A dose–response analysis of the effects of prenatal alcohol exposure on cognitive development
Bibliographic record
Abstract
BACKGROUND: Most studies of the effects of prenatal alcohol exposure (PAE) on cognitive function have assumed that the dose-response curve is linear. However, data from a few animal and human studies suggest that there may be an inflection point in the dose-response curve above which PAE effects are markedly stronger and that there may be differences associated with pattern of exposure, assessed in terms of alcohol dose per drinking occasion and drinking frequency. METHODS: We performed second-order confirmatory factor analysis on data obtained at school age, adolescence, and early adulthood from 2227 participants in six US longitudinal cohorts to derive a composite measure of cognitive function. Regression models were constructed to examine effects of PAE on cognitive function, adjusted for propensity scores. Analyses based on a single predictor (absolute alcohol (AA)/day) were compared with analyses based on two predictors (dose/occasion and drinking frequency), using (1) linear models and (2) nonparametric general additive models (GAM) that allow for both linear and nonlinear effects. RESULTS: The single-predictor GAM model showed virtually no nonlinearity in the effect of AA/day on cognitive function. However, the two-predictor GAM model revealed differential effects of maternal drinking pattern. Among offspring of infrequent drinkers, PAE effects on cognitive function were markedly stronger in those whose mothers drank more than ~3 drinks/occasion, and the effect of dose/occasion was strongest among the very frequent drinkers. Frequency of drinking did not appear to alter the PAE effect on cognitive function among participants born to mothers who limited their drinking to ~1 drink/occasion or less. CONCLUSIONS: These findings suggest that linear models based on total AA/day are appropriate for assessing whether PAE affects a given cognitive outcome. However, examination of alcohol dose/occasion and drinking frequency is needed to fully characterize the impact of different levels of alcohol intake on cognitive impairment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".