Reproductive history, maternal anxiety and past physical activity practice predict physical activity levels throughout pregnancy
Bibliographic record
Abstract
We compared physical activity (PA) levels between pregnant women who conceived naturally (NC) or after fertility treatments (FT) and determined factors predicting prenatal moderate-to-vigorous intensity physical activity (MVPA). The study was conducted in Trois-Rivières (Canada) between October 2015 and July 2018. MVPA and anxiety levels were assessed at each trimester of pregnancy (TR1, TR2 and TR3) using an accelerometer and the State-Trait Anxiety Inventory, respectively. Sociodemographic and reproductive history data were self-reported or collected from medical files. Repeated measures analysis of variance and regression analyses were conducted. Ninety-six women were included in the analyses (58 NC and 38 FT). MVPA levels and daily step counts decreased significantly throughout pregnancy (time effect: F = 28.68, p < 0.0001 and F = 39.18, p < 0.0001, respectively), but NC and FT women presented similar MVPA and daily step counts (no group effect). The decline in PA practice throughout pregnancy was similar in both groups (no interaction effect). At TR1, State (β = -0.272, p = 0.012) and Trait (β = -0.349, p = 0.001) anxiety and past PA (β = 0.483, p < 0.0001) were correlated with MVPA. Past MVPA was also correlated with MVPA at TR2 (β = 0.595, p < 0.0001) and TR3 (β = 0.654, p < 0.0001). Past PA was the strongest predictors of MVPA levels at TR1, TR2, and TR3, predicting 17% (p = 0.0002), 34% (p < 0.0001) and 42% (p < 0.0001), respectively. Overall, our findings suggest that MVPA practice throughout pregnancy is built on past PA practice. Therefore, to be effective at promoting PA throughout pregnancy, obstetric health care providers and fitness professionals should reinforce the importance of being active as early as possible during pregnancy.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".