Food and beverage advertising expenditures in Canada in 2016 and 2019 across media
Bibliographic record
Abstract
BACKGROUND: Food and beverage advertising has been identified as a powerful determinant of dietary intake and weight. Available evidence suggests that the preponderance of food and beverage advertising expenditures are devoted to the promotion of unhealthy products. The purpose of this study is to estimate food advertising expenditures in Canada in 2019 overall, by media and by food category, determine how much was spent on promoting healthier versus less healthy products and assess whether changes in these expenditures occurred between 2016 and 2019. METHODS: Estimates of net advertising expenditures for 57 selected food categories promoted on television, radio, out-of-home media, print media and popular websites, were licensed from Numerator. The nutrient content of promoted products or brands were collected, and related expenditures were then categorized as "healthy" or "unhealthy" according to a Nutrient Profile Model (NPM) proposed by Health Canada. Expenditures were described using frequencies and relative frequencies and percent changes in expenditures between 2016 and 2019 were computed. RESULTS: An estimated $628.6 million was spent on examined food and beverage advertising in Canada in 2019, with television accounting for 67.7%, followed by digital media (11.8%). In 2019, most spending (55.7%) was devoted to restaurants, followed by dairy and alternatives (11%), and $492.9 million (87.2% of classified spending) was spent advertising products and brands classified as "unhealthy". Fruit and vegetables and water accounted for only 2.1 and 0.8% of expenditures, respectively, in 2019. In 2019 compared to 2016, advertising expenditures decreased by 14.1% across all media (excluding digital media), with the largest decreases noted for print media (- 63.0%) and television (- 14.6%). Overall, expenditures increased the most in relative terms for fruit and vegetables (+ 19.5%) and miscellaneous products (+ 5%), while decreasing the most for water (- 55.6%) and beverages (- 47.5%). CONCLUSIONS: Despite a slight drop in national food and beverage advertising spending between 2016 and 2019, examined expenditures remain high, and most products or brands being advertised are unhealthy. Expenditures across all media should continue to be monitored to assess Canada's nutrition environment and track changes in food advertising over time.
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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".