Top dietary sources of energy, sodium, sugars, and saturated fats among Canadians: insights from the 2015 Canadian Community Health Survey
Bibliographic record
Abstract
Dietary factors are major contributors to morbidity and mortality, and significant attention is being paid to interventions to support healthy eating, including through the creation of a healthier food supply. The objective of this study was to inform interventions to support healthy eating by examining the top dietary sources of calories, sodium, sugars, and saturated fats among Canadians in relation to sex, age, and income. We drew upon data from the 2015 Canadian Community Health Survey, which collected interviewer-administered 24-h dietary recalls from Canadians who were 1 year of age and older (n = 20 176), residing in the 10 provinces. Foods and beverages were grouped into 91 mutually exclusive categories (e.g., 100% fruit juice, fruit drinks). On the basis of the average proportion contributed, the top 20 sources of each dietary component were identified for all individuals and by sex–age and income groups. The mean amount of each dietary component contributed by each category (per capita and per consumer) and the proportions of persons consuming items in each category were also examined. Top sources included commonly consumed items (e.g., breads and flatbreads as sources of sodium), as well as those high in a given dietary component (e.g., soda as a source of sugars). Several food and beverage categories were top contributors to more than one dietary component examined, suggesting possible priorities for intervention and future analyses. The identification of major sources of calories and nutrients of concern can inform population health efforts, such as reformulation, to improve the health of 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.013 |
| Science and technology studies | 0.003 | 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".