Maternal Anxiety and Breastfeeding
Bibliographic record
Abstract
BACKGROUND: Maternal anxiety and depression may impair maternal intention, motivation, and self-efficacy in multiple domains associated with child health including breastfeeding. OBJECTIVE: We tested the hypothesis that mothers who experience substantial anxiety during pregnancy or the postpartum period are at increased risk for reduced initiation, exclusivity, and continuation of breastfeeding. METHODS: We obtained data on 255 Canadian pregnant women from the Maternal Adversity, Vulnerability and Neurodevelopment (MAVAN) study recruited between June 2004 and February 2009. We utilized data collected from 18 to 23 weeks gestation through 12 months postpartum. Multivariate logistic regression was used to assess whether scores on the Hamilton Anxiety Scale (HAM-A) and State-Trait Anxiety Inventory (STAI) were associated with initiation, exclusivity, and continuation of breastfeeding. RESULTS: Prenatal anxiety was not associated with breastfeeding outcomes. In adjusted models, a single point increase in HAM-A scores at 3 months postpartum was associated with an 11% reduction in the odds of exclusive breastfeeding at 6 months (adjusted odds ratio [aOR] = 0.89; 95% CI, 0.80-0.99). A single point increase in STAI State and STAI Trait scores at 3 months postpartum was associated with a 4% (aOR = 0.96; 95% CI, 0.92-0.99) and 7% (aOR = 0.93; 95% CI, 0.86-1.00) reduction, respectively, in the odds of any breastfeeding at 12 months. CONCLUSION: Our findings suggest a relationship between maternal anxiety and reduced exclusivity and continuation of breastfeeding. Maternal anxiety should be actively monitored and managed appropriately in the postpartum period to support optimal breastfeeding practices.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".