A Commercial Determinants of Health Perspective on the Food Environments of Public Hospitals for Children and Young People in High-Income Countries: We Need to Re-Prioritize Health
Bibliographic record
Abstract
There is growing evidence that public hospitals in high-income countries-in particular, Anglo-Saxon neoliberal countries (USA, UK, Canada, New Zealand, and Australia)-have been engaging with food retailers to attract private capital and maximise their incomes in a drive to reduce costs. Added to which, public hospital food can have a substantial influence on the health of children and young people. However, there is still relatively little research on food for young people in healthcare settings. This is concerning, as an appropriate food intake is vital not only for the prevention of and recovery from diseases, but also for the physical growth and psychological development of young people. This critical narrative review examined the available evidence on hospital food provision, practices, and environments, as well as children's experiences of hospitalization in high-income countries, drawing on both peer-reviewed articles and the grey literature. Our analytical lens for this review was the Commercial Determinants of Health (CDOH), a framework that necessitates a critical examination of commercial influences on individual, institutional, and policy practices relevant to health. Our findings illustrate the mechanisms through which the CDOH act as a barrier to healthy food and eating for children in hospitals in high-income countries. Firstly, hospital food environments can be characterised as obesogenic. Secondly, there is a lack of culturally inclusive and appropriate foods on offer in healthcare settings and an abundance of processed and convenience foods. Lastly, individualised eating is fostered in healthcare settings at the expense of commensal eating behaviours that tend to be associated with healthier eating. Public hospitals are increasingly facing commercial pressures. It is extremely important to resist these pressures and to protect patients, especially children and adolescents, from the marketing and selling of foods that have been proven to be addictive and harmful.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".