary activities, and body weights. METHODS: Data were obtained from the Children's Lifestyle and School-performance Study, a survey including 5,471 grade five students and their parents in the province of Nova Scotia, Canada. Students completed the Harvard Food Frequency Questionnaire and had their height and weight measured. Parents completed questions on socio-economic background and how they perceived their neighborhood. We applied multilevel regression methods to relate these neighborhood characteristics with children's fruit and vegetable consumption, dietary fat intake, diet quality, frequency of engaging in sports with and without a coach, screen time, overweight and obesity. RESULTS: Children in neighborhoods with greater perceived access to shops had healthier diets and were less likely to be overweight or obese. Children in neighborhoods with good access to playgrounds, parks and recreational facilities were reportedly more active and were less likely to be overweight or obese, whereas children in safe neighborhoods engaged more in unsupervised sports. CONCLUSIONS: The study demonstrated associations between neighborhood characteristics, health behaviors and childhood overweight. This contributes to the knowledge base that is still too narrow to justify informed preventative public health policy. We advocate the evaluation of natural experiments created by new policy that affect neighborhood infrastructures as the optimal opportunity to enlarge this knowledge base.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".