Which government policies to create sustainable food systems have the potential to simultaneously address undernutrition, obesity and environmental sustainability?
Bibliographic record
Abstract
INTRODUCTION: A transformation of food systems is urgently needed, given their contribution to three ongoing and interlinked global health pandemics: (1) undernutrition and food insecurity, (2) obesity and non-communicable diseases (NCDs), and (3) climate change and biodiversity loss. As policymakers make decisions that shape food systems, this study aimed to identify and prioritise policies with double- or triple-duty potential to achieve healthier and more environmentally sustainable food systems. METHODS: This study undertook a 4-step methodological approach, including (i) a compilation of international policy recommendations, (ii) an online survey, (iii) four regional workshops with international experts and (iv) a ranking for prioritisation. Policies were identified and prioritised based on their double- or triple-duty potential, synergies and trade-offs. Using participatory and transdisciplinary approaches, policies were identified to have double- or triple-duty potential if they were deemed effective in tackling two or three of the primary outcomes of interest: (1) undernutrition, (2) obesity/NCDs and (3) environmental degradation. RESULTS: The desk review identified 291 recommendations for governments, which were merged and classified into 46 initially proposed policies. Based on the results from the online survey, 61% of those policies were perceived to have double- or triple-duty potential. During the workshops, 4 potential synergies and 31 trade-offs of these policies were identified. The final list of 44 proposed policies for healthier and more environmentally sustainable food systems created was divided into two main policy domains: 'food supply chains' and 'food environments'. The outcome with the most trade-offs identified was 'undernutrition', followed by 'environmental sustainability', and 'obesity/NCDs'. Of the top five expert-ranked food supply chain policies, two were perceived to have triple-duty potential: (a) incentives for crop diversification; (b) support for start-ups, and small- and medium-sized enterprises. For food environments, three of the top five ranked policies had perceived triple-duty potential: (a) affordability of healthier and more sustainable diets; (b) subsidies for healthier and more sustainable foods; (c) restrictions on children's exposure to marketing through all media. CONCLUSION: This study identified and prioritised a comprehensive list of double- and triple-duty government policies for creating healthier and more environmentally sustainable food systems. As some proposed policies may have trade-offs across outcomes, they should be carefully contextualised, designed, implemented and monitored.
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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 | 0.029 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".