MétaCan
Menu
Back to cohort
Record W3169944615 · doi:10.1186/s13044-021-00105-1

Associations between maternal urinary iodine assessment, dietary iodine intakes and neurodevelopmental outcomes in the child: a systematic review

2021· review· en· W3169944615 on OpenAlexaboutno aff
Anna M. Monaghan, Maria S. Mulhern, Emeir M. McSorley, JJ Strain, Matthew S. Dyer, Edwin van Wijngaarden, Alison J. Yeates

Bibliographic record

VenueThyroid Research · 2021
Typereview
Languageen
FieldMedicine
TopicThyroid Disorders and Treatments
Canadian institutionsnot available
FundersNational Institutes of HealthUlster University
KeywordsMedicineIodineIodine deficiencyPregnancyOffspringUrinary systemPediatricsEnvironmental healthNational Health and Nutrition Examination SurveyObstetricsInternal medicinePopulationThyroid

Abstract

fetched live from OpenAlex

OBJECTIVE: Mild to moderate iodine deficiency during pregnancy has been associated with adverse neurodevelopmental outcomes in offspring. Few research studies to date combine assessment of urinary iodine (UIC and/or ICr), biomarkers that best reflect dietary intake, with reported dietary intake of iodine rich foods in their assessment of iodine deficiency. Thus, a systematic review was conducted to incorporate both these important measures. DESIGN: Using PRISMA guidelines, a comprehensive search was conducted in three electronic databases (EMBASE®, MedLine® and Web of Science®) from January 1970-March 2021. Quality assessment was undertaken using the Newcastle Ottawa Scale. Eligible studies included reported assessment of iodine status through urinary iodine (UIC and/or ICr) and/or dietary intake measures in pregnancy alongside neurodevelopmental outcomes measured in the children. Data extracted included study author, design, sample size, country, gestational age, child age at testing, cognitive tests, urinary iodine assessment (UIC in μg/L and/or ICr in μg/g), dietary iodine intake assessment and results of associations for the assessed cognitive outcomes. RESULTS: Twelve studies were included with nine reporting women as mild-moderately iodine deficient based on World Health Organization (WHO) cut-offs for urinary iodine measurements < 150 μg/l, as the median UIC value in pregnant women. Only four of the nine studies reported a negative association with child cognitive outcomes based on deficient urinary iodine measurements. Five studies reported urinary iodine measurements and dietary intakes with four of these studies reporting a negative association of lower urinary iodine measurements and dietary iodine intakes with adverse offspring neurodevelopment. Milk was identified as the main dietary source of iodine in these studies. CONCLUSION: The majority of studies classified pregnant women to be mild-moderately iodine deficient based on urinary iodine assessment (UIC and/or ICr) and/or dietary intakes, with subsequent offspring neurodevelopment implications identified. Although a considerable number of studies did not report an adverse association with neurodevelopmental outcomes, these findings are still supportive of ensuring adequate dietary iodine intakes and urinary iodine monitoring throughout pregnancy due to the important role iodine plays within foetal neurodevelopment. This review suggests that dietary intake data may indicate a stronger association with cognitive outcomes than urinary iodine measurements alone. The strength of this review distinguishes results based on cognitive outcome per urinary iodine assessment strategy (UIC and/or ICr) with dietary data. Future work is needed respecting the usefulness of urinary iodine assessment (UIC and/or ICr) as an indicator of deficiency whilst also taking account of dietary intakes.

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)0.006
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.007
Bibliometrics0.0090.010
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.148
GPT teacher head0.465
Teacher spread0.317 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations31
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueThyroid ResearchSame topicThyroid Disorders and TreatmentsFrench-language works237,207