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Record W4406598491 · doi:10.1186/s12884-025-07148-4

Physical behaviours during pregnancy may alter the association of maternal insulin sensitivity with neonatal adiposity: a prospective pre-birth cohort of mother-child pairs

2025· article· en· W4406598491 on OpenAlexafffund
Piraveena Satkunanathan, Catherine Allard, Myriam Doyon, Patrice Perron, Luigi Bouchard, Marie‐France Hivert, Tricia M. Peters

Bibliographic record

VenueBMC Pregnancy and Childbirth · 2025
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-JeanUniversité de SherbrookeCentre Hospitalier Universitaire de SherbrookeMcGill UniversityJewish General Hospital
FundersCanadian Institutes of Health ResearchFonds de Recherche du Québec - SantéDiabète QuébecAmerican Diabetes Association
KeywordsMedicineReproductive medicineProspective cohort studyPregnancyObstetricsCohort studyInsulin sensitivityCohortAssociation (psychology)Insulin resistancePediatricsInsulinEndocrinologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Lower maternal insulin sensitivity during pregnancy is associated with greater fetal adiposity. Physical activity can improve insulin sensitivity, but it is not known if physical behaviours influence the known association of maternal insulin sensitivity with offspring adiposity. This study aimed to investigate the moderating impact of physical behaviours on this association. METHODS: Pregnant women (n = 812) from the Gen3G cohort were recruited during the first trimester of pregnancy and followed until delivery. At the first (V1) and second trimester (V2) hospital visits, Gen3G staff measured anthropometry, and participants reported sleep duration as well as leisure physical activity and sedentary behaviour via lifestyle questionnaires. We used plasma glucose and insulin values from the 75 g oral glucose tolerance test at V2 to calculate insulin sensitivity using the Matsuda index. We recorded birthweight from electronic medical records. Among a subset of neonates (n = 265), trained research staff measured skinfold thickness using a calibrated skinfold caliper following standardized protocols to estimate neonatal adiposity. Linear regression analyses assessed the association of insulin sensitivity with birthweight z-score and sum of neonatal skinfold thickness, adjusting for maternal age, race/ethnicity, gravidity, smoking, with and without adjustment for maternal body mass index at V1. We evaluated moderation by physical activity, sedentary behaviour, or nighttime sleep duration using interaction terms and stratified analyses for the association of maternal insulin sensitivity with offspring birthweight and with offspring adiposity. RESULTS: Lower Matsuda index was associated with higher birthweight z-score (ß±SE= -0.180 ± 0.056, p = 0.001) and with higher sum of skinfold thickness (neonatal adiposity) (ß±SE=-0.877 ± 0.383, p = 0.02) in fully adjusted models. The association between Matsuda index and sum of skinfold thickness was weaker in women with higher levels of physical activity at V2 ([high ≥ 1.26 kcal/kg/day] ß±SE=-0.15 ± 0.65) compared to women with lower levels [low < 1.26 kcal/kg/day] ß±SE=-1.36 ± 0.51, P-interaction = 0.01). We also observed potential interactions of sleep and sedentary behaviour at V2 with Matsuda index for the association with birthweight z-score. We did not observe effect modification by levels of physical behaviours assessed at V1. CONCLUSION: The association between lower insulin sensitivity and higher neonatal adiposity was attenuated in women with higher physical activity levels in the second trimester, independent of maternal body mass index.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.004
GPT teacher head0.233
Teacher spread0.229 · 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".

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Citations1
Published2025
Admission routes2
Has abstractyes

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