The complementary expertise and resources of Johns Hopkins University and RTI International are combined to become the Data Analysis Center (DAC) for the NIH Environmental Influences on Child Health Outcomes (ECHO) program. A DAC with expertise in data harmonization, epidemiology and biostatistics is essential for effective longitudinal and multi-level analyses to elucidate the influences of life course environmental and social exposures, and genetic susceptibility on pediatric health and adverse outcomes. The efficiency offered by capitalizing on extant pediatric studies is more readily accomplished with a DAC prepared to deal with the associated challenges. Our DAC uniquely offers deep experience in developing innovative methods for analyzing data combined from disparate cohorts. To help drive the next generation science in pediatric research, expertise in epidemiology, statistics, informatics, pediatric outcomes, environmental exposures, and genetics is synergized to realize these specific aims: (1) Provide statistical and epidemiological expertise in the design, analysis, and interpretation of studies relevant to the scientific goals of ECHO. In particular, use principles of reproducible science to address how environmental exposures, social context, and genetic predispositions influence the risk of respiratory, metabolic, neurodevelopmental, and pre-, peri-, and postnatal outcomes. The development and application of novel methodology to best analyze the complex ECHO data is central to this goal; (2) Harmonize, manage, and quality assure the data across the ECHO cohorts, including the provision of secured systems for data transfer, editing, merging, storing, and backup; (3) Develop procedures for standardized execution of protocols across cohorts and studies in collaboration with the coordinating center, steering committee, and cohorts; and (4) Promote the use of quality-assured ECHO data in scientific studies of pediatric outcomes, by: engaging the scientific community, providing an interactive system for visualization and data extraction, and tracking the progress of approved projects. The proposed data harmonization, and methods for bridging the cohorts will be key in making ECHO the premier resource for epidemiological studies of pediatric health.

Public Health Relevance

The ECHO program will create an extensive resource for elucidating the roles of environmental and genetic characteristics that affect child health. The JHU/RTI Data Analysis Center will advance ECHO research by providing state-of-the-art study designs and analyses, and by publicizing high quality, well-documented ECHO data to promote informative analyses by the scientific community at-large.

Agency
National Institute of Health (NIH)
Institute
Office of The Director, National Institutes of Health (OD)
Type
Resource-Related Research Projects--Cooperative Agreements (U24)
Project #
5U24OD023382-02
Application #
9355710
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Blaisdell, Carol J
Project Start
2016-09-21
Project End
2023-08-31
Budget Start
2017-09-01
Budget End
2018-08-31
Support Year
2
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Johns Hopkins University
Department
Public Health & Prev Medicine
Type
Schools of Public Health
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21205
Lau, Bryan; Lesko, Catherine (2018) Missingness in the Setting of Competing Risks: from missing values to missing potential outcomes. Curr Epidemiol Rep 5:153-159
Jacobson, Lisa P; Lau, Bryan; Catellier, Diane et al. (2018) An Environmental influences on Child Health Outcomes viewpoint of data analysis centers for collaborative study designs. Curr Opin Pediatr 30:269-275
Lesko, Catherine R; Jacobson, Lisa P; Althoff, Keri N et al. (2018) Collaborative, pooled and harmonized study designs for epidemiologic research: challenges and opportunities. Int J Epidemiol 47:654-668
Edwards, Jessie K; Lesko, Catherine R; Keil, Alexander P (2017) Invited Commentary: Causal Inference Across Space and Time-Quixotic Quest, Worthy Goal, or Both? Am J Epidemiol 186:143-145