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Urinary iodine and goiter in preschool children from the Amhara region, Ethiopia (804.23)

2014· article· en· W1749585484 on OpenAlexaff
Dawd Gashu, Karim Bougma, Kimberly Harding, Aregash Samuel, Abdulaziz Adish, Gulelat Desse Haki, Grace S. Marquis

Bibliographic record

VenueThe FASEB Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicThyroid Disorders and Treatments
Canadian institutionsNutrition InternationalMcGill University
Fundersnot available
KeywordsGoiterMedicineIodine deficiencyIodised saltUnderweightPediatricsMicronutrientEnvironmental healthThyroidInternal medicineBody mass indexOverweightPathology

Abstract

fetched live from OpenAlex

Iodine deficiency (ID) is highly prevalent in Ethiopia. As part of a salt iodization project, children ( n=688 ) 54‐60 months of age were randomly selected from 26 districts of the Amhara region, Ethiopia. Anthropometry, urinary iodine (UI) and goiter were assessed and the presence of visible goiter in the family was queried between October, 2011‐March, 2012. Children’s nutritional status was categorized using WHO standards. UI was determined using the Sandell‐Kolthoff reaction. Goiter was assessed by palpation following the WHO/UNICEF/ICCIDD guidelines. Stunting (<‐2HAZ) was 43.2% while underweight (<‐2WAZ) was 29.9 %. The median UI was 11.4 µg/L and varied widely by district (0‐286 µg/L). Individual values ranged from 0‐502 µg/L. Overall, 20.9 % of children had visible goiter and 23 % had palpable goiter, with variation by district in total goiter rate from 5‐79%. Goiter prevalence was significantly higher in children with visible goiter in the family than in children from families without visible goiter. Median UI was higher (p=0.001) in children from families without visible goiter than from families with visible goiter (20 vs. 4.1 µg/L), respectively. Our data illustrate the severity of ID in Amhara region and the need for rapid and complete implementation of salt iodization. The wide variation in goiter prevalence and UI among districts emphasizes the importance of both national and local monitoring programs Grant Funding Source : Funded by Micronutrient Initiative and The German Academic Exchange Service

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.011
GPT teacher head0.235
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2014
Admission routes1
Has abstractyes

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