Associations between familial affluence and obesity risk behaviours among children
Bibliographic record
Abstract
BACKGROUND: Results of studies examining associations between socioeconomic status and obesity among children are mixed. OBJECTIVE: To examine whether physical activity, television viewing, computer use, and fruit, vegetable, soft drink and sweet consumption differed according to familial affluence of children attending schools in disadvantaged communities. METHOD: A total of 218 children (seven to 11 years of age) recruited from three Calgary (Alberta) schools located in two adjacent socioeconomically disadvantaged neighbourhoods completed online surveys during the spring of 2005/2006. The number of days per week participating in vigorous physical activity for more than 20 min, and weekly frequency of fruit, vegetable, sweet and soft drink consumption were collected. Time spent watching television and using a computer during a normal school day was also captured. A family affluence scale was used to assess socioeconomic status (number of family holidays in the past year, ownership of motor vehicles and computers, and bedroom sharing). Associations between familial affluence and obesity risk behaviours were estimated using Pearson's correlation and demographic-adjusted logistic regression ORs. RESULTS: Higher family affluence scale scores were significantly associated with weekly fruit consumption (r=0.14). Children with lower affluence were less likely to participate in vigorous physical activity five days/week or more (OR=0.39), and to use a computer for more than 2 h/day (OR=0.41) than children with higher affluence. Linear trends between familial affluence and the likelihood of participating in physical activity and using a computer were also found. However, no other behaviours were related to affluence. CONCLUSIONS: Increasing opportunities for physical activity and accessibility to healthy food may be important for reducing obesity risk among less affluent children.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".