Examining the influence of the neighbourhood environment on childhood obesity
Bibliographic record
Abstract
Rising rates of childhood obesity in Canada, linked to a changing environment, may have considerable health and societal costs. This dissertation investigates the influence of the neighbourhood environment on childhood overweight and physical activity. This research asks three questions. First, are there disparities in childhood obesity and physical activity by neighbourhood socioeconomic status? Second, are there critical periods during childhood when neighbourhood socioeconomic disparities in overweight develop? Third, do aspects of the proximate social and physical environment explain relations between neighbourhood socioeconomic status and childhood overweight and physical activity? To answer questions one and two data from the National Longitudinal Survey of Children and Youth (NLSCY, Cycles 1 to 5, 1994/5 to 2002/3) are used. Nationally representative cross-sectional data from Cycle 4 (2000/2001) for children ages 5 to 17 years are used to assess if neighbourhood socioeconomic status has an independent influence on overweight. Longitudinal data from Cycles 1 to 5 are used to assess when the development of disparities in overweight by neighbourhood socioeconomic status occur. Multilevel analysis methods are used. To answer question three, eight neighbourhoods with contrasting income (higher and lower) and residential density (higher and lower) in the Vancouver Census Metropolitan Area are studied. Information on children’s bodyweight, physical activity and perception of the neighbourhood social and physical environment is obtained from a telephone survey. Each neighbourhood is directly assessed by raters using the Neighbourhood Observational Survey Instrument and the Park Observational Survey Instrument. Analysis using the NLSCY finds a gradient in which increasing neighbourhood socioeconomic status is associated with a decreased incidence of overweight. Longitudinal analysis finds that neighbourhood disparities in overweight widen as children age. The analysis of eight neighbourhoods finds lower quality social and physical environments in lower income neighbourhoods. Findings suggest that reducing the incidence of childhood obesity requires policies to target the conditions of daily life including the places children live.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".