An overview on the nutrition transition and its health implications: Tunisia case
Bibliographic record
Abstract
Background: In the last decades, Tunisia has undergone major demographic, socio-economic and lifestyle (including diet) changes, with drastic increases in excess adiposity and nutrition related non-communicable diseases (NCDs). This review provides an update of the nutritional situation in Tunisia. Methods: Several Tunisian datasets or international databases were used to assess availability and consumption of foods and health outcomes. Results: Both from national aggregated availability data and individual food consumption data, there was a trend both of increasing food intake and modernization/westernization of the diet (especially in urban areas), towards more consumption of dairy and meat products, sugar, fat and salt. But consumption of fruits and vegetables was still above WHO recommendations. Except for iodine, micronutrients deficiency (iron, vitamin A and D) was markedly, but unevenly, present among specific groups (e.g., a third of adult women had anaemia). Among infants, both exclusive and predominant breastfeeding were low, while the minimum diet diversification rate was 63%. Among children, stunting was residual but increase of overweight was a concern. In 2016 17.6% of men and 34.6 % of women over 15 y. were obese and 15.5% had diabetes, a twofold increase in the last decades. These prevalences were much higher in urban and more developed areas. Also, 86% of the mortality rate was attributable to NCDs. Conclusion: Addressing the double burden of malnutrition and NCDs is a priority and should be based on a sustainability framework, involve a diversity of stakeholders and emphasize double duty actions and reduction of nutrition and health inequalities
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".