The Predictive Spatial-Temporal Modeling for the Risk of Fetal Alcohol Syndrome (FAS) in Newborns Exposed to Alcohol During Pregnancy

• Activity Number: 69 - Modern Statistical Methods for Multi-Scale and Time Series Data
• Type: Contributed
• Date/Time: Sunday, July 30, 2017 : 4:00 PM to 5:50 PM
• Sponsor: International Indian Statistical Association
• Author(s): Bu Hyoung Lee* and Alexandra D. Carides and Helen Anni
• Companies: Loyola University Maryland and Temple University and Temple University
• Keywords: fetal alcohol syndrome ; alcohol ; spatial-temporal modeling ; spatial-temporal heatmap

Abstract

In this research, we develop hierarchical spatial-temporal models to explain and predict the risk of fetal alcohol syndrome (FAS) in newborns exposed to alcohol during pregnancy. FAS is known to be the most preventable cause of infant mental retardation, but more than 20 percent of pregnant women drink alcohol and the prevalence of FAS as high as 2.0 cases per 1000 births in the United States. First, we graphically and numerically analyze two annual datasets in Pennsylvania from 1996 to 2015-the annual surveys of the behavior risk factor surveillance system (BRFSS) conducted by the Centers for Disease Control and Prevention (CDC) and the hospital reports (HR) managed by the Pennsylvania Department of Health. Next, we propose hierarchical spatial-temporal models for the datasets and compare their model efficiency. Finally, we discover the spatial-temporal distribution of FAS newborns and explain the influence of factors such as poor prenatal care and nutrition, multiple pregnancies, and low socioeconomic status to FAS. Therefore, we enhance our understanding of the incidence, prevalence and etiology of FAS and uncover risk and protective factors associated with them.