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Record W4412125492 · doi:10.1249/mss.0000000000003811

Physical Activity before and during Pregnancy in Relation to Delivery, Neonatal, and Child Health Outcomes: A Meta-Analysis of Observational Studies with Meta-Regression

2025· article· en· W4412125492 on OpenAlexaff
Lingling Li, Haiyan Lin, Jordyn M. Cox, Rachel Wang, Allison Sivak, Margie H. Davenport, Chenxi Cai

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2025
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsAlberta Advanced EducationUniversity of Alberta
Fundersnot available
KeywordsObservational studyMeta-analysisMeta-regressionPregnancyMedicineRelation (database)ObstetricsInternal medicineComputer scienceBiologyData mining

Abstract

fetched live from OpenAlex

BACKGROUND: An increasing number of observational studies suggest that physical activity (PA) before or during pregnancy may reduce the risks of adverse delivery, neonatal, and child health outcomes, but the results remain conflicted and inconclusive. Many pregnant women fail to follow PA guidelines, suggesting that there must be a synthesis of real-world evidence. OBJECTIVE: To examine the influence of PA before and during pregnancy on delivery, neonatal, and child health outcomes. METHODS: Ten electronic databases have been searched until December 17, 2024. All types of observational studies were included, except for case studies and reviews, as long as they had data on women before or during pregnancy, looked at PA (either measured or reported), compared it to low or no PA, and examined outcomes related to birth (like preterm birth, low birth weight, cesarean section, small-for-gestational-age, larger-for-gestational-age, macrosomia) and child health (like body mass index z -score, overweight, body fat mass, and cognitive development). RESULTS: We included 79 observational studies ( N = 371,046). "Low" to "very low" certainty evidence revealed that compared with low levels of PA, high levels of PA before and during pregnancy were associated with a 13%-25% reduction in the odds of having a preterm delivery (before pregnancy: odds ratio (OR), 0.87 (95% confidence interval (CI), 0.79-0.97; I2 = 0%); during pregnancy: OR, 0.75 (95% CI, 0.68-0.82; I2 = 84%)). High levels of PA during pregnancy were also associated with reduced odds of having a cesarean section (OR, 0.73 (95% CI, 0.62-0.87; I2 = 89%)). Other outcomes were not associated with PA. To achieve at least a 10% reduction in the odds of preterm birth, pregnant women need to accumulate at least 216 MET·min·wk -1 of leisure time PA. CONCLUSIONS: Observational evidence suggests that higher PA levels before and during pregnancy may be associated with improved birth 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 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)0.033
metaresearch head score (Gemma)0.075
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.075
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0240.089
Bibliometrics0.0090.010
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0040.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.081
GPT teacher head0.389
Teacher spread0.308 · 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 designMeta-analysis
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

Citations3
Published2025
Admission routes1
Has abstractyes

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