Breakfast Consumption and Diet Quality of Teens in Southwestern Ontario
Bibliographic record
Abstract
Background: Breakfast skipping has previously been associated with worse diet quality among adolescents; the latter increases the risk of chronic disease. However, many studies do not consider diet quality as a function of calories, which is problematic as skippers tend to consume less energy than consumers. Additionally, due to the lack of one accepted definition of both breakfast skipping and diet quality, it is unclear how differences found may change when using varying definitions. Objectives: We aimed to compare the Healthy Eating Index-2015 (HEI-2015) scores and nutrient intakes of teen breakfast skippers and consumers in Southwestern Ontario, Canada. Methods: Cross-sectional, baseline data were used from SmartAPPetite, an ongoing nutrition intervention study. Singular 24-h dietary recalls and sociodemographic data from 512 adolescents aged 13-19 y were used to compare HEI-2015 scores and nutrient intakes via multivariable linear regression. Results: Previous day breakfast skippers had significantly lower HEI-2015 scores (-4.4; 95% CI: -8.4, -0.4) and significantly lower intakes of calories, saturated fat, and vitamin C, as well as significantly higher intake of sodium and total fat. Conclusions: Previous day breakfast consumers had significantly higher diet quality scores and better nutrient intakes than breakfast skippers, although, on average, both had poor diet quality. Consequently, it is unlikely that simply advising teens to consume breakfast will result in meaningful change in diet quality, and more effort should be placed on promoting nutritious breakfasts.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.003 | 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".