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Record W2950975299 · doi:10.1093/cdn/nzz048.or35-07-19

Maternal Diet Quality and Infant Growth Trajectories During the First Year of Life (OR35-07-19)

2019· article· en· W2950975299 on OpenAlexaboutno aff
Andrea López‐Cepero, Lisa Nobel, Tiffany A. Moore-Simas, Milagros C. Rosal

Bibliographic record

VenueCurrent Developments in Nutrition · 2019
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOddsObservational studyOdds ratioBirth weightWeight gainPregnancyPediatricsDemographicsGestational ageObstetricsDemographyInternal medicineLogistic regressionBiologyBody weight

Abstract

fetched live from OpenAlex

To examine the association between maternal diet quality and infant weight for length growth trajectory during their first year of life. Participants were singleton infant-mother pairs (N = 77) enrolled in the Pregnancy and Postpartum Observational Dietary Study. Mothers completed socio-demographics and dietary (24-hour recalls) assessments at 3 months postpartum. The Alternate Healthy Eating Index (aHEI) was calculated to measure maternal diet quality. Infant weight for length measures from birth to 12 months were abstracted from pediatric records. World Health Organization guidelines were used to calculate infants’ weight for length percentiles. Group-based trajectory analysis was done to identify subgroups of infants with similar growth profiles and to evaluate the association between maternal aHEI and infant's growth trajectory. Models were adjusted for maternal age, race, education and excessive gestational weight gain (GWG). Mothers’ mean age was 28 years ± 5.2; 27% were Latina, and 55% had some college education or more; 60% had experienced excessive GWG; and their average aHEI was 26.7 ± 7.5. Three infant growth trajectories were identified: a low and stable growth group (43.2%), a rapid growth group (33.5%), and a moderate growth group (23.3%). Maternal aHEI was significantly associated with lower odds of having their infant in the rapid growth group (OR = 0.83; P = 0.012), with each unit increase in aHEI score being associated with 17% lower odds of infant's rapid growth. Trajectory models suggested three patterns of infant growth. Higher maternal diet quality was associated with lower odds of infant rapid growth. Future studies are needed to replicate these findings in larger cohorts and identify mediators of this association to prevent childhood obesity. CCTS (UL1TR001453), NCATS (UL1TR000161), NIMHD (1P60MD006912-02), CDC (U48-DP001933), NIGMS (R25GM113686-02), NHLBI (F30HL128012), and Canadian Institutes of Health Research (DFS-140394).

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 score0.003
Threshold uncertainty score0.249

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 head0.031
GPT teacher head0.317
Teacher spread0.286 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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