Breakfast in Canada: Prevalence of Consumption, Contribution to Nutrient and Food Group Intakes, and Variability across Tertiles of Daily Diet Quality. A Study from the International Breakfast Research Initiative
Bibliographic record
Abstract
This study used 24-h recall data from the nationally representative 2015 Canadian Community Health Survey-Nutrition to assess breakfast intake among Canadians aged 6–12 years (n = 2331), 13–17 years (n = 2026), 18–54 years (n = 7651), and 55+ years (n = 6279). Overall, 90% consumed breakfast; breakfast consumers reported higher intakes of energy and key nutrients and had higher daily diet quality scores assessed using the Nutrient-Rich Foods Index 9.3 (NRF 9.3). Among breakfast consumers (n = 16,484), breakfast contributed a mean of 389 kcal (1628 kJ) and 21.6% of daily energy intake. Relative to its contribution to energy, breakfast contributed higher intakes of fruit, whole grains, and fluid milk, as well as associated nutrients (e.g., carbohydrate, total sugars, fiber, calcium, and vitamin D). Among breakfast consumers classified by daily dietary quality (NRF 9.3 score), energy intake at breakfast did not differ across tertiles for either children or adults. However, intakes of key nutrients, fiber, and total sugars increased across tertiles, and among adults, intakes of saturated fat and sodium decreased. Mean intakes of fruit, whole grains, and fluid milk also increased across tertiles, as did the proportion of individuals consuming these foods; higher fruit and milk intakes may explain higher sugar intakes as diet quality increased. Promoting the consumption of these foods at breakfast could contribute to improved diet quality among Canadians.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".