Breastfeeding and long‐term maternal metabolic health in the <scp>HUNT</scp> Study: a longitudinal population‐based cohort study
Bibliographic record
Abstract
OBJECTIVE: Breastfeeding (BF) has been reported to improve long-term maternal metabolic health in observational studies, but not in the randomised controlled PROBIT study. Research also suggests that maternal pre-pregnant metabolic health may affect BF. We aimed to disentangle effects of BF on long-term maternal metabolic health from effects of pre-pregnant metabolic health on BF duration and long-term metabolic health. DESIGN: Longitudinal population-based cohort study. SETTING: Nord-Trøndelag county, Norway. POPULATION: Women with a first live-born baby (1987-2008) participating in the Nord-Trøndelag Health Study (HUNT). METHODS: Odds ratios (ORs) for short BF duration (<3 months) by pre-pregnant body mass index (BMI), waist circumference (WCF), blood pressures (BPs), and heart rate (HR) were adjusted for age and smoking using logistic regression. Mixed linear models were used to estimate effects of BF duration (<3, 3-6, >6 months) on mean values of metabolic health parameters from baseline to follow-up. MAIN OUTCOME MEASURES: Mean change in BMI, WCF, BPs, HR, serum-glucose, and serum-lipids from baseline to follow-up by BF duration categories. RESULTS: We analysed 1403 women with a median follow-up of 12 years (interquartile range 11-22). Pre-pregnant WCF and HR correlated inversely with BF duration. Pre-pregnant BMI had a u-shaped correlation-pattern with BF duration. We observed similar between-group differences in metabolic health parameters at baseline and at follow-up, which implies that mean change in metabolic health parameters was similar across BF groups. Those women who started out with the best health had the longest BF duration and ended up with the best health, and those women who started out with the poorest health had shortest BF duration and ended up with the poorest health. CONCLUSIONS: Our results do not support a causal relationship between long BF duration and improved metabolic health. It is more likely that pre-pregnant metabolic health affects both BF duration and long-term metabolic health. Reverse causality can explain previously observed improved long-term metabolic health after BF. TWEETABLE ABSTRACT: Breastfeeding seems not to affect long-term maternal metabolic health, but good pre-pregnant metabolic health does.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".