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Your Environment. Your Health.

Wayne State University

Superfund Research Program

Data Management & Analysis Core

Project Leader: Mei Lu (Henry Ford Health System)
Grant Number: P42ES030991
Funding Period: 2022-2027
View this project in the NIH Research Portfolio Online Reporting Tools (RePORT)

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Project Summary (2022-2027)

Exposure to volatile organic compounds (VOCs) is an important determinant of maternal-offspring health, with implications for preterm birth and associated adverse health outcomes. VOCs contaminate shallow soils and groundwater of post-industrial cities at Superfund, residential, commercial, and industrial properties, leading to exposures via vapor intrusion. The Center for Leadership in Environmental Awareness and Research (CLEAR) is dedicated to understanding and mitigating this serious environmental health problem. The Data Management and Analysis Core (DMAC) provides unified and integrated data and biostatistics/informatics services, while promoting scientific synergy across the CLEAR projects and cores; they achieve these goals by interfacing with the CLEAR cores to advance the two environmental science and engineering research projects (Building Aboveground Strategies to Identify and Address Belowground Hot Spots for VOC Vapor Intrusion in Complex Urban Settings and Integrated IoT Sensing and Edge Computing Coupled with a Bayesian Network Model for Exposure Assessment and Targeted Remediation of Vapor Intrusion projects) and three biomedical research projects (Developmental VOC Exposure in Zebrafish: Toxic Mechanisms and Biomarkers, Impact of BTEX Chemical Exposure During Pregnancy to Maternal and Fetal Well-Being, and Epidemiological Study of Volatile Organic Compounds and Preterm Birth in Detroit projects).

The DMAC leverages over 25 years of experience serving as the Data Coordinating Center for multisite projects, including their flexible, centralized data management infrastructure that builds on standard operating procedures, their seamless collaboration with research scientists in designing cost- and time-efficient studies and having data collection based on “FAIR” guiding principles (Findable, Accessible, Interoperable, and Reusable), and their biostatistics and informatics expertise in analyzing complex data using cutting- edge analytical methods in public health research. DMAC ensures the success of CLEAR research projects by: 1) Customizing a web-accessible, centralized, and secured data management system to capture complex data to ensure data quality and timely data integration to foster data sharing and interoperability and 2) Catalyzing CLEAR growth by working with project and core leaders to develop new hypotheses about VOC exposures and adverse health effects based on integrated data analysis and by collaborating with the Research Experience and Training Coordination Core to train the next generation of environmental scientists in the principles of data collection and management.

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