Thursday, November 21, 2024
11/21/2024
Abstract In the last three decades, extensive research has been conducted on the effects of prenatal alcohol intake on birth outcomes, fetal alcohol spectrum disorders, and children’s developmental delays. However, there is limited research on highly prevalent comorbidities that exist among pregnant women who consume alcohol during pregnancy, and how these maternal comorbidities in conjunction with prenatal alcohol consumption affect birth outcomes. Given the high national rates of obesity and subsequent diabetes, pregnancy-induced hypertension, and related preeclampsia and toxemia along with persistently high rates of preconceptual and prenatal alcohol consumption among US women, this gap in our science is significant. The proposed study will address this gap using an innovative approach that yields risk profiles that may be easily translated into clinical screening tools and provide the underpinnings of tailored interventions for the target population. The objectives of this study are to: (1a) estimate the extent of comorbidities among pregnant women with prenatal alcohol exposure; (1b) build maternal morbidity risk profiles based on social and behavioral determinants of health among women with prenatal alcohol intake using machine learning (ML) methods; (2a) examine the effects of comorbidities on adverse birth outcomes among alcohol-exposed pregnancies; and 2(b) build risk profiles for adverse birth outcomes using ML methods. We will use data from the Prenatal Alcohol and SIDS and Stillbirth Network (PASS) (2007-2015) and the Pregnancy Risk Assessment Monitoring System (2000-2021). Logistic regression will be used to compute odds ratios and 95% confidence intervals in examining the direction and magnitude of the association between comorbidities and alcohol exposure during pregnancy. Further, we will examine the effects of comorbidities on adverse birth outcomes among alcohol- exposed pregnancies using traditional statistical methods. ML methods such as classification trees will be used to construct risk profiles for maternal morbidity and adverse birth outcomes in identifying high-risk groups based on exposure to prenatal alcohol intake. This study will provide vital information on comorbidities among women who consume alcohol during pregnancy. The proposed study presents a model of study that combines both maternal and infant health in the context of maternal-fetal exposure to alcohol using innovative methods of data analysis that will yield previously unidentified risk profiles. Given the need for careful allocation of scarce healthcare resources for prevention and treatment programs, the identification of these risk profiles is both innovative and critical.
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