Perceived Availability of Healthy and Unhealthy Foods in the Community, Work, and Higher Education Settings across Five Countries: Findings from the International Food Policy Study 2018
Bibliographic record
Abstract
BACKGROUND: Food environments play a key role in dietary behavior and vary due to different contexts, regulations, and policies. OBJECTIVES: This study aimed to characterize the perceived availability of healthy and unhealthy foods in 3 different settings in 5 countries. METHODS: We analyzed data from the 2018 International Food Policy Study, a cross-sectional survey of adults (18-100 y, n = 22,824) from Australia, Canada, Mexico, the United Kingdom (UK), and the USA. Perceived availability of unhealthy (junk food and sugary drinks) and healthy foods (fruit or vegetables, healthy snacks, and water) in the community, workplace, and university settings were measured (i.e. not available, available for purchase, or available for free). Differences in perceived availability across countries were tested using adjusted multinomial logistic regression models. RESULTS: Across countries, unhealthy foods were perceived as highly available in all settings; in university and work settings unhealthy foods were perceived as more available than healthy foods. Australia and Canada had the highest perceived availability of unhealthy foods (range 87.5-90.6% between categories), and the UK had the highest perceived availability of fruits and vegetables for purchase (89.3%) in the community. In university and work settings, Mexico had the highest perceived availability for purchase of unhealthy foods (range 69.9-84.9%). The USA and the UK had the highest perceived availability of fruits and vegetables for purchase (65.3-66.3%) or for free (21.2-22.8%) in the university. In the workplace, the UK had high perceived availability of fruits and vegetables for purchase (40.2%) or for free (18.5%), and the USA had the highest perceived availability of junk food for free (17.3%). CONCLUSIONS: Across countries, unhealthy foods were perceived as highly available in all settings. Variability between countries may reflect differences in policies and regulations. Results underscore the need for the continuation and improvement of policy efforts to generate healthier food environments.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".