Availability and marketing of food and beverages to children through sports settings: a systematic review
Bibliographic record
Abstract
OBJECTIVE: The current systematic review aimed to identify and critically appraise research on food environments in sports settings, including research into the types of food and beverages available, the extent and impact of food and beverage sponsorship and marketing, and views about food environments among key stakeholders. DESIGN: A systematic review. Fourteen English-language studies (two were papers describing different facets of the same study), published between 1985 and 2011, were identified from searches of electronic databases and bibliographies of primary studies. SETTING: Most studies originated from Australia (n 10), with the remaining studies originating in the UK (n 1), New Zealand (n 1), the USA (n 1) and Canada (n 1). Data were collected from observations in stadia, websites and televised sports events, through in-depth interviews, focus groups and surveys with sports club members, parents and quick serve restaurant managers. RESULTS: Literature exploring food environments in sports settings was limited and had some important methodological limitations. No studies comprehensively described foods available at clubs or stadia, and only one explored the association between food and beverage sponsorship and club incomes. Club policies focused on the impact of health promotion funding rather than the impact of sponsorship or food availability in sports settings. CONCLUSIONS: Further research, including comprehensive studies of the food environment in sports settings, is required to document the availability, sponsorship and marketing of food and beverages at national, regional and club levels and to estimate how sports settings may influence children's diets.
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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 | 0.012 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.013 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".