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Published on: June 29, 2013
On the pitfalls of adjusting for gestational age at birth
Allen J Wilcox1, Clarice R Weinberg, Olga Basso
1Epidemiology Branch (MD A3-05), National Institute of Environmental Health Sciences, P.O. Box 12233, Durham, NC 27709, USA. wilcox@niehs.nih.gov
Insights
Adjusting for gestational age in preterm birth studies can create bias, potentially reversing findings. This highlights the need to reconsider its use in perinatal research for accurate causal inference.
Area of Science:
- Perinatal epidemiology
- Maternal-fetal medicine
- Biostatistics
Background:
- Preterm delivery is a major cause of infant morbidity and mortality.
- Underlying pathological factors causing preterm birth are not fully understood.
- These factors can confound the association between early delivery and neonatal outcomes.
Purpose of the Study:
- To investigate the impact of adjusting for gestational age in studies of preterm birth.
- To explore the potential for bias, including outcome reversal, due to gestational age adjustment.
- To clarify the role of gestational age as a collider in perinatal research.
Main Methods:
- Review of theoretical concepts of colliders in causal inference.
- Presentation of simulation studies to quantify bias from gestational age adjustment.
- Analysis of confounding in the association between risk factors and neonatal outcomes.
Main Results:
- Adjustment for gestational age can introduce significant bias when estimating direct effects.
- Under certain conditions, this bias can lead to a complete reversal of exposure-outcome associations.
- Gestational age is identified as a collider, complicating causal inference.
Conclusions:
- Adjusting for gestational age is generally not justified for causal inference in perinatal research.
- Failure to appreciate gestational age as a collider can lead to erroneous conclusions.
- Revising analytical strategies is crucial for accurate understanding of preterm birth impacts.
Abstract:
Preterm delivery is a powerful predictor of newborn morbidity and mortality. Such problems are due to not only immaturity but also the pathologic factors (such as infection) that cause early delivery. The understanding of these underlying pathologic factors is incomplete at best. To the extent that unmeasured pathologies triggering preterm delivery also directly harm the fetus, they will confound the association of early delivery with neonatal outcomes. This, in turn, complicates studies of newborn outcomes more generally. When investigators analyze the association of risk factors with neonatal outcomes, adjustment for gestational age as a mediating variable will lead to bias. In the language of directed acyclic graphs, gestational age is a collider. The theoretical basis for colliders has been well described, and gestational age has recently been acknowledged as a possible collider. However, the impact of this problem, as well as its implications for perinatal research, has not been fully appreciated. The authors discuss the evidence for confounding and present simulations to explore how much bias is produced by adjustments for gestational age when estimating direct effects. Under plausible conditions, frank reversal of exposure-outcome associations can occur. When the purpose is causal inference, there are few settings in which adjustment for gestational age can be justified.
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