Beverage intake patterns of Canadian children and adolescents
Bibliographic record
Abstract
OBJECTIVE: Little is known of the beverage intake patterns of Canadian children or of characteristics within these patterns. The objective was to determine beverage intake patterns among Canadian children and compare intakes of fourteen types of beverages, along with intakes of vitamin C and Ca, and sociodemographic factors across clusters. DESIGN: Dietary information was collected using one 24 h recall. Sociodemographic data were collected by interview. Cluster analysis was used to determine beverage intake patterns. Pearson's χ2 and 95 % CI were used to test differences across clusters. SETTING: Data from the Canadian Community Health Survey Cycle 2·2. SUBJECTS: Children aged 2-18 years with plausible energy intake and complete sociodemographic data (n 10 038) were grouped into the following categories: 2-5-year-old boys and girls, 6-11-year-old girls, 6-11-year-old boys, 12-18-year-old girls and 12-18-year-old boys. RESULTS: Five beverage clusters emerged for children aged 2-5 years, six clusters for children aged 6-11 years (both sexes) and four clusters for those aged 12-18 years (both sexes). Sweetened beverage clusters appeared in all age-sex groups. Intakes of sweetened beverages ranged from 553 to 1059 g/d and contributed between 2 % and 18 % of total energy intake. Girls 6-11 years of age in the 'soft drink' cluster had lower Ca intake compared with other clusters in that age-sex group. Age and ethnicity differed across clusters for most age-sex groups. Differences for household food security status and income were found; however, no pattern emerged. CONCLUSIONS: Patterns in beverage intake among Canadian children include beverages that are predominantly sugar sweetened. Public health nutrition professionals can use knowledge about beverage patterns among children, as well as the characteristics of these groups, in the development of nutritional programmes and policies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".