Consumption of ultra-processed foods predicts diet quality in Canada
Bibliographic record
Abstract
This study describes food consumption patterns in Canada according to the types of food processing using the Nova classification and investigates the association between consumption of ultra-processed foods and the nutrient profile of the diet. Dietary intakes of 33,694 individuals from the 2004 Canadian Community Health Survey aged 2 years and above were analyzed. Food and drinks were classified using Nova into unprocessed or minimally processed foods, processed culinary ingredients, processed foods and ultra-processed foods. Average consumption (total daily energy intake) and relative consumption (% of total energy intake) provided by each of the food groups were calculated. Consumption of ultra-processed foods according to sex, age, education, residential location and relative family revenue was assessed. Mean nutrient content of ultra-processed foods and non-ultra-processed foods were compared, and the average nutrient content of the overall diet across quintiles of dietary share of ultra-processed foods was measured. In 2004, 48% of calories consumed by Canadians came from ultra-processed foods. Consumption of such foods was high amongst all socioeconomic groups, and particularly in children and adolescents. As a group, ultra-processed foods were grossly nutritionally inferior to non-ultra-processed foods. After adjusting for covariates, a significant and positive relationship was found between the dietary share of ultra-processed foods and the content in carbohydrates, free sugars, total and saturated fats and energy density, while an inverse relationship was observed with the dietary content in protein, fiber, vitamins A, C, D, B6 and B12, niacin, thiamine, riboflavin, as well as zinc, iron, magnesium, calcium, phosphorus and potassium. Lowering the dietary share of ultra-processed foods and raising consumption of hand-made meals from unprocessed or minimally processed foods would substantially improve the diet quality of Canadian.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".