The Division’s research often involves targeted population subgroups including couples of reproductive age of which some may be planning pregnancies, women with low and high-risk pregnancies, or children and adolescents with risky behaviors along. Sampling frameworks utilized by the Division typically include population-based strategies (e.g., registries, marketing databases) and clinically based sampling (e.g., billing and clinic records, surgical schedules). To the extent feasible, the referent population is delineated for all sampling frameworks including those implemented within clinical facilities. The Division’s research is often conducted with nongovernmental investigators from either schools of medicine and biomedical sciences or public health via research and development contracts. All Division research is highly collaborative and trans-disciplinary reflecting the complexity of our research questions, novel study protocols and our passion for answering critical data gaps with the ultimate goal of promoting the health and well-being of populations. Of note is the dual publication track record for much of the Division’s research. For example, biobehavioral and epidemiological investigators will publish the results in their respective journals, while the biostatistical investigators will use this work to motivate original methods research and to publish methods papers in statistical journals. In addition, Division investigators publish their research in subject matter specialty and population health journals. The Division’s research includes both observational and experimental study designs, with most research being prospective in nature and with longitudinal data capture including the collection of biospecimens and in some studies, imaging data (e.g., digital video recording, pregnancy ultrasounds). Of note is the hierarchical data structure underlying much of our work either from the use of triads/diads or genome wide analytic studies (GWAS) or multiscale data from study participants (e.g., day, cycle, woman and couple level data collection for fecundity and fertility research). The highly timed and conditional nature of human reproduction and development is well suited for statistical methods such as joint modeling. Examples of prospective cohort studies with longitudinal measurement and biospecimens and a hierarchical data structure include: the NICHD Fetal Growth Studies (FGS), Longitudinal Investigation of Fertility & Environment (LIFE Study), Next Generation Health Study (NEXT), and the Diabetes and Women’s Health Study. Examples of studies with high dimensional data requiring GWAS and EWAS techniques include: Endometriosis: Natural History, Diagnosis, and Outcomes (ENDO) and genetic determinants of birth defects. Examples of our randomized trials include: Cultivating Healthy Eating in Families of Youth with Type 1 Diabetes (CHEF Trial), Family Management of Diabetes (FMOD); The Teen Passenger Simulation Study; Effects of Asp...