PROJECT SUMMARY/ABSTRACT Significance: Autism spectrum disorder (ASD) is an increasingly prevalent neurodevelopmental condition in the United States, for which the etiology largely unknown. ASD is a spectrum, characterized by restrictive and repetitive behaviors, and difficulties and differences in communication and learning. More severe and profound forms of ASD require lifelong support. Early diagnosis of ASD is critical as it allows for the opportunity to develop strengths and build skills, increasing independence later in life. It is important to explore the possible causes of ASD that occur in the perinatal period to target potential cases for screening and intervention. Previous research has shown that common indicators of hormonal variability including thyroid dysfunction and metabolic conditions among pregnant people are associated with ASD in their children. Research on other prevalent exogenous and endogenous hormonal exposures and their association with ASD, is inconclusive. Specific Aims: The overarching goal of this proposal is to evaluate how variability in the perinatal hormone environment is associated with ASD. My specific aims are 1) to investigate if there is an increased risk of ASD in children of pregnant people who used hormonal contraception (HC) in the 3 months prior to conception or during pregnancy, compared to children of pregnant people who did not use HC in this timeframe, and if this risk increases with progestin-only contraceptives, 2) to investigate if there is an increased risk of ASD in children of pregnant people who reported diagnosis of endometriosis, polycystic ovary syndrome (PCOS), or uterine fibroids, compared to children of pregnant people who did not report diagnoses of these conditions, and 3) to investigate if, among a subgroup of pregnant people with reported subfertility, the risk of ASD in their children is altered by certain fertility treatments compared to those who did not receive fertility treatment. Approach: These aims will be assessed using data from The Study to Explore Early Development (SEED), a multi-site case control study of ASD in the United States. Logistic regression models will be used to estimate the odds of the exposure in cases compared to controls, for each aim. Inverse probability of exposure weights (IPEW) and inverse probability of observations weights (IPOW) will be calculated and implemented into logistic regression models to control for bias from confounding and missing data, respectively. Fellowship Information: The applicant is a PhD student in the Department of Epidemiology at the University of North Carolina at Chapel Hill (UNC), and a predoctoral trainee in the NICHD funded T32 training program in reproductive, perinatal, and pediatric epidemiology. The proposed training plan will provide the applicant with the necessary resources to build on her rigorous education at UNC, successfully complete her doctoral dissertation, and pursue the professional skills necessary to...