Temporal snacking patterns among Canadian children and adolescents
Bibliographic record
Abstract
Snacking is nearly universal among children but there is growing concern around snacking patterns and energy contribution. This study aimed to characterize temporal snacking patterns among Canadian children and adolescents. A cross-sectional analysis drew on data from 5209 respondents aged 4–18 years from the 2015 Canadian Community Health Survey Nutrition, using one 24 h dietary recall. Descriptive statistics estimated proportions of morning, afternoon, and evening snackers, the mean caloric contribution of each snacking period to total daily energy intake, and the top food categories consumed as snacks (kcal per capita). Snacking was nearly universal and accounted for one of every four calories consumed. Morning snacks were more popular among children vs. adolescents and contributed significantly less energy than afternoon or evening snacking periods for both age groups ( P < 0.001). The top food groups consumed as snacks were the same for children and adolescents, although the ranking order varied. Fruits were the leading food group in terms of per capita energy for children and second for adolescents. Aside from fruits and milks, all other top per capita energy contributors were generally more energy-dense, nutrient-poor foods such as cookies, biscuits and cereal bars, and other breads. Among children, morning snacks were higher in desirable nutrients compared with afternoon snacks. Not all snacking periods are equal in terms of energy and nutrients. A better understanding of how time of day may influence the quality of snack foods can inform meal-based guidance and help children achieve the recommended daily amounts of foods and nutrients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".