Development of a Malian food exchange system based on local foods and dishes for the assessment of nutrient and food intake in type 2 diabetic subjects
Bibliographic record
Abstract
Objective: To develop exchange lists for the assessment of food and nutrient intakes for people with diabetes in Mali.Design: Based on North American exchange lists, a Malian food exchange system was developed using food composition tables for Mali. Dietary intakes were assessed by two 48-hour dietary recalls. Daily numbers of exchanges were determined for the whole sample and for each gender. Energy and macronutrient intakes obtained by a software-based nutritional analysis of the dietary recalls were compared with the average energy and nutrient values calculated with the exchange lists.Setting: Centre National de Lutte contre le Diabète.Subjects: Seventeen male and 40 female adults with type 2 diabetes.Results: The analysis of food recalls using the Malian exchange system showed that subjects consumed the following numbers of exchanges per day: 2.6 ± 1.5 meat and substitutes, 0.5 ± 0.8 legumes, 0.7 ± 1.2 milk, 8.0 ± 4.1 fat, 8.3 ± 3.0 starch, 1.5 ± 0.9 vegetables, 0.2 ± 0.5 fruit, and 0.0 ± 0.2 sugar-added foods, totalling 1 854 ± 648 kcal, 260 ± 92 g carbohydrate, 56 ± 23 g protein and 63 ± 31 g fat. These results concerning energy and macronutrients did not differ significantly from those obtained from the nutritional analysis of food recalls with software using data from the Food Composition Table for Mali. Compared to women, men consumed significantly larger numbers of exchanges of meat and substitutes, fat, starch, and fruit. No significant differences were found for the intakes of legumes, milk, vegetables and sugar-added foods.Conclusions: This study allowed the development of Malian food exchange lists and demonstrated their usefulness for the description of the dietary pattern and energy and macronutrient intakes of male and female Malian type 2 diabetic patients.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".