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Record W2024171603 · doi:10.1155/2012/470247

Preventing Long-Term Risk of Obesity for Two Generations: Prenatal Physical Activity Is Part of the Puzzle

2012· review· en· W2024171603 on OpenAlexafffund
Stéphanie-May Ruchat, Michelle F. Mottola

Bibliographic record

VenueJournal of Pregnancy · 2012
Typereview
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsChildren’s Health Research InstituteWestern University
FundersCanadian Diabetes Association
KeywordsMedicineOverweightPsychological interventionObesityPregnancyContext (archaeology)Weight gainIncidence (geometry)Postpartum periodPediatricsGerontologyObstetricsBody weightEndocrinologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: The period surrounding pregnancy has been identified as a risk period for overweight/obesity in both mother and child because of excessive gestational weight gain (GWG). The promotion of a healthy GWG is therefore of paramount importance in the context of the prevention of obesity in the current and next generations. OBJECTIVE: To provide a comprehensive overview of the effect of prenatal physical activity interventions, alone or in combination with nutritional counselling, on GWG and to address whether preventing excessive GWG decreases the incidence of infant high birth weight and/or postpartum weight retention. METHOD: A search of the PubMed database was conducted to identify all relevant studies. Nineteen studies were included in this review: 13 interventions combining physical activity, nutrition, and GWG counselling and 6 interventions including physical activity alone. RESULTS: Prenatal lifestyle interventions promoting healthy eating and physical activity habits appear to be the most effective approach to prevent excessive GWG. Achievement of appropriate GWG may also decrease the incidence of high infant birth weight and postpartum weight retention. CONCLUSION: Healthy eating habits during pregnancy, combined with an active lifestyle, may be important elements in the prevention of long-term risk of obesity for two generations.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.948
Threshold uncertainty score0.412

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.083
GPT teacher head0.397
Teacher spread0.314 · 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 designOther design
Domainnot available
GenreReview

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

Citations36
Published2012
Admission routes2
Has abstractyes

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