Sociodemographic, behavioural and environmental correlates of sweetened beverage consumption among pre-school children
Bibliographic record
Abstract
OBJECTIVE: To identify sociodemographic and environmental correlates of sweetened beverages (regular soft drinks, fruit juice) among children of pre-school age. DESIGN: Children's dietary intake, food behaviours and screen time were measured by parental report. A Geographic Informational System was used to assess the number of grocery stores and fast-food restaurants available within 1 km of the children's residence. Multivariate log-binomial regression models were constructed to determine correlates of drinking soft drinks during the previous week. SETTING: Edmonton region, Canada. SUBJECTS: Children aged 4 and 5 years (n 2114) attending a public health unit for immunization were recruited for a cohort study on determinants of childhood obesity, between 2005 and 2007. RESULTS: Children from neighbourhoods with low socio-economic status (relative risk (RR) = 1·17, 95 % CI 0·98, 1·40) or who participated in >2 h of screen time daily (RR = 1·28, 95 % CI 1·13, 1·45) were significantly more likely to have consumed regular soft drinks within the last week. Those who lived within 1 km of a grocery store were significantly less likely to consume regular soft drinks (RR = 0·84, 95 % CI 0·73, 0·96). Children who participated in >2 h of screen time daily (RR = 1·16, 95 % CI 1·06, 1·27) were more likely to exceed the recommended weekly number of servings of fruit juice. CONCLUSIONS: Socio-economic and built environment factors are associated with soft drink consumption in children of pre-school age. These findings may help health professionals to advocate for policies that reduce soft drink consumption among 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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".