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Record W4220749058 · doi:10.1159/000522197

Associations between Gestational Weight Gain Adequacy and Neonatal Outcomes in Tanzania

2022· article· en· W4220749058 on OpenAlexfundno aff
Nandita Perumal, Dongqing Wang, Anne Marie Darling, Molin Wang, Enju Liu, Willy Urassa, Andrea B. Pembe, Wafaie Fawzi

Bibliographic record

VenueAnnals of Nutrition and Metabolism · 2022
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsMedicineWeight gainObstetricsPediatricsSmall for gestational agePregnancyBirth weightGestational ageBody mass indexLow birth weightMass indexTanzaniaInternal medicineBody weight

Abstract

fetched live from OpenAlex

INTRODUCTION: Gestational weight gain (GWG) is associated with fetal and newborn health; however, data from sub-Saharan Africa are limited. METHODS: We used data from a prenatal micronutrient supplementation trial among a cohort of human immunodeficiency virus-negative pregnant women in Dar es Salaam, Tanzania to estimate the relationships between GWG and neonatal outcomes. GWG adequacy was defined as the ratio of the total observed weight gain over the recommended weight gain based on the Institute of Medicine body mass index-specific guidelines. Neonatal outcomes assessed were stillbirth, perinatal death, preterm birth, low birthweight, macrosomia, small-for-gestational age (SGA), large-for-gestational age (LGA), stunting at birth, and microcephaly. Modified Poisson regressions with robust standard error were used to estimate the relative risk of newborn outcomes as a function of GWG adequacy. RESULTS: Of 7,561 women included in this study, 51% had severely inadequate (<70%) or inadequate GWG (70 to <90%), 31% had adequate GWG (90 to <125%), and 18% had excessive GWG (≥125%). Compared to adequate GWG, severely inadequate GWG was associated with a higher risk of low birthweight, SGA, stunting at birth, and microcephaly, whereas excessive GWG was associated with a higher risk of LGA and macrosomia. CONCLUSION: Interventions to support optimal GWG are needed and may contribute to preventing adverse neonatal outcomes.

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 score0.312
Threshold uncertainty score0.289

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 head0.051
GPT teacher head0.346
Teacher spread0.295 · 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

Citations14
Published2022
Admission routes1
Has abstractyes

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