Postpartum weight retention and the early evolution of cardiovascular risk over the first 5 years after pregnancy
Bibliographic record
Abstract
BACKGROUND: The cumulative effect of postpartum weight retention from each pregnancy in a woman's life may contribute to her risk of ultimately developing type 2 diabetes and cardiovascular disease. However, there is limited direct evidence supporting this hypothesis. Thus, we sought to characterize the impact of postpartum weight retention on the trajectories of cardiovascular risk factors over the first 5-years after pregnancy. METHODS: , 50.9% primiparous) underwent serial cardiometabolic characterization (anthropometry, blood pressure, lipids, oral glucose tolerance test, insulin sensitivity/resistance (Matsuda index, HOMA-IR), C-reactive protein (CRP), adiponectin) at 1-year, 3-years, and 5-years postpartum. Based on the magnitude of weight change between pre-pregnancy and 5-years postpartum, they were stratified into the following 3 groups: weight loss (n = 100), weight gain 0-6% (n = 110), and weight gain ≥ 6% (n = 120). RESULTS: At 1-year postpartum, cardiovascular risk factors did not differ between the groups. However, an adverse risk factor profile progressively emerged in the weight retention groups at 3- and 5-years. Indeed, after covariate adjustment, there was stepwise worsening (from the weight loss group to weight gain 0-6% to weight gain ≥ 6% group) of the following cardiovascular risk factors at 5-years: triglycerides (p = 0.001), HDL (p = 0.02), LDL (p = 0.01), apolipoprotein-B (p = 0.003), Matsuda index (p < 0.0001), HOMA-IR (p < 0.0001), fasting glucose (p = 0.07), and CRP (p = 0.01). Moreover, on logistic regression analyses, weight gain ≥ 6% emerged as an independent predictor of pre-diabetes/diabetes at 5-years (adjusted OR = 3.40, 95%CI: 1.63-7.09). CONCLUSION: Postpartum weight retention predicts trajectories of worsening cardiovascular risk factors and glucose intolerance over the first 5-years after delivery, consistent with its postulated contribution to future vascular disease in women.
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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 | 0.000 | 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 | 0.001 | 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".