Association between physical activity education and prescription during prenatal care and maternal and fetal health outcomes: a quasi-experimental study
Bibliographic record
Abstract
BACKGROUND: Physical activity (PA) during pregnancy is associated with healthy gestational weight gain (GWG) and a reduced risk of developing gestational diabetes (GD), gestational hypertension (GHT) and fetal macrosomia. However, in Canada, less than 20% of pregnant women meet PA recommendations. This study assessed associations between an intervention including PA education by prenatal nurses and a PA prescription delivered by physicians and fetal and maternal outcomes. METHODS: This is a quasi-experimental study. Two groups of women who received their prenatal care at the obstetrics clinic of a university hospital were created. In the first group, 394 pregnant women followed at the clinic received standard care. In the second group, 422 women followed at the clinic received standard care supplemented with education on the relevance of PA during pregnancy and a prescription for PA. Data for both study groups were obtained from the medical records of the mothers and their newborns. Logistic regressions were used to compare the odds of developing excessive GWG, GD, GHT, and fetal macrosomia between the two study groups. RESULTS: The addition of PA education and PA prescription to prenatal care was associated with 29% lower odds of developing excessive GWG (adjusted odds ratios (OR) 0.71, 95% confidence intervals (CI) 0.51-0.99), 73% lower odds of developing GHT (0.27, 0.14-0.53), 44% lower odds of fetal macrosomia (> 4 kg) (0.56, 0.34-0.93), and 40% lower odds of being large for gestational age (0.60, 0.36-0.99). The intervention was not associated with a difference in odds of developing GD (0.48, 0.12-1.94). CONCLUSIONS: The inclusion of education and prescription of PA as part of routine prenatal care was associated with improvements in maternal and fetal health outcomes, including significantly lower odds of GWG, GHT and macrosomia.
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 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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".