Increased Breastfeeding Rates in Black Women After a Treatment Intervention
Bibliographic record
Abstract
There has been a considerable increase in rates of breastfeeding in the United States. Despite these trends, black women continue to fall below medical recommendations. Impoverished and poorly educated women also have a comparatively lower rate of breastfeeding. Provider encouragement and supportive interventions increase breastfeeding initiation among women of all backgrounds. The data presented come from a three-site randomized controlled bilingual depression treatment trial from 2005 to 2011 that examined the comparative effectiveness of interpersonal psychotherapy and a parenting education program. Breastfeeding education and support were provided for the majority of participants in each intervention. Breastfeeding status was queried at postpartum week 4. We found higher rates of breastfeeding in black women compared with those reported in national surveys. The black breastfeeding rate did not significantly differ from that of white or Hispanic women. American-born black women were just as likely to breastfeed as American-born white women, both at significantly greater rates than American-born Hispanic women. We also found no differences in breastfeeding rate in poorly educated and impoverished women. These data must be seen against the backdrop of a significant intervention to treat depression. Because breastfeeding interventions have been shown to increase breastfeeding rates, the support provided in our study likely increased rates in groups that lag behind.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".