Patterns and trajectories of gestational weight gain: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: Gestational weight gain in excess of or below Health Canada's guidelines is known to increase the risk of adverse outcomes for both the woman and her baby. This study describes patterns and trajectories of total and rate of gestational weight gain in a large prospective cohort of pregnant women and adolescents in the Alberta Pregnancy Outcomes and Nutrition study. METHODS: We collected weight and height data for 1541 pregnant adolescents and women (mean age 31 years, < 27 weeks' gestation) recruited through advertisements and physicians' offices in Calgary and Edmonton between May 2009 and November 2012. Data were collected once during each trimester following enrolment and once at about 3 months post partum. The participants were categorized according to their prepregnancy body mass index (BMI) as underweight, of normal weight, overweight or obese. We calculated distributions of total and weekly rates of weight gain and determined trajectories of weight gain for each prepregnancy BMI category. RESULTS: Of the 1541 participants, 761 (49.4%) exceeded Health Canada's guidelines for total gestational weight gain, and 272 (17.6%) gained less weight than recommended. A total of 63 (19.2%) and 38 (23.6%) participants categorized as overweight or obese, respectively, exceeded the recommended upper limit by 5 to less than 10 kg, and 53 (16.2%) and 27 (16.8%), respectively, exceeded the upper limit by at least 10 kg. Ninety-five participants (30.3%) in the overweight group and 59 (39.6%) of those in the obese group gained weight at more than double the recommended rate between the second and third trimesters. The median weight gain for participants in the normal, overweight and obese categories had exceeded recommended upper limits by about 30, 20 and 18 weeks' gestation, respectively. INTERPRETATION: Adherence to Health Canada's guidelines for gestational weight gain was low. Excess gestational weight gain was most marked among those with a prepregnancy BMI in the overweight or obese category. The findings suggest that weight management in pregnancy is challenging and complex. Messages and supports that are tailored for women in different prepregnancy BMI categories may help to improve guideline-concordant gestational weight gain.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".