Processed and Ultra-processed Food Products: Consumption Trends in Canada from 1938 to 2011
Bibliographic record
Abstract
PURPOSE: A classification of foods based on the nature, extent, and purpose of industrial food processing was used to assess changes in household food expenditures and dietary energy availability between 1938 and 2011 in Canada. METHODS: Food acquisitions from six household food budget surveys (1938/1939 , 1953, 1969, 1984, 2001, and 2011) were classified into unprocessed or minimally processed foods, processed culinary ingredients, and ready-to-consume processed or ultra-processed products. Contributions of each group to household food expenditures, and to dietary energy availability (kcal per capita) were calculated. RESULTS: During the period studied, household expenditures and dietary energy availability fell for both unprocessed or minimally processed foods and culinary ingredients, and rose for ready-to-consume products. The caloric share of foods fell from 34.3% to 25.6% and from 37% to 12.7% for culinary ingredients. The share of ready-to-consume products rose from 28.7% to 61.7%, and the increase was especially noteworthy for those that were ultra-processed. CONCLUSIONS: The most important factor that has driven changes in Canadian dietary patterns between 1938 and 2011 is the replacement of unprocessed or minimally processed foods and culinary ingredients used in the preparation of dishes and meals; these have been displaced by ready-to-consume ultra-processed products. Nutrition research and practice should incorporate information about food processing into dietary assessments.
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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 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".