Standardized Map of Iodine Status in Europe
Bibliographic record
Abstract
Background: Knowledge about the population's iodine status is important, because it allows adjustment of iodine supply and prevention of iodine deficiency. The validity and comparability of iodine-related population studies can be improved by standardization, which was one of the goals of the EUthyroid project. The aim of this study was to establish the first standardized map of iodine status in Europe by using standardized urinary iodine concentration (UIC) data. Materials and Methods: We established a gold-standard laboratory in Helsinki measuring UIC by inductively coupled plasma mass spectrometry. A total of 40 studies from 23 European countries provided 75 urine samples covering the whole range of concentrations. Conversion formulas for UIC derived from the gold-standard values were established by linear regression models and were used to postharmonize the studies by standardizing the UIC data of the individual studies. Results: In comparison with the EUthyroid gold-standard, mean UIC measurements were higher in 11 laboratories and lower in 10 laboratories. The mean differences ranged from −36.6% to 49.5%. Of the 40 postharmonized studies providing data for the standardization, 16 were conducted in schoolchildren, 13 in adults, and 11 in pregnant women. Median standardized UIC was <100 μg/L in 1 out of 16 (6.3%) studies in schoolchildren, while in adults 7 out of 13 (53.8%) studies had a median standardized UIC <100 μg/L. Seven out of 11 (63.6%) studies in pregnant women revealed a median UIC <150 μg/L. Conclusions: We demonstrate that iodine deficiency is still present in Europe, using standardized data from a large number of studies. Adults and pregnant women, particularly, are at risk for iodine deficiency, which calls for action. For instance, a more uniform European legislation on iodine fortification is warranted to ensure that noniodized salt is replaced by iodized salt more often. In addition, further efforts should be put on harmonizing iodine-related studies and iodine measurements to improve the validity and comparability of results.
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| 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".