Association of pre-pregnancy BMI and gestational weight gain with fat mass distribution and accretion during pregnancy and early postpartum: a prospective study of Albertan women
Bibliographic record
Abstract
OBJECTIVES: To examine the patterns of fat mass gain in pregnancy and fat loss in the early postpartum period relative to women's pre-pregnancy body mass index (BMI) and by adherence to Institute of Medicine's gestational weight gain (GWG) recommendations. DESIGN: Prospective cohort study with three to four study visits. SETTING: This study is a part of the prospective longitudinal birth cohort, 'The Alberta Pregnancy Outcomes and Nutrition Study' (APrON) that recruited pregnant women from the cities of Edmonton and Calgary in Alberta. PARTICIPANTS: 1820 pregnant women were recruited and followed through their pregnancy and at 3 months postpartum. OUTCOME MEASURES: Body weight and skinfold thicknesses were measured during pregnancy and early postpartum in women. Body density was calculated from sum of skinfold thickness (biceps, triceps, subscapula and suprailiac), and total fat mass accretion during pregnancy was calculated using Van Raaij's equations and at postpartum using Siri's equation. Differences in total fat mass gain, fat mass loss and fat retention according to pre-pregnancy BMI categories and GWG categories were tested using two-way analysis of variance and post hoc comparisons. RESULTS: Most women (64%) had a normal pre-pregnancy BMI, and overall 49% women exceeded the GWG recommendations. Obese women gained significantly less total fat mass, had lower fat mass loss and had lower postpartum fat retention than normal-weight women (p<0.05). Women with excessive GWG gained higher total fat mass and had higher postpartum fat mass retention (p<0.03) than women who met the GWG recommendations. Total GWG was positively correlated with total fat gain (r=0.61, p<0.01) and total fat retention (r=0.31, p<0.05). CONCLUSION: Excessive GWG is the significant risk factor for higher fat mass accretion during pregnancy and higher postpartum fat retention, irrespective of pre-pregnancy BMI.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".