Eating-Out: A Study of the Nutritional Quality of Canadian Chain Restaurant Foods and Interventions to Promote Healthy Eating
Bibliographic record
Abstract
Canadians are increasingly eating outside-the-home. At the outset of this thesis there were no data on the nutritional quality of Canadian chain restaurant foods, the Sodium Working Groupâ s plan to monitor sodium reductions in the food supply was abandoned, and despite interest and numerous bills, there was no existing menu-labelling legislation in Canada. The specific objectives of this thesis were to 1) investigate the nutritional quality of the Canadian chain restaurant food supply; 2) explore consumersâ use of menu-labelling; and 3) test the potential of alternative forms of labelling in non-chain restaurant settings. Objective 1 was investigated by developing and analyzing a national database of over 9000 menu-items from Canadian fast-food and sit-down chain restaurants which was created in 2010. There was wide variation in calorie levels within each restaurant and food category; furthermore, portion size, as opposed to calorie density, was the most important driver of this variation. Sodium levels in menu items often exceed daily recommendations and despite reported efforts by the restaurant sector to improve, as of 2013, reductions were minimal. Objective 2 used an online, national consumer survey to test three menu-labelling treatments (calories; calories and sodium; and calories, sodium and serving size labelling). The effect of labelling on consumer choice varied depending on the restaurant setting, however, overall, labelling sodium in addition to calories led consumers to choose meals with significantly less sodium. There was no additional benefit from adding serving size information. Objective 3 was examined in a quasi-experimental, population-level nutrition labelling/education intervention study in a campus cafeteria. Results showed that this intervention could modestly increase fruit and vegetable consumption, and decrease sugar-sweetened beverage consumption among University students. Overall, this thesis provides food supply and consumer data to inform public health policy debates around issues concerning food consumed outside-the-home.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".