The Relationship between Self-Reported Exposure to Sugar-Sweetened Beverage Promotions and Intake: Cross-Sectional Analysis of the 2017 International Food Policy Study.
Bibliographic record
Abstract
Sugar-sweetened beverage (SSB) consumption is independently associated with several non-communicable diseases, so policymakers are increasingly implementing measures, such as marketing regulation, to reduce intake. To help understand how such measures work, this study examined the association between SSB consumption and self-reported exposure to SSB promotions, both overall and by type of promotion, and whether these relationships vary between the UK, USA, Canada, Mexico, and Australia. Cross-sectional analysis of the online 2017 International Food Policy Study was performed (n = 15,515). Participants were grouped into 5265 (34%) non-, 5117 (33%) low-, and 5133 (33%) high-SSB consumers. Multinomial logistic regression models examined whether SSB consumption varied by exposure to total SSB promotion and by type: traditional, digital, recreational environment, and functional environment. Multiplicative interactions were included to investigate international variations. An additional unit of total self-reported SSB promotion exposure increased the likelihood of participants being low SSB consumers (relative risk ratio (RRR) = 1.08, 95% confidence interval (CI) = 1.06-1.10) and high SSB consumers (RRR = 1.13, 95% CI = 1.11-1.16). Only exposure to traditional and digital promotion increased the likelihood of participants being SSB consumers, though this may be explained by degree of exposure, which was not measured in this study. Some evidence illustrated international variation in these relationships.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".