Romitti, Paul A.

ABSTRACTBackgroundPrevious studies of maternal alcohol consumption and craniosynostosis have reported null or inverse associations. We updated a previous analysis of National Birth Defects Prevention Study (NBDPS) data to further examine associations between maternal alcohol consumption and craniosynostosis.MethodsNBDPS was a multi‐site, population‐based case–control study. Mothers of craniosynostosis cases and randomly selected liveborn controls delivered during 1997–2011 completed a telephone interview about pregnancy exposures. We examined associations for self‐reported periconceptional maternal alcohol consumption (during the month before conception through the third gestational month) and odds of craniosynostosis in offspring. We used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between any alcohol consumption and binge consumption and craniosynostosis, overall and by affected suture. Finally, we performed a probabilistic bias analysis using a range of assumptions about the sensitivity and specificity of self‐reported consumption by case/control status.ResultsWe analyzed interview data from 1435 mothers of craniosynostosis cases and 11,216 mothers of controls. Periconceptional alcohol consumption prevalence was similar among case (36.9%) and control (38.2%) mothers. We observed point estimates near or below 1.0 for alcohol consumption (any and binge) and all suture subtypes of craniosynostosis, with all CIs including the null. Our bias‐adjusted estimates for periconceptional alcohol consumption were higher than our conventional estimates but supported the null findings.ConclusionsWe observed primarily null associations between maternal periconceptional alcohol consumption and craniosynostosis. However, our findings do not diminish the prevailing clinical guidance in the United States that pregnant people should abstain from alcohol consumption.

Motivated by the paucity of high‐quality stillbirth surveillance data and the spatial analysis of such data, we describe the pattern of stillbirth events as a step toward increased understanding of risk factors which can better guide future measures to mitigate these events. A challenge in such an analysis is that some mothers experience stillbirth events from independent pregnancies within a defined study period. To account for these dependencies, we parameterize our model to include a maternal contextual effect and broaden the appeal of Bayesian Poisson point process modeling to quantify excess stillbirth risk while considering a form of a log‐Gaussian Cox process. In the presence of extra unobserved spatial variation in risk, we demonstrate a pragmatic methodologic strategy to model the risk surface in relation to covariates and that there is a variance‐bias trade‐off associated with the use of a maternal contextual effect. We applied our strategy to the spatial distribution of stillbirth in Iowa during the years 2005–2011 using data obtained from an active, statewide public health surveillance program. We identified areas of excess risk for further investigation based on model components that captured important features of the data.