The National Children's Study: An Introduction and Historical Overview

Assessing preconception exposure to environmental chemicals and fecundity: Strategies, challenges, and research priorities

In 2022, approximately one out of six people globally experienced infertility at some point in their life. Environmental chemicals, particularly those with endocrine disrupting activity, may contribute to impaired fecundity and infertility. We review existing prospective cohort studies of environmental chemicals and fecundity, identify methodological challenges and biases, and outline future research priorities. Studies of preconception environmental chemical exposures and fecundity have occurred in US, Singapore, China and Denmark with recruitment as early as 1982-1986, as recent as 2015-2017 and sample sizes ranging from 99 to 936. Higher exposure to certain chemicals (e.g. heavy metals, perfluoroalkyl substances) was associated with longer time to pregnancy; yet the literature is scarce or nonexistent for many chemicals. Furthermore, prospective studies face challenges and potential biases related to recruiting participants prior to conception, measuring environmental chemicals during critical windows of exposure, and ascertaining when pregnancy occurred. Research priorities include expanding the scope of biomonitoring data collected during the preconception period, continuing to develop and validate analytic methods for self-sampled biospecimens in traditional and novel matrices, collecting data in male partners and investigating etiologic associations according to indicators of marginalization.

How do 3-year-olds do on the NIH Toolbox Cognitive Battery?

The NIH Toolbox includes a cognitive battery that provides an Early Childhood Composite score for children age 3-7. However, very few studies have evaluated feasibility when it is used in the youngest segment of this age range-3-year-olds. The current study evaluated performance on the four cognitive subtests composing the early childhood composite, two of which assess executive function, in a large sample of 3-year-olds enrolled in a Vanguard pilot of the National Children's Study. Results found that in a cohort of 609 3-year-olds (mean age = 39.6 months, SD = 1.6, 53% male, 64% White, 87% Non-Hispanic) who were administered four subtests included in the Early Childhood Composite, up to approximately 30% were unable to pass practice items on the Flanker, Dimensional Change Card Sort, and Picture Sequence Memory, whereas only approximately 3% were unable to pass practice items on the Picture Vocabulary Test. Furthermore, of those that did pass practice and achieve scores on the subtests, approximately 70% and 80% performed at or below chance level on the executive function tasks (Flanker and Dimensional Change Card Sort) and Picture Sequence Memory, respectively. Ultimately, the average 3-year-old has difficulty with three of the four NIH Toolbox tasks composing the Early Childhood Composite and may not yet have developed the requisite skills. These findings indicate that changes compatible with the developmental level of preschoolers are recommended to increase the feasibility and effectiveness of the NIH Toolbox in measuring individual cognition differences in 3-year-old children.

Meta-analysis under imbalance in measurement of confounders in cohort studies using only summary-level data

BACKGROUND

Cohort collaborations often require meta-analysis of exposure-outcome association estimates across cohorts as an alternative to pooling individual-level data that requires a laborious process of data harmonization on individual-level data. However, it is likely that important confounders are not all measured uniformly across the cohorts due to differences in study protocols. This imbalance in measurement of confounders leads to association estimates that are not comparable across cohorts and impedes the meta-analysis of results.

METHODS

In this article, we empirically show some asymptotic relations between fully adjusted and unadjusted exposure-outcome effect estimates, and provide theoretical justification for the same. We leverage these results to obtain fully adjusted estimates for the cohorts with no information on confounders by borrowing information from cohorts with complete measurement on confounders. We implement this novel method in CIMBAL (confounder imbalance), which additionally provides a meta-analyzed estimate that appropriately accounts for the dependence between estimates arising due to borrowing of information across cohorts. We perform extensive simulation experiments to study CIMBAL's statistical properties. We illustrate CIMBAL using National Children's Study (NCS) data to estimate association of maternal education and low birth weight in infants, adjusting for maternal age at delivery, race/ethnicity, marital status, and income.

RESULTS

Our simulation studies indicate that estimates of exposure-outcome association from CIMBAL are closer to the truth than those from commonly-used approaches for meta-analyzing cohorts with disparate confounder measurements. CIMBAL is not too sensitive to heterogeneity in underlying joint distributions of exposure, outcome and confounders but is very sensitive to heterogeneity of confounding bias across cohorts. Application of CIMBAL to NCS data for a proof-of-concept analysis further illustrates the utility and advantages of CIMBAL.

CONCLUSIONS

CIMBAL provides a practical approach for meta-analyzing cohorts with imbalance in measurement of confounders under a weak assumption that the cohorts are independently sampled from populations with the same confounding bias.

Microbiome First Approaches to Rescue Public Health and Reduce Human Suffering

The is a sequential article to an initial review suggesting that Microbiome First medical approaches to human health and wellness could both aid the fight against noncommunicable diseases and conditions (NCDs) and help to usher in sustainable healthcare. This current review article specifically focuses on public health programs and initiatives and what has been termed by medical journals as a catastrophic record of recent failures. Included in the review is a discussion of the four priority behavioral modifications (food choices, cessation of two drugs of abuse, and exercise) advocated by the World Health Organization as the way to stop the ongoing NCD epidemic. The lack of public health focus on the majority of cells and genes in the human superorganism, the microbiome, is highlighted as is the "regulatory gap" failure to protect humans, particularly the young, from a series of mass population toxic exposures (e.g., asbestos, trichloroethylene, dioxin, polychlorinated biphenyls, triclosan, bisphenol A and other plasticizers, polyfluorinated compounds, herbicides, food emulsifiers, high fructose corn syrup, certain nanoparticles, endocrine disruptors, and obesogens). The combination of early life toxicity for the microbiome and connected human physiological systems (e.g., immune, neurological), plus a lack of attention to the importance of microbial rebiosis has facilitated rather than suppressed, the NCD epidemic. This review article concludes with a call to place the microbiome first and foremost in public health initiatives as a way to both rescue public health effectiveness and reduce the human suffering connected to comorbid NCDs.

The National Children's Study Archive Model: A 3-Tier Framework for Dissemination of Data and Specimens for General Use and Secondary Analysis

The National Children's Study (NCS) Archive was created as a repository of samples, data, and information from the NCS Vanguard Study-a longitudinal pregnancy and birth cohort evaluating approaches to study influence of environmental exposures on child health and development-to provide qualified researchers with access to NCS materials for use in secondary research. The National Children's Study Archive (NCSA) model is a 3-tiered access model designed to make the wealth of information and materials gathered during the NCS Vanguard Study available at a user appropriate level. The NCSA model was developed as a 3-tier framework, for users of varying access levels, providing intuitive data exploration and visualization tools, an end-to-end data and sample request management system, and a restricted portal for participant-level data access with a team of experts available to assist users. This platform provides a model to accelerate transformation of information and materials from existing studies into new scientific discoveries. Trial Registration: ClinicalTrials.gov Identifier: NCT00852904 (first posted February 27, 2009).

Approach to High Volume Enrollment in Clinical Research: Experiences from an All of Us Research Program Site

Clinical trials and cohort studies are required to meet target recruitment of study participants within stipulated timelines, especially when the priority is to include populations traditionally unrepresented in biomedical research. By the third quarter of 2019, the University of Arizona‐Banner Health Provider Organization (UA‐Banner HPO) has enrolled > 30,000 core participants into the All of Us Research Program (AoURP), the research cohort of the Precision Medicine Initiative. The majority of enrolled participants meet the criteria for individuals under‐represented in biomedical research. The enrollment goals were calculated based on a target of 20,000 as set by the National Institutes of Health and our health provider organization achieved enrollment numbers between 17% and 86% above the targeted daily enrollment. We evaluated enrollment methods and challenges to enrollments encountered by the UA‐Banner Health Provider Organization into the AoURP. Challenges to enrollment centered around the need for high‐touch engagement methods, time investment necessary for stakeholder inclusion, and the use of purely digital enrollment methods especially in populations under‐represented in biomedical research. These challenges occurred at the level of the individual, provider, institutions, and community, and cumulatively impacted participant enrollment. Successful strategies for engagement and enrollment leveraged provider partners as advocates for the program. For high‐volume enrollment in clinical research, it is important to engage leaders in the healthcare setting, patient providers, and tailor engagement and enrollment to potential participant needs. We emphasize the need for precision engagement and enrollment methods tailored to individual needs.

Comparison of Recruitment Strategy Outcomes in the National Children's Study

BACKGROUND AND OBJECTIVES

In 2000, the US Congress authorized the National Institutes of Health to conduct a prospective national longitudinal study of environmental influences on children's health and development from birth through 21 years. Several recruitment methodologies were piloted to determine the optimal strategy for a main National Children's Study.

METHODS

After an initial pilot recruitment that used a household enumeration strategy performed poorly, the National Children's Study Vanguard Study developed and evaluated the feasibility, acceptability, and cost of 4 alternate strategies to recruit a large prospective national probability sample of pregnant women and their newborn children. We compare household-based recruitment, provider-based recruitment, direct outreach, and provider-based sampling (PBS) strategies with respect to overall recruitment success, efficiency, cost, and fulfillment of scientific requirements.

RESULTS

Although all 5 strategies achieved similar enrollment rates (63%-81%) among eligible women, PBS achieved the highest recruitment success as measured by the ratio of observed-to-expected newborn enrollees per year of 0.99, exceeding those of the other strategies (range: 0.35-0.48). Because PBS could reach the enrollment target through sampling of high volume obstetric provider offices and birth hospitals, it achieved the lowest ratio of women screened to women enrolled and was also the least costly strategy. With the exception of direct outreach, all strategies enrolled a cohort of women whose demographics were similar to county natality data.

CONCLUSIONS

PBS demonstrated the optimal combination of recruitment success, efficiency, cost, and population representativeness and serves as a model for the assembly of future prospective probability-based birth cohorts.