Restricting child-directed ads is effective, but adding a time-based ban is better: evaluating a multi-phase regulation to protect children from unhealthy food marketing on television
Bibliographic record
Abstract
BACKGROUND: As childhood obesity rates continue to rise, health organizations have called for regulations that protect children from exposure to unhealthy food marketing. In this study, we evaluate the impact of child-based versus time-based restrictions of "high-in" food and beverage advertising in Chile, which first restricted the placement of "high-in" advertisements (ads) in television attracting children and the use of child-directed content in high-in ads and, second, banned high-in ads from 6am-10pm. "High-in" refers to products above regulation-defined thresholds in energy, saturated fats, sugars, and/or sodium. High-in advertising prevalence and children's exposure to high-in advertising are assessed. METHODS: We analyzed a random stratified sample of advertising from two constructed weeks of television at pre-regulation (2016), after Phase 1 child-based advertising restrictions (2017, 2018), and after the Phase 2 addition of a 6am-10pm high-in advertising ban (2019). High-in ad prevalence in post-regulation years were compared to prior years to assess changes in prevalence. We also analyzed television ratings data for the 4-12 year-old child audience to estimate children's ad exposure. RESULTS: Compared to pre-regulation, high-in ads decreased after Phase 1 (2017) by 42% across television (41% between 6am-10pm, 44% from 10pm-12am) and 29% in programs attracting children (P < 0.01). High-in ads further decreased after Phase 2, reaching a 64% drop from pre-regulation across television (66% between 6am-10pm, 56% from 10pm-12am) and a 77% drop in programs attracting children (P < 0.01). High-in ads with child-directed ad content also dropped across television in Phase 1 (by 41%) and Phase 2 (by 67%), compared to pre-regulation (P < 0.01). Except for high-in ads from 10pm-12am, decreases in high-in ads between Phase 1 (2018) and Phase 2 were significant (P < 0.01). Children's high-in ad exposure decreased by 57% after Phase 1 and by 73% after Phase 2 (P < 0.001), compared to pre-regulation. CONCLUSIONS: Chile's regulation most effectively reduced children's exposure to unhealthy food marketing with combined child-based and time-based restrictions. Challenges remain with compliance and limits in the regulation, as high-in ads were not eliminated from television. Yet, having a 6am-10pm ban is clearly critical for maximizing the design and implementation of policies that protect children from unhealthy food marketing.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".