Database of the iodine content of food and diets populated with data from published literature
Bibliographic record
Abstract
A database of results for the iodine content of foods and die ts was prepared for a DFID funded project looking at Environmental Controls in Iodine Deficiency Disorders. It was populated with citations from the literature and contains 732 records. On the basis of these data, the geometric mean result for the iodine content of foods is 87 μg/kg, from 494 citations. Using classifications based on food type the following order for levels of iodine is determined: Marine fish (1455.9 μg/kg) > Freshwater fish (102.8 μg/kg) > Leafy vegetables (88.8 μg/kg) > Dairy (83.9 μg/kg) > Other vegetables (80.1 μg/kg) > Meat (68.4 μg/kg) > Cereals (56.0 μg/kg) > Fresh fruit (30.6 μg/kg) > Bread (17.0 μg/kg) > Water (6.4 μg/l) (The figure in brackets represents the geometric mean value for each group) The results show that in general grain crops are poorer sources of iodine than vegetables and that there is some equivocal evidence to suggest that leafy vegetables contain higher iodine concentrations than other vegetables but fish and seaweed are by far the greatest natural sources of iodine in foodstuffs. The geometric mean result for the average daily dietary intake is 161 μg/day, based on 84 citations. It is noted that vegetarian and vegan diets often do not meet the recommended adult daily intake of 150 μgI/day due to the lack of dairy, meat and fish components. Results also show that Japanese, USA and Canadian dietary intakes are higher than other countries. Intake depends not only on the iodine content of the food but also on the composition of the diet. Results show that food accounts for over 90% of human iodine exposure in most circumstances with water and air providing minimal inputs. However, in subsistence populations drinking highiodine groundwaters, water can contribute more than 20% of the dietary intake. Results of dietary studies show the following general order of percentage daily iodine intake from the main food groups in Western Countries: Dairy (50%) > Cereals (20%) > Fish (9%) > Meat (8%) > Vegetables (7%) > Sweets (5%) > Fruits (1%) The majority of iodine in Western diets comes from adventitious sources such as iodophors in the dairy industry, red food colouring and improvers in cereals, bread, meat and sweets. Removing these components to equate to a developing country diet where people are often dependant on staple grain foodstuffs such as rice shows that intakes fall below 100 μg/day. It is concluded that without adventitious sources of iodine or a marine foods component, most diets would fail to provide the recommended daily intake of 150 μg/day.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".