Prevalence of Breastfeeding in the United States: The 2001 National Immunization Survey
Bibliographic record
Abstract
OBJECTIVE: To address key gaps in the annual monitoring of breastfeeding prevalence in the United States, 3 breastfeeding questions concerning the initiation, duration, and exclusivity of breastfeeding were added to the rotating modules of the National Immunization Survey (NIS) beginning in the third quarter of 2001. The present study examines the current prevalence of breastfeeding in the United States using NIS data from this initial quarter. METHODS: The NIS is a random-digit-dialing survey of households with children aged 19 to 35 months, followed by a mail survey of the eligible children's vaccination providers to validate the child's vaccination information. In the third quarter of 2001, a randomly selected subset of households interviewed in the NIS (N = 896) were asked questions about breastfeeding. RESULTS: Almost two thirds (65.1%) of children had ever been breastfed. At 6 and 12 months, 27.0% and 12.3%, respectively, were receiving some breast milk. Non-Hispanic blacks had the lowest rates of breastfeeding initiation and continuation. Exclusive breastfeeding rates were low in the United States with only 7.9% at 6 months. CONCLUSIONS: Although breastfeeding initiation is near the national goal of 75%, breastfeeding continuation lags behind the national goals of 50% and 25% at 6 and 12 months, respectively. Strenuous public health efforts are needed to improve breastfeeding practices among blacks.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".