Effects of Food Advertising on Youth’s Eating Behavior: A Systematic Review of Longitudinal Studies
Bibliographic record
Abstract
ABSTRACT Background:Previous cross-sectional studies have found a positive relationship between commercial audiovisual media viewing and youth overweight/obesity, suggesting that advertising of low-nutritional-value products (LNVP) influences unhealthy food consumption patterns. The objective of this study was to analyze the long-term influence of LNVP advertising on children’s and adolescents’ consumption habits.Method:A systematic literature review following PRISMA guidelines examined the long-term effects of LNVP advertising on youth’s diet-related outcomes. A search in PubMed and PsycINFO (June 2024) included studies from the last 12 years exploring the relationship between digital food advertising and subsequent consumption behaviors. Two authors independently screened and assessed studies using an adapted Newcastle-Ottawa Scale. Results: Findings were inconclusive, with six of twelve studies reporting a positive relationship, while the other six found no association. Conclusions: LNVP advertising does not enhance youth’s food choices or nutritional knowledge. Its impact on diet appears limited and may depend on other factors, such as parental nutritional knowledge.
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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 | 0.013 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".