Modeling the Impact of Prepregnancy BMI, Physical Activity, and Energy Intake on Gestational Weight Gain, Infant Birth Weight, and Postpartum Weight Retention
Bibliographic record
Abstract
BACKGROUND: A "fit pregnancy" requires balancing energy expenditure with energy intake (EI) to achieve appropriate gestational weight gains (GWG), healthy infant birth weights (IBW), and minimal postpartum weight retention (PPWR). Our objective was to develop an integrated conceptual framework to assess the contribution of prepregnancy weight (PP-BMI), EI, and physical activity (PA) as determinants of GWG, IBW, and PPWR. METHODS: Pregnant women (n = 59) were recruited from prenatal classes. Energy intake was estimated using 3 24-hr diet recalls and PA using a validated PA questionnaire and a pedometer. Telephone interviews at 6-weeks postpartum assessed self-reported GWG, IBW, and PPWR. Hierarchical multiple regression analyses were used to explore the potential predictors of GWG, IBW, and PPWR. RESULTS: Prepregnancy BMI was associated with GWG, and EI was associated with IBW; each model captured only 6%-18% of the variability. In contrast, PPWR was predicted by PP-BMI, GWG, and EI, which together explained 61% of its variability, whereas GWG alone explained 51% of the variability in PPWR. CONCLUSIONS: Modeling the relationship using hierarchical models suggests that PP-BMI, prepartum PA, and EI differentially impact GWG, IBW, and PPWR.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".