Trends in food supply, diet, and the risk of non-communicable diseases in three Small Island Developing States: implications for policy and research
Bibliographic record
Abstract
Introduction Small island developing states (SIDS) are a diverse group of coastal and tropical island countries primarily located in the Caribbean and Pacific. SIDS share unique social, economic, and environmental vulnerabilities, high dependency on food imports, and susceptibility to inadequate, unhealthy diets, with high burdens of two or more types of malnutrition. Our objective was to examine trends in food availability, imports, local production, and risks of non-communicable diseases (NCDs) in three SIDS: Haiti, Saint Vincent and the Grenadines (SVG) and Fiji. Methods Data on food availability, imports, exports, and production was extracted from the Food and Agriculture Organization Database (FAOSTAT), and on overweight, obesity and diabetes prevalence from the NCD Risk Factor Collaboration database (NCD-RisC) from 1980 to 2018. Data were collated, graphed, and used to calculate import dependency ratios (IDRs) using Excel and R software. Results Between 1980 and 2018, the availability of calories per capita per day has risen in Fiji and SVG by over 500, to around 3000. In Haiti, the increase is around 200, to a level of 2,200 in 2018, and in all three settings, > 10% of calories in 2018 came from sugar. In Fiji and Haiti, the availability of fruit and vegetables is <400 g per person per day (the minimum intake recommended by WHO). Between 1980 and 2010, both Fiji and SVG experienced high IDRs: around 80% (Fiji) and 65% (SVG). In Haiti, IDR has more than doubled since 1980, to around 30%. The prevalence of obesity (BMI > 30 Kg/m 2 ) has increased since 1980 (by 126% to 800%) and is substantially higher in women. In the most recent data for Fiji, an estimated 35% of women are obese (24% men); in SVG, 30% women (15% men); and in Haiti, 26% women (15% men). Conclusion The increase in per capita availability of calories, which has taken place since 1980, is concurrent with an increase in IDR, a loss of local food, and increases in obesity prevalence. These findings highlight the importance of further research to understand the drivers of food supply transformations, and to influence improving nutrition, through production, availability, and consumption of nutritious local foods.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".