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Record W2620063736 · doi:10.4314/ahs.v17i1.4

How weight during pregnancy influences the association between pre-pregnancy body mass index and types of delivery and birth: a comparison of urban and rural areas

2017· article· en· W2620063736 on OpenAlexafffund
Manoochehr Babanezhad

Bibliographic record

VenueAfrican Health Sciences · 2017
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsUniversity of Waterloo
FundersGolestan University of Medical SciencesUniversity of Waterloo
KeywordsMedicineOverweightBody mass indexPregnancyObstetricsFetal macrosomiaBirth weightLow birth weightPrenatal careObesityWeight gainMass indexGestational diabetesPopulationGestationEnvironmental healthBody weightEndocrinology

Abstract

fetched live from OpenAlex

BACKGROUND: Women in study areas suffered from the problems of caesarean delivery (CD), low birth weight (LBW), and macrosomia. OBJECTIVE: To investigate how gestational weight gain (GWG) influences the effect of the pre-pregnancy body mass index (BMI) on the risks of CD, LBW, and macrosomia in urban and rural areas in a city of Iran. METHODS: We used 767 and 612 eligible subjects from the public health care centers in urban and rural areas respectively. RESULTS: The risk of CD increased from 74% to 2.62-fold in urban and from 62% to 2.15-fold in rural areas, and the risk of macrosomia increased from 58% to 2.35-fold in urban and from 47% to 96% in rural areas, among obese women compared to normal weight women who gained above median GWG. The risk of LBW increased from 38% to 92% in urban and from 49% to 97% in rural areas among lean women compared to normal weight women who gained below median GWG. CONCLUSION: These findings strongly support the need to reform adequate pre-pregnancy weight and GWG against the risks of CD and macrosomia among overweight and obese women, and against the risk of LBW among lean women in both areas.

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 score0.009
Threshold uncertainty score0.347

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 studies0.0000.001
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 head0.029
GPT teacher head0.329
Teacher spread0.299 · 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

Citations5
Published2017
Admission routes2
Has abstractyes

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