How supportive is the global food supply of food-based dietary guidelines? A descriptive time series analysis of food supply alignment from 1961 to 2013
Bibliographic record
Abstract
BACKGROUND: FAO/WHO have encouraged national governments to create food-based dietary guidelines (FBDGs) to support healthy diets. However, little is known about the extent to which food supply composition aligns with FBDGs, thereby structurally supporting or undermining population-level adherence. It is also unclear how this alignment has evolved over time. The aim of this study was to determine to what extent the global food supply aligns with FBDGs, and to examine historical trends. METHODS: Descriptive time series analysis of food supply alignment (FSA), 1961-2013. FSA was characterised as a ratio dividing country-level food supply data by FBDG across four food groups: fruit and vegetables (FV); sugar (SU); fish and seafood (FS); and red and processed meat (RP). FBDG data was collected from guidance produced by international bodies, and from countries with published FBDGs. The food supply was estimated using yearly FAOSTAT data. A population-weighted average of this ratio was created for all countries included in the analysis, and stratified by region and country income. FINDINGS: FBDGs from 89 countries were included. Of those, 80% had country guidelines for FV, 34% for SU, 44% for FS, and 21% for RP. FSA (1.0 = perfect alignment) based on global guidelines showed a higher supply than recommended for FV (1.2), SU (1.2) and RP (1.1). FSA based on country guidelines showed a lower supply than recommended for FV (0.9) and a higher supply than recommended for SU (2.3), RP (2.3) and FS (1.4). FSA also showed substantial differences in levels and trends across region and country income. INTERPRETATION: As of 2013, food supplies were not aligned with national and international FBDGs and misalignment persisted across five decades with subtantial variation in trends based on geography and country income. The long running nature of these trends suggest that the transition toward sustainable and healthful food systems represent a signifiant global challange. Additionally, acknowledging the degree of misalignment between macro-level structural factors, such as the composition of the food supply, in relation to national or global food policy aims may further aid efforts for population level adherence.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".