Breastfeeding Initiation Trends by Special Supplemental Nutrition Program for Women, Infants, and Children Participation and Race/Ethnicity Among Medicaid Births
Bibliographic record
Abstract
OBJECTIVE: Describe long-term breastfeeding initiation trends by prenatal Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) participation and race/ethnicity. DESIGN: Cross-sectional study of birth certificate data from 2009 to 2017 in 24 states that adopted the 2003 birth certificate revision by 2009. PARTICIPANTS: Term births with hospital costs covered by Medicaid (N = 6,402,704). MAIN OUTCOME MEASURES: Breastfeeding initiation. ANALYSIS: The descriptive characteristics of WIC participants and WIC-eligible nonparticipants were compared by year and race/ethnicity using the chi-square test of independence or t tests. Adjusted breastfeeding initiation prevalence was estimated using linear regression models with county fixed effects, controlling for sociodemographic and obstetric/health factors. Trends were compared by WIC status overall and within racial/ethnic groups. Differences and P values were assessed using interaction terms between WIC and year. RESULTS: Breastfeeding initiation increased for WIC participants and nonparticipants. Special Supplemental Nutrition Program for Women, Infants, and Children participants had lower adjusted breastfeeding initiation (2009: 69.0%; 2017: 78.5%) than nonparticipants (2009: 70.8%; 2017: 80.1%) (P < 0.001 per year). Breastfeeding initiation increased more rapidly in WIC participants than in nonparticipants for non-Hispanic Asian/Pacific Islander (21.4% and 8.6%, respectively; P < 0.001) and American Indian/Alaskan Native (13.6% and 8.1%, respectively; P = 0.02)-narrowing the gap between WIC participants and nonparticipants over time. CONCLUSIONS AND IMPLICATIONS: Annual birth certificate data provide detailed information for monitoring trends and disparities in breastfeeding initiation by prenatal WIC status. These findings can inform WIC and maternal child health program efforts to improve breastfeeding promotion for populations with low-income and racial/ethnic groups.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".