Regional Variation in Rates of Low Birth Weight
Bibliographic record
Abstract
OBJECTIVE: Low birth weight (LBW; < 2500 g) is the result of complex and poorly understood interactions between the biological determinants of the mother and the fetus, the parent's socioeconomic status, and medical care. After controlling for these established risk factors, the extent of regional variation in LBW rates remains unknown. This study measures regional variation in LBW rates and identifies regions of neonatal health services with significantly high or low adjusted rates. METHODS: Linking the United States 1998 singleton birth cohort (N = 3.8 million) with county and health care characteristics, we conducted a small area analysis of LBW across 246 regions of neonatal health services. We measured observed rates and then used a multivariable, hierarchical model to estimate adjusted LBW rates by regions. We then stratified these rates by race for the 208 regions with adequate sample size. RESULTS: Observed LBW rates varied across regions from 3.8 to 10.6 per 100 live births (interquartile range: 5.0-6.8 [25th-75th percentile]; median: 5.9). After controlling for known maternal and area risk factors, 67 (27.0%) regions had rates significantly below and 98 (39.8%) regions had rates significantly higher than the national rate of 6.0 per 100 live births. Although black mothers were more likely to give birth to an LBW newborn, regional adjusted rates still varied > 3-fold within both black and nonblack subgroups. CONCLUSIONS: After controlling for known maternal and area risk factors, LBW rates markedly varied across US regions of neonatal health services for both black and nonblack mothers. Additional analyses of these regions may provide opportunities for regional accountability in pregnancy outcomes, LBW research, and targeted improvement interventions, especially in high-risk populations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".