Modifying the food environment for childhood obesity prevention: challenges and opportunities
Bibliographic record
Abstract
The prevention of childhood obesity is a global priority. However, a range of complex social and environmental influences is implicated in the development of obesity and chronic disease that goes beyond the notion of individual choice. A population-level approach recognises the importance of access to and availability of healthy foods outside the home. These external food environments, in restaurants, supermarkets, and in school, or recreation and sports settings, are often characterised by energy dense, nutrient-poor food items that do not reflect the current nutritional guidelines for health. In addition, our understanding of these broader influences on nutritional intake is still limited. Particularly, lacking is a clear understanding of what constitutes the food environment, as well as robust measures of components of the food environment across different contexts. Therefore, this review summarises the literature on food environments of relevance to childhood obesity prevention, with a focus on places where children live, learn and play. Specifically, the paper highlights the approaches and challenges related to defining and measuring the food environment, discusses the aspects of the food environment unique to children and reports on environmental characteristics that are being modified within community, school and recreational settings. Results of the review show the need for a continued focus on understanding the intersection between individual behaviour and external factors; improved instrument development, especially regarding validity and reliability; clearer reported methodology including protocols for instrument use and data management; and considering novel study design approaches that are targeted at measuring the relationship between the individual and their food environment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".