Does “Sitting” Stand Alone? A Brief Report Evaluating the Effects of Prenatal Sedentary Time on Maternal and Newborn Anthropometric Outcomes
Bibliographic record
Abstract
BACKGROUND: Research on sedentary behavior and effects on maternal and newborn outcomes has been inconclusive. The objective of this report was to correlate sedentary time with maternal and fetal anthropometric measurements and compare the effect on sedentary time based on meeting prenatal activity guidelines. METHODS: Healthy pregnant women (N = 61) in their second trimester (24-28 wk gestation) provided 7-day accelerometry data. Outcomes, including neonatal weight, length, and body fat percentage, were collected 24 to 48 hours after delivery. Placenta weight was measured immediately after delivery. Gestational weight gain was calculated by subtracting self-reported prepregnancy weight from measured weight at 38 weeks gestation. Correlations between sedentary time and outcomes were tested with Spearman and Pearson coefficient of correlations in all women separately and in accordance with the 2019 Canadian prenatal exercise guidelines. RESULTS: No significant associations were found between sedentary time and the selected outcomes, even when compared by prenatal exercise level. There was no difference in total time spent sedentary between active (576.7 [52.8] min) and inactive women (599.3 [51.6] min). CONCLUSIONS: Meeting exercise recommendations during pregnancy does not significantly decrease total sedentary time. Future studies should aim to evaluate the health effects of both decreasing sedentary time and meeting prenatal exercise guidelines.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".