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Record W4318542971 · doi:10.1080/09637486.2023.2171371

First-trimester diet quality in association with maternal subcutaneous and visceral adipose tissue thicknesses and glucose homeostasis during pregnancy

2023· article· en· W4318542971 on OpenAlexafffund
Émilie Bernier, Anne-Sophie Plante, Julie Robitaille, Simone Lemieux, M. Fusco Girard, Emmanuel Bujold, Claudia Gagnon, S. John Weisnagel, André Tchernof, Anne‐Sophie Morisset

Bibliographic record

VenueInternational Journal of Food Sciences and Nutrition · 2023
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsUniversité LavalCanadian Nutrition Society
FundersDanone Institute of Canada
KeywordsPregnancyInsulin resistanceMedicineInternal medicineEndocrinologyGlucose homeostasisAdipose tissueGestationInsulinFetusBody mass indexGestational diabetesBiology

Abstract

fetched live from OpenAlex

We aimed to characterise the associations between first-trimester diet quality, adiposity, and glucose homeostasis measurements throughout pregnancy in a sample of 104 healthy pregnant women. Three Web-based 24-h recalls were completed, from which the Alternate Healthy Eating Index (AHEI) was calculated. At each trimester (12.5 ± 0.7, 22.8 ± 1.0, and 33.6 ± 1.3 weeks of gestation), fasting glucose and insulin were measured to compute an insulin resistance index (HOMA-IR). Subcutaneous and visceral adipose tissue thicknesses were estimated by ultrasound at the end of the first trimester. Inverse associations were observed between the first-trimester AHEI and first-trimester fasting insulin (r = 0.24; p < 0.05), and HOMA-IR (r = −0.22; p < 0.05), as well as third-trimester fasting insulin (r = −0.20; p < 0.05). A trend was also observed between first-trimester AHEI and first-trimester SAT thickness (r = −0.17; p < 0.1). Pre- and early-pregnancy adiposity measurements were identified as high predictors fasting insulin concentrations throughout pregnancy. Higher early-pregnancy diet quality is associated with more favourable metabolic measurements during pregnancy.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.053
Threshold uncertainty score0.201

Codex and Gemma teacher scores by category

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

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 head0.022
GPT teacher head0.320
Teacher spread0.298 · 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 teacher head, 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

Citations7
Published2023
Admission routes2
Has abstractyes

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