Cardiometabolic Implications of Postpartum Weight Changes in the First Year After Delivery
Bibliographic record
Abstract
OBJECTIVE: The cumulative effect of postpartum weight retention from each pregnancy in a woman's life may contribute to her ultimate risk of diabetes and vascular disease. However, there is little direct evidence supporting this hypothesis. In this context, we sought to evaluate the cardiometabolic implications of patterns of postpartum weight change and the time course thereof in the first year after pregnancy. RESEARCH DESIGN AND METHODS: Three hundred five women underwent cardiometabolic characterization at recruitment in pregnancy and at 3 and 12 months postpartum. Based on their respective weight changes between prepregnancy and 3 months postpartum (loss or gain) and between 3 and 12 months postpartum (loss or gain), participants were stratified into four groups: loss/loss, gain/loss, loss/gain, and gain/gain. RESULTS: Most women (81.0%) had higher weight at 3 months postpartum compared with prepregnancy. Between 3 and 12 months, most women (74.4%) lost weight. At 3 months, there were modest differences between the four groups in mean adjusted LDL cholesterol (P = 0.01) and apolipoprotein-B (apoB; P = 0.02) but no significant differences in adjusted blood pressure, fasting and 2-h glucose, HDL, triglycerides, homeostasis model assessment of insulin resistance (HOMA-IR), adiponectin, and C-reactive protein. By 12 months postpartum, however, clear gradients emerged, with mean adjusted diastolic blood pressure (P = 0.02), HOMA-IR (P = 0.0003), LDL (P = 0.001), and apoB (P < 0.0001) all progressively increasing from the loss/loss group to gain/loss to loss/gain to gain/gain. Similarly, at 12 months, mean adjusted adiponectin showed a stepwise decrease from loss/loss to gain/loss to loss/gain to gain/gain (P = 0.003). CONCLUSIONS: An adverse cardiometabolic profile emerges as early as 1 year postpartum in women who do not lose weight between 3 and 12 months after delivery.
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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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".