Consumption of High-Risk Foods in the Canadian Population, Foodbook Study, 2014 to 2015
Bibliographic record
Abstract
ABSTRACT: Many foods have the potential to cause foodborne illness; however, some pose a higher risk. Data were collected through the Foodbook study, a population-based telephone survey conducted between 2014 and 2015 that assessed 10,942 Canadians' food exposures using a 7-day recall period. The 19 foods included in the survey were identified as high risk for common foodborne pathogens in Canada. Results were analyzed by age group, gender, region of residence, income, and education. Consumption proportions of high-risk foods ranged from 0.4% (raw oysters) to 49.3% (deli meats). Roughly 94% of the population reported consuming one or more high-risk food in the past week. Certain high-risk food behaviors were associated with demographic characteristics. High-risk adults such as those 65 years or older still report consuming high-risk foods of concern, including deli meats (41.8%), soft cheeses (13.7%), and smoked fish (6.3%). Consumption of certain foods differed between genders, with males consuming significantly more deli meats, hot dogs, and raw or undercooked eggs and females consuming significantly more prebagged mixed salad greens. The overall number of high-risk foods consumed was similar, with both genders most frequently consuming three to five high-risk foods. High-risk food consumption was seen to increase with increasing household income, with 14.2% of the highest income level consuming six-plus high-risk foods in the past week, compared with 7.1% of the lowest income level. If a respondent had heard of a risk of foodborne illness associated with a food, it did not affect whether it was consumed. Additional consumer food safety efforts put in place alongside current messaging may improve high-risk food consumption behaviors. Enhancing current messaging by using multifaceted communications (e.g., social media and information pamphlets) and highlighting the large incidence and severity of foodborne illnesses in Canada are important strategies to improve behavior change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".