Sustained Reduction of Subclinical Inflammation in the Years After Breastfeeding
Bibliographic record
Abstract
CONTEXT: Lactation is associated with lower future risk of cardiovascular disease (CVD) in women but the mechanism(s) underlying this relationship remain unclear. OBJECTIVE: We sought to characterize the relationship between duration of exclusive breastfeeding and CV risk factors over the first 5 years post partum. METHODS: In this prospective cohort study, 328 women underwent serial cardiometabolic characterization (anthropometry, blood pressure [BP], lipids, fasting glucose, adiponectin, C-reactive protein [CRP]) at 1 year, 3 years, and 5 years post partum. Outcomes were CV risk factors in 3 groups defined by duration of exclusive breastfeeding: less than 3 months (n = 107), 3 to 6 months (n = 101), and 6 months or more (n = 120). RESULTS: The prevalence of metabolic syndrome did not differ between the groups at 3 years but, by 5 years post partum, was higher in women who had exclusively breastfed for less than 3 months than in those who did so for 3 to 6 and 6 months or more, respectively (14.0% vs 6.9% vs 4.2%; P = .02). However, after adjustment for covariates (including body mass index [BMI]), there were no statistically significant differences between groups in BP, glucose, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, or adiponectin. Indeed, the only CV risk factor difference that persisted after covariate adjustment was that women who had exclusively breastfed for less than 3 months had higher CRP both at 3 years (P = .04) and 5 years (P = .01). Moreover, generalized estimating equation analyses with adjustment for covariates (including time-dependent BMI) showed that CRP remained higher over time in these women, as compared to their peers, from 1 year to 3 years to 5 years post partum (P = .03). CONCLUSION: Sustained reduction of subclinical inflammation may contribute to the cardioprotective effect of lactation 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 | 0.001 | 0.002 |
| 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 | 0.000 |
| 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".