Gestational Weight Gain is associated with Postpartum Weight Retention and Infant Anthropometrics
Bibliographic record
Abstract
Optimal gestational weight gain is essential for healthy pregnancy outcomes. The study objective is to describe the association between gestational weight gain and early postpartum weight retention, and infant anthropometrics at birth and 3 months. Pregnant women (n=600) were followed up 2–3 times during pregnancy and at 3 months postpartum. Data on maternal weight at pre‐pregnancy, during pregnancy and postpartum were collected. Women were categorized as, “Below”, “Met” or “Above” based on the 2010 Gestational Weight Gain Guidelines. Infant birthweight and weight and length at 3 months were available. Age and sex specific z‐scores were calculated for birthweight and infant anthropometrics at 3 months. Data were analysed using regression. Over 55% women gained above recommended guidelines. Overweight (OR = 5.5, p <0.001) and obese (OR = 6.5, p <0.001) women were more likely to gain excess weight when compared to normal weight women. In comparison to adequate gestational weight gain, excessive weight gain was associated with higher postpartum weight retention (ß = −3.03, p <0.001), birthweight z‐scores (ß = 0.34, p <0.01), infant weight for age z‐score (ß = 0.40, p <0.01), and infant BMI z‐score (ß = 0.55, p <0.05). Excessive gestational weight gain promotes obesity in mothers and higher weights in infants. Interventions that optimize weight gain may significantly affect the long‐term health of women and children. Grant Funding Source : Alberta Innovates ‐ Health Solutions
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".