Iodine Status and Availability of Iodized Salt: An Across-Country Analysis
Bibliographic record
Abstract
BACKGROUND: Iodine deficiency has serious consequences, and the Universal Salt iodization initiative has attempted to reduce the extent of deficiency. OBJECTIVE: We aim to see how far across-country variations in urinary iodine in school-age children can be explained by environmental factors, particularly soil iodine and the availability of iodized salt. METHODS: We use simple multivariate regression for two separate datasets, one for 30 developing countries, and one for 13 developed countries, using data on availability of iodized salt and soil iodine levels. RESULTS: Median urinary iodine excretion is significantly and positively related to household availability of iodized salt (elasticity, 0.73) for developing countries, but the soil coefficient is not significant, probably because the dummy variable is not well measured. For the developed countries, there is a positive and significant effect of salt penetration rates (elasticity, 0.83) and a positive and significant effect of soil iodine (elasticity, 0.77). There is also a suggestion that countries with more serious soil deficits are more likely to iodize salt, so that univariate regressions of urinary iodine excretion on salt availability or penetration rates underestimate the beneficial effects of iodized salt availability on iodine nutrition. CONCLUSIONS: There are limitations to cross-sectional (ecologic) studies such as this, and the data are not perfect. Nevertheless, the results provide support for policies to iodize salt, given the widespread deficiency of iodine in diets worldwide.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".