Maternal Water Exercise And Its Effects On Weight Gain And Fetal Outcomes: A Meta-analysis
Bibliographic record
Abstract
Physical activity during pregnancy is known to bring benefits not only for the mother but also for the fetus. Water-based exercises have been recommended as an adequate modality of exercise during pregnancy, however, no meta-analysis has analyzed the effects of water exercise programs on maternal weight gain and fetal outcomes including birthweight. PURPOSE: To conduct a systematic review and meta-analysis of randomized controlled trials to investigate the effects of prenatal water-based exercise on maternal weight gain and fetal outcomes. METHODS: Eligible trials were identified by a structured search of MEDLINE, EMBASE, ISI Web of Science, Scopus, and SportDiscus up to October 2018. Data were retrieved comparing standard care with standard care plus prenatal water exercise (at least once a week) for at least one of the following outcomes: maternal weight gain, gestational age at delivery, and/or fetal birthweight. Study selection and data extraction were performed by two independent reviewers. Random-effects meta-analysis was conducted for mean difference between exercise and control groups (PROSPERO registration: CRD42016039473). RESULTS: Our search yielded 1846 publications of which 1562 were assessed for eligibility. In total, 9 studies were eligible and included in the meta-analysis. Pregnant women who engaged in a water exercise program showed a significant difference in total maternal weight gain (5 RCTs, n=561, OR -1.00 [95% CI -1.55, -0.45], p<0.001) compared to standard care only. No significant effects on gestational age at delivery (8 RCTs, n=1442, OR 0.04 [95% CI -1.02, 1.10], p=0.94) and birthweight (8 RCTs, n=1427, OR -24.32 [95% CI -86.44, 37.80]) were found. CONCLUSION: Water exercise during pregnancy controls maternal weight gain without influencing the duration of pregnancy or baby weight. Health care providers can consider suggesting water-based exercises during pregnancy to promote appropriate weight gain.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.050 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".