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Record W2885832469 · doi:10.1186/s40798-018-0148-x

Exercise in Pregnancy and Children’s Cardiometabolic Risk Factors: a Systematic Review and Meta-Analysis

2018· review· en· W2885832469 on OpenAlexafffund
Laetitia Guillemette, Jacqueline Hay, D. Scott Kehler, Naomi C. Hamm, Christopher Oldfield, Jonathan McGavock, Todd A. Duhamel

Bibliographic record

VenueSports Medicine - Open · 2018
Typereview
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsSt. Boniface HospitalUniversity of ManitobaChildren's Hospital Research Institute of ManitobaResearch Manitoba
FundersCanadian Institutes of Health ResearchCanadian Diabetes AssociationUniversity of ManitobaLawson FoundationResearch ManitobaHeart and Stroke Foundation of Canada
KeywordsMedicineMeta-analysisRandomized controlled trialObservational studyDyslipidemiaOffspringPregnancyConfidence intervalPhysical therapyCohort studyBirth weightRelative riskPediatricsInternal medicineDisease

Abstract

fetched live from OpenAlex

Maternal metabolic health during the prenatal period is an established determinant of cardiometabolic disease risk. Many studies have focused on poor offspring outcomes after exposure to poor maternal health, while few have systematically appraised the evidence surrounding the role of maternal exercise in decreasing this risk. The aim of this study is to characterize and quantify the specific impact of prenatal exercise on children’s cardiometabolic health markers, at birth and in childhood. A systematic review of Scopus, MEDLINE, EMBASE, CENTRAL, CINAHL, and SPORTDiscus up to December 2017 was conducted. Randomized controlled trials (RCTs) and prospective cohort studies of prenatal aerobic exercise and/or resistance training reporting eligible offspring outcomes were included. Four reviewers independently identified eligible citations and extracted study-level data. The primary outcome was birth weight; secondary outcomes, specified a priori, included large-for-gestational age status, fat and lean mass, dyslipidemia, dysglycemia, and blood pressure. We included 73 of the 9804 citations initially identified. Data from RCTs was pooled using random effects models. Statistical heterogeneity was quantified using the I2 test. Analyses were done between June and December 2017 and the search was updated in December 2017. Fifteen observational studies (n = 290,951 children) and 39 RCTs (n = 6875 children) were included. Observational studies were highly heterogeneous and had discrepant conclusions, but globally showed no clinically relevant effect of exercise on offspring outcomes. Meta-analyzed RCTs indicated that prenatal exercise did not significantly impact birth weight (mean difference [MD] − 22.1 g, 95% confidence interval [CI] − 51.5 to 7.3 g, n = 6766) or large-for-gestational age status (risk ratio 0.85, 95% CI 0.51 to 1.44, n = 937) compared to no exercise. Sub-group analyses showed that prenatal exercise reduced birth weight according to timing (starting after 20 weeks of gestation, MD − 84.3 g, 95% CI − 142.2, − 26.4 g, n = 1124), type of exercise (aerobic only, MD − 58.7 g, 95% CI − 109.7, − 7.8 g; n = 2058), pre-pregnancy activity status (previously inactive, MD − 34.8 g, 95% CI − 69.0, − 0.5 g; n = 2829), and exercise intensity (light to moderate intensity only, MD − 45.5 g, 95% CI − 82.4, − 8.6 g; n = 2651). Fat mass percentage at birth was not altered by prenatal exercise (0.19%, 95% CI − 0.27, 0.65%; n = 130); however, only two studies reported this outcome. Other outcomes were too scarcely reported to be meta-analyzed. Prenatal exercise does not causally impact birth weight, fat mass, or large-for-gestational-age status in a clinically relevant way. Longer follow up of offspring exposed to prenatal exercise is needed along with measures of relevant metabolic variables (e.g., fat and lean mass). Protocol registration number: CRD42015029163 .

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)0.012
metaresearch head score (Gemma)0.034
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.034
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0160.026
Bibliometrics0.0080.010
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.390
Teacher spread0.309 · 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
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

Citations16
Published2018
Admission routes2
Has abstractyes

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