Greater energy demand of exercise during pregnancy does not impact mechanical efficiency
Bibliographic record
Abstract
Pregnant women are recommended to engage in 150 min of moderate-intensity physical activity per week to reduce pregnancy complications. Many women struggle to remain physically active throughout pregnancy, and there is no consensus about whether women adopt a less efficient movement pattern as they progress through pregnancy and experience gestational weight gain. This study assessed the change in energy expenditure and mechanical efficiency in pregnant women (PREG; n = 10) when performing a walking treadmill task in early, mid, and late pregnancy and also compared with an age- and body mass index-matched, nonpregnant (CON; n = 10) group. On average, the PREG group gained within the Institute of Medicine’s gestational weight gain guidelines (11.6 ± 3.6 kg) and were all inactive (measured using accelerometry), except for 1 participant, by the third trimester, as per the 2019 Canadian physical activity guidelines for pregnant women. Energy expended to complete the walking task increased throughout pregnancy and was higher than the controls (111.5 ± 24.6 kcal) in mid and late pregnancy (139.0 ± 22.2 kcal, p = 0.02, and 147.3 ± 24.6 kcal, p = 0.005, respectively), but not early pregnancy (129.9 ± 18.9 kcal, p = 0.08). Walking mechanical efficiency was similar within pregnant women at each time point and compared to nonpregnant controls. Our findings add to the growing body of evidence demonstrating that pregnant women can safely perform physical activity by showing that walking mechanical efficiency is unchanged at low to moderate intensities. Novelty Energy demand during exercise increases proportionally to weight gain across pregnancy trimesters. However, mechanical efficiency remains unchanged during low- to moderate-intensity walking.
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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) | 0.002 | 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".