Beverage patterns among Canadian children and relationship to overweight and obesity
Bibliographic record
Abstract
Sweetened beverage intake has risen in past decades, along with a rise in prevalence of overweight and obesity among children. Our objective was to examine the relationship between beverage intake patterns and overweight and obesity among Canadian children. Beverage intake patterns were identified by cluster analysis of data from the cross-sectional Canadian Community Health Survey 2.2. Intake data were obtained from a single 24-hour recall, height and weight were measured, and sociodemographic data were obtained via interview. Data on children and adolescents aged 2-18 years who met inclusion criteria (n = 10 038) were grouped into the following categories: 2-5 years (male and female), 6-11 years (female), 6-11 years (male), 12-18 years (female), and 12-18 years (male). χ² test was used to compare rates of overweight and obesity across clusters. Logistic regression was used to determine the association between overweight and obesity and beverage intake patterns, adjusting for potential confounders. Clustering resulted in distinct groups of who drank mostly fruit drinks, soft drinks, 100% juice, milk, high-fat milk, or low-volume and varied beverages (termed "moderate"). Boys aged 6-11 years whose beverage pattern was characterized by soft drink intake (553 ± 29 g) had increased odds of overweight-obesity (odds ratio 2.3, 95% confidence interval 1.2-4.1) compared with a "moderate" beverage pattern (23 ± 4 g soft drink). No significant relationship emerged between beverage pattern and overweight and obesity among other age-sex groups. Using national cross-sectional dietary intake data, Canadian children do not show a beverage-weight association except among young boys who drink mostly soft drinks, and thus may be at increased risk for overweight or obesity.
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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 | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".