In addition to implementing the National Children’s Study in Orleans Parish, the Tulane University Study Center is also involved in formative research projects that will inform different aspects of the Study as it progresses.
Investigation and Application of an Environmental Exposure Index for the National Children’s Study, Improved Human Exposure Assessment Using Hierarchical Bayesian Modeling
The aim of this research is to demonstrate how existing statistical modeling techniques can be applied to combine National Children’s Study data with other existing environmental data to develop enhanced personal exposure estimates for Study participants. This project is a collaborative effort between the Tulane University, Mt. Sinai, and Duplin County Study Centers and Battelle Memorial Institute. The proposed modeling techniques will be applied to air pollution and possible other environmental data in two Study locations: Queens County, NY, and Duplin County, NC.
Nationwide environmental monitoring data are routinely collected on chemical concentrations of agents in air, water, and other media that may be used and/or modeled to enhance exposure assessments. To supplement the environmental data collected by the National Children’s Study, this project will examine the publicly available environmental monitoring data that could be used to support and enhance exposure assessments of Study participants. The concept for this proposed project is to use data from these other sources in combination with Study data to more accurately assess exposures of Study participants. Hierarchical Bayesian modeling techniques will be employed to combine data and interpolate environmental data concentrations that cover the personal environment of Study participants. Alternative approaches will also model the environmental data and develop an Exposure Index. The proposed methods will be compared to the modeling methods used by Mt. Sinai researchers with respect to feasibility, data requirements, and modeling results. The goal is to identify the benefits and limitations of each of the available modeling methods, as well as to identify effectiveness of modeling techniques given variable data parameters (e.g., urban vs. rural, dense vs. sparse monitoring inputs).
Real-Time Analytics in the National Children’s Study
The objective of this project is to develop the capacity to analyze biospecimens and environmental samples in a clinical research laboratory as they are collected; develop and implement methods to improve the real time flow of data with ongoing quality assessments; and examine prototype business models to gain cost efficiency to reduce the per sample cost of analyses. Specifically, the goals are to: 1) enhance capacity for the real time analyses of biospecimens and environmental samples collected during the National Children’s Study; and 2) explore methods to increase efficiency and decrease costs associated with these analyses. The ability to analyze samples and provide results to researchers and participants shortly after sample collection will enhance the Study’s ability to produce and report findings; provide information on environmental agents of concern to the public and policy makers; and serve as an incentive to recruit and retain participants. It is also possible that real time analyses in the same laboratory may decrease participant burden by facilitating multiple analyses on the same sample or requiring less volume of the sample to be collected.
The approach of this project is to build upon the existing clinical research laboratory of the Tulane/LSU Clinical and Translational Research Center to carry out clinical analysis of biospecimens and environmental samples collected for the Study in a cost effective manner. Three types of samples and analyses are needed for the Study: 1) clinical parameters such as stress hormones, nutrients, and other physiological parameters; 2) environmental contaminants in biological fluids (e.g., bisphenol A, phthalates, or metals in blood or urine); and 3) environmental agents in environmental media (air, water, soil dusts). Few laboratories have the capacity to conduct this spectrum of analyses. The development of laboratory capacity to support the Study protocol will develop the capacity for real time analyses of samples, lower long-term cost of laboratory analysis, and minimize participant burden.
Self-Reported Stress and Cortisol Measurement
The overall goal of this multi-center, collaborative research project is the evaluation of maternal stress measurement for use in the National Children’s Study. Maternal stress and stress-related biomarkers (particularly cortisol) over pregnancy represent an integral part of several major Study hypotheses and priority outcomes, including pregnancy and birth outcomes, child body composition, metabolic function and obesity, pulmonary function and asthma, and neurodevelopment. A wide range of approaches and protocols are available to assess maternal stress and stress biology in pregnancy. This collaborative project seeks to develop a common, core protocol to determine the most reliable, acceptable, and cost-efficient approaches for the assessment of maternal stress and stress-related biomarkers. Additionally, five inter-related projects will address specific Study questions:
- Development of an optimized measure of chronic stress in pregnancy data-reduction project to create an optimized measure of psychosocial stress during pregnancy validated against biological markers of maternal stress (lead: Greater Chicago Study location).
- Evaluating psychosocial stressors in pregnant women (lead: University of Texas Health Science Study Center).
- Selection and validation of self-reported and biological measures of maternal stress using ecological momentary assessment (EMA) methodology (lead: Southern and Central California Study Center, Orange County Location).
- Biological moderators of cortisol activity (lead: Southern and Central California Study Center, Orange County Location).
- Validation of cortisol in hair samples for quantification of long-term cortisol exposure in pregnant and non-pregnant women (lead: Pacific Northwest Center).
Organizations collaborating on this project are: Brown University; Children’s Hospital of Philadelphia; Greater Chicago Study Center; Tulane University School of Public Health and Tropical Medicine; University of Irvine, California; University of Minnesota; University of Pittsburgh; University of Texas, San Antonio; and University of Washington.
Collaborative Improvement and Innovation Network for the Two-Tiered Recruitment Strategy (High Intensity/Low Intensity) Model
The overall goal of this formative research project is to optimize the implementation and performance of the Two-Tiered Recruitment Strategy (High Intensity/Low Intensity) Model through a Hi/Lo Collaborative Improvement-Innovation Network (COIN). The specific aims of the Hi/Lo COIN are to 1) optimize the implementation and performance of the Hi/Lo Model for recruitment using structured, planned testing of alternative approaches; 2) accelerate the pace of collaborative learning and innovation by effectively sharing knowledge and resources through a culture of trust and innovation and using a well-coordinated platform for communication and information sharing; 3) determine which implementation strategies are most important for success and which issues must be addressed to spread and scale the Two-Tiered Recruitment Strategy (High Intensity/Low Intensity) Model to other sites. The Study Centers will partner to systematically evaluate the collaborative efforts of the Hi/Lo sites in implementing the alternate recruitment strategy.
The Los Angeles-Ventura Study location is the lead for this project. Collaborating organizations include: Alleghenies Consortium Study Center, Colorado Study Center, Emory Battelle Morehouse Chattanooga Study Center, Greater Chicago Study Center, Johns Hopkins University Study Center, Tulane University Study Center, University of Minnesota Study Center, University of Utah Study Center, Vanderbilt University Study Center.