Racial/Ethnic Disparity in Association Between Fetal Alcohol Syndrome and Alcohol Intake During Pregnancy: Multisite Retrospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Alcohol consumption during pregnancy is associated with a range of adverse birth-related outcomes, including stillbirth, low birth weight, preterm birth, and fetal alcohol syndrome (FAS). With more than 10% of women consuming alcohol during pregnancy worldwide, it is increasingly important to understand how racial/ethnic variations affect FAS onset. However, whether race and ethnicity inform FAS risk assessment when daily ethanol intake is controlled for remains unknown. OBJECTIVE: This study aimed to assess racial/ethnic disparities in FAS risk associated with alcohol consumption during pregnancy. METHODS: We used data from a longitudinal cohort study (the Collaborative Initiative on Fetal Alcohol Spectrum Disorders) at 5 hospital sites around the United States of 595 women who consumed alcohol during pregnancy from 2007 to 2017. Questionnaires, in-person interviews, and reviews of medical, legal, and social service records were used to gather data on average alcoholic content (AAC) during pregnancy. Self-reports of maternal race (American Indian/Alaska Native [AI/AN], Asian, Native Hawaiian or other Pacific Islander, Black or African American, White, more than one race, and other) and ethnicity (Hispanic/Latino or not Hispanic/Latino), as well as FAS diagnoses based on standardized dysmorphological criteria, were used for analysis. Log-binomial regression was used to examine the risk of FAS associated with each 1-gram increase in ethanol consumption during pregnancy, stratified by race/ethnicity. RESULTS: A total of 3.4% (20/595) of women who reported consuming alcohol during pregnancy gave birth to a baby with FAS. Women who gave birth to a baby with FAS had a mean AAC of 32.06 (SD 9.09) grams, which was higher than that of women who did not give birth to a baby with FAS (mean 12.07, SD 15.87 grams). AI/AN mothers with FAS babies had the highest AAC (mean 42.62, SD 8.35 grams), followed by White (mean 30.13, SD 4.88 grams) and Black mothers (mean 27.05, SD 12.78 grams). White (prevalence ratio [PR] 1.10, 95% CI 1.03-1.19), Black (PR 1.13, 95% CI 1.04-1.23), and AI/AN (PR 1.10, 95% CI 1.00-1.21) mothers had 10% to 13% increased odds of giving birth to a baby with FAS given the same exposure to alcohol during pregnancy. Regardless of race, a 1-gram increase in AAC resulted in a 4% increase (PR 1.04, 95% CI 1.02-1.07) in the chance of giving birth to a baby with ≥2 facial anomalies (ie, short palpebral fissures, thin vermilion border of the upper lip, and smooth philtrum) and a 4% increase (PR 1.04, 95% CI 1.01-1.07) in the chance of deficient brain growth. CONCLUSIONS: The risk of delivering a baby with FAS was comparable among White, Black, and AI/AN women at similar levels of drinking during pregnancy. Regardless of race, a 1-gram increase in AAC resulted in increased odds of giving birth to a baby with facial anomalies or deficient brain growth.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".