Cost and affordability implications of transitioning from current diets to National dietary guidelines and EAT-Lancet recommendations in Argentina: a modelling study
Bibliographic record
Abstract
BACKGROUND: Current dietary patterns contribute to health issues and pose high demands on the food production system, leading to environmental degradation. This paper aims to analyze the cost and affordability of current diets in Argentina, compared to one diet based on National Dietary Guidelines and 3 variants of diets based on EAT-Lancet Recommendations. METHODS: The methodology proposed by INFORMAS (International Network for Food and Obesity/Non-communicable Diseases Research, Monitoring and Action Support) was used to design six model diets for a reference household, considering the most consumed food products by the Argentinean population and similar healthier and/or more environmentally sustainable options. Nutritional information and prices of food products were obtained from official sources. Monte Carlo Simulations were performed to estimate the average cost of the diets (and variability). Affordability was measured as the percentage of average monthly household income each model diet represents. RESULTS: On average the diet based on National Dietary Guidelines was the most expensive (274.95 USD; 95% CI: 274.85-275.05), followed by the current diet (261.84 USD; 95% CI: 261.62-262.06), the flexitarian diet that includes higher amount of animal protein sources (design to be more similar to the current consumption pattern in Argentina) (259.43 USD; 95% CI: 259.30-259.55), and then the vegan diet (256.96 USD; 95% CI: 256.90-257.03). The lowest costs were found for the current isocaloric diet (248.29 USD; 95% CI: 248.06-248.52) and the flexitarian diet with less animal proteins (248.37 USD; 95% CI: 248.26-248.48). Between 53% and 59% of the average income is needed to cover the cost of diets. CONCLUSIONS: Diets based on National Dietary Guidelines are on average the most expensive (least affordable), while the least expensive (most affordable) are the current isocaloric diet and the flexitarian diet with fewer animal protein sources, suggesting that there are dietary options that can reduce greenhouse gas emissions and provide health benefits without increasing food expenses.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".