Project Summary The mission of Mount Sinai's P30 Center on Health and Environment Across the LifeSpan (HEALS) is to accelerate team science–based research utilizing life course–informed models of health. The Biostatistics and Data Science Facility Core (BDSFC) plays a key role in that mission by modeling complex exposure and phenotype data generated by Center Members across a spectrum of study types (basic, clinical, epidemiologic), exposures and health outcomes. Services include study design, covariate selection, data analysis as well as developing methods when needed to address our Center's research themes (mixtures/ exposomics, clinical environmental research, and environmental justice). Environmental conditions are not distributed equally and the risk of higher toxic exposures is not random. Higher rates of poor air quality, poor water quality, poor nutrition and the probability of exposure to toxic chemicals tracks along racial and socioeconomic gradients. By embracing a life course approach, our Center promotes research that addresses both the early life and later life environments that determine developmental health trajectories. We also emphasize the complexity of environmental health which crosses space (geospatial variability) and time (longitudinal effects, life stage effects) while bridging public health (prevention of disease) with medicine (diagnosis and treatment variability). Our approach is based upon the fundamental principle that “all diseases have an environmental basis.” While we offer standard data analytic services (e.g., linear models, longitudinal mixed effects models, power calculations, study analysis planning) the statistical methods and study designs needed for analyzing the complex, high-dimensional data that arise in much of our Center's work are still relatively new and require knowledge of advanced statistical techniques and the ability to curate and interpret complex biologic data – expertise maintained by the faculty of the BDSFC. Core faculty and researchers engage in research motivated by questions and methodological challenges that arise from center collaborations and innovations by our Center Cores. Core faculty and staff provide statistical and data science training for postdoctoral fellows working on environmental health sciences (EHS) related projects. Providing such services via a core facility allows the P30 Center to build and maintain specialized resources (e.g., expertise in measuring and advanced statistical, data science and epidemiological methods related to evaluation of environmental mixtures). Thus, to support the overall goals of the P30 Center, the BDSFC proposes the following specific aims: (1) to ensure that Center projects are grounded in sound biostatistical/data science principles and use state-of-the-art methods for design and analysis of EHS data; (2) to conduct mission-critical biostatistical/data science methods research for further quality assurance of all research and data analysis...