Eating away from home in Canada: impact on dietary intake
Bibliographic record
Abstract
BACKGROUND: Public health measures related to the COVID-19 pandemic have upended the way Canadians eat and shop for food. Since the pandemic began, many Canadians have reported consuming food away from home (FAFH) less often. FAFH tends to be less healthful than food prepared at home. Little is known about patterns of Canadians' FAFH consumption before the pandemic. This study used 2015 national-level nutrition data, the most recent available, to characterize patterns of FAFH consumption and selected markers of dietary intake. DATA AND METHODS: National-level food intake data came from the first 24-hour dietary recall provided by 20,475 respondents aged 1 or older to the 2015 Canadian Community Health Survey-Nutrition. Mean daily intakes of selected food subgroups and nutrients, adjusted for total energy intake, were compared between those who had consumed any food in a restaurant on the previous day and those who had not. Estimates were generated overall and for eight age and sex groups. RESULTS: In 2015, overall, 21.8% of Canadians had consumed FAFH in a restaurant on the previous day. Eating out was most common among males aged 19 to 54 (27.7%) and least common among young children aged 1 to 5 (8.4%). Compared with Canadians who had not eaten out on the previous day, those who had eaten out had consumed, on that day, fewer servings of whole fruit; whole grains; dark green and orange vegetables; other vegetables (excluding potatoes); milk and fortified soy-based beverages; and legumes, nuts and seeds, on average. Those who had eaten out had consumed, on average, less fibre and total sugar, and more total fat, saturated fat and sodium on that day. There were few differences for meat and poultry, fish and seafood, and protein intake. DISCUSSION: On the day that Canadians ate out in a restaurant, their dietary intake was generally less favourable than that of Canadians who did not eat out. If Canadians continue to eat at home more and to consume less FAFH, as early pandemic-period reports suggest, then results can be used to gauge the potential dietary implications of these shifts.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| 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".