On the use of the outcome variable “small for gestational age” when gestational age is a potential mediator: a maternal asthma perspective
Bibliographic record
Abstract
BACKGROUND: The variable "small for gestational age," frequently defined as birth weight below the 10th percentile in a gestational age and sex-normalized population, is nowadays generally perceived as a more adequate measure than birth weight or low birth weight (birth weight < 2500 g) to capture fetal growth. However, the use of small for gestational age rather than birth weight or low birth weight as an outcome (dependent) variable may have important impacts on the interpretation of analyses aimed at estimating the causal effect of an exposure of interest on infants. We hypothesized potential differences in both types of effects estimated (direct or total) and in ability to control for confounding bias. METHODS: We first examined the use of outcome variables birth weight and small for gestational age to get insights on modeling practices within the field of maternal asthma. Using directed acyclic graph simulations where gestational age was a potential mediator, we then compared estimated exposure effects in regression models for birth weight, low birth weight, and small for gestational age. Graphs with and without confounding were considered. RESULTS: Our simulations showed that the variable small for gestational age captures the direct effect of exposure on birth weight, but not the indirect effect of exposure on birth weight through gestational age. Interestingly, exposure effect estimates from small for gestational age models were found unbiased whenever exposure effect estimates from birth weight models were affected by collider bias due to conditioning on gestational age in the models. CONCLUSIONS: The sole consideration of the outcome small for gestational age in a study may lead to suboptimal understanding and quantification of the underlying effect of an exposure on birth weight-related measures. Instead, our results suggest that both outcome variables (low) birth weight and small for gestational age should minimally be considered in studies investigating perinatal outcomes.
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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 | 0.015 | 0.286 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".