Measuring social-emotional development in schoolchildren: A national-level analysis of ECLS-B cohort data

The present study examined the social-emotional development items assessed by kindergarten teachers in the Early Childhood Longitudinal Study-Birth Cohort to determine the optimal factor structure underlying the items as well as the reliability and validity of the resulting factors. This study identified an empirically derived factor structure for teacher-reported social development, investigated whether there was evidence of bias in teacher assessments of social-emotional constructs, examined factor invariance across demographic characteristics (i.e., race and ethnicity, sex, and poverty status), and examined the external validity of the derived factors by determining the extent to which they were associated with well-established measures of early childhood competencies. Findings suggested a 4-factor solution was optimal, consisting of (a) Interpersonal Skills, (b) Externalizing Behavior, (c) Approaches to Learning, and (d) Perspective Taking. Findings offer suggestive evidence of teacher biases in assessments and some, although not conclusive, support for the invariance of social-emotional dimension across demographic characteristics. Results provide a useful next step toward documenting reliable and valid social-emotional measures for use in early childhood research and challenges users of national datasets to think critically about the use of "scales" without a priori attention to important psychometric properties.

Developmental impacts of the COVID-19 pandemic on young children: a conceptual model for research with integrated administrative data systems

The COVID-19 pandemic made its mark on the entire world, upending economies, shifting work and education, and exposing deeply rooted inequities. A particularly vulnerable, yet less studied population includes our youngest children, ages zero to five, whose proximal and distal contexts have been exponentially affected with unknown impacts on health, education, and social-emotional well-being. Integrated administrative data systems could be important tools for understanding these impacts. This article has three aims to guide research on the impacts of COVID-19 for this critical population using integrated data systems (IDS). First, it presents a conceptual data model informed by developmental-ecological theory and epidemiological frameworks to study young children. This data model presents five developmental resilience pathways (i.e. early learning, safe and nurturing families, health, housing, and financial/employment) that include direct and indirect influencers related to COVID-19 impacts and the contexts and community supports that can affect outcomes. Second, the article outlines administrative datasets with relevant indicators that are commonly collected, could be integrated at the individual level, and include relevant linkages between children and families to facilitate research using the conceptual data model. Third, this paper provides specific considerations for research using the conceptual data model that acknowledge the highly-localised political response to COVID-19 in the US. It concludes with a call to action for the population data science community to use and expand IDS capacities to better understand the intermediate and long-term impacts of this pandemic on young children.

A longitudinal analysis of fast-food exposure on child weight outcomes: Identifying causality through school transitions

This article investigates the effect of fast-food availability on childhood weight outcomes by gender, race, and location. We use a novel identification strategy based on changes in fast-food exposure along the route between the home and school that occur as students progress through the public school system and transition to different types of schools, e.g. from elementary school to intermediate school or from intermediate school to high school. Using a longitudinal census of height and weight for public school students in Arkansas, we find no evidence that changes in fast-food exposure are associated with changes in body mass index z-score for any student subpopulation.

Integrated Administrative Data for Early Childhood Iowa: A Governance Model to inform Policy and Program Collaboration

In response to demands on public systems to do more, do better, and cost less, the value of integrated administrative data systems (IDS) for social policy is increasing (Fantuzzo & Culhane, 2016). This is particularly relevant in programming for young children where services are historically fragmented, disconnected from systems serving school-aged children, and siloed among health, human services, and education agencies. Guided by the vision that Iowa’s early childhood system will be effectively and efficiently coordinated to support healthy families, we are developing an early childhood IDS to address this disconnection and facilitate relevant and actionable social policy research. Iowa’s IDS is a state-university partnership that acknowledges the need for agencies to retain control of their data while enabling it to be integrated across systems for social policy research. The innovative governance model deliberately incorporates procedures for stakeholder engagement at critical tension points between executive leaders, program managers, researchers, and practitioners. Standing committees (Governance Board, Data Stewardship, and Core team) authorize and implement the work of the IDS, while ad-hoc committees are solicited for specific projects to advise and translate research into practice. This paper will articulate the Iowa IDS governance model that was informed by means tested principles articulated by the Actionable Intelligence for Social Policy Network. It will include our collaborative development process; articulated mission and principles that guided discussions about legal authorization, governance, and use cases; and the establishment of governance committees to implement our vision for ethical and efficient use of administrative data for social policy.

Middle school transition and body weight outcomes: Evidence from Arkansas Public Schoolchildren

There is evidence that middle school transition adversely affects educational and psychological outcomes of pre-teen children, but little is known about the impacts of middle school transition on other aspects of health. In this article, we estimate the impact of middle school transition on the body mass index (BMI) of public schoolchildren in Arkansas, United States. Using an instrumental variable approach, we find that middle school transition in grade 6 led to a moderate decrease of 0.04 standard deviations in BMI z-scores for all students. Analysis by subsample indicated that this result was driven by boys (0.06-0.07 standard deviations) and especially by non-minority boys (0.09 standard deviations). We speculate that the changing levels of physical activities associated with middle school transition provide the most reasonable explanation for this result.

Food environment and childhood obesity: the effect of dollar stores

In this paper we examine the effect of dollar stores on children's Body Mass Index (BMI). We use a dataset compiled by the Arkansas Center for Health Improvement that reflects a BMI screening program for public school children in the state of Arkansas. We combine propensity score matching with difference-in-differences methods to deal with time-invariant as well time-varying unobserved factors. We find no evidence that the presence of dollar stores within a reasonably close proximity of the child's residence increases BMI. In fact, we see an increase in BMI when dollar stores leave a child's neighborhood. Given the proliferation of dollar stores in rural and low-income urban areas, the question of whether dollar stores are contributing to high rates of childhood obesity is policy relevant. However, our results provide some evidence that exposure to dollar stores is not a causal factor.

Pregnancy weight gain and childhood body weight: a within-family comparison

BACKGROUND

Excessive pregnancy weight gain is associated with obesity in the offspring, but this relationship may be confounded by genetic and other shared influences. We aimed to examine the association of pregnancy weight gain with body mass index (BMI) in the offspring, using a within-family design to minimize confounding.

METHODS AND FINDINGS

In this population-based cohort study, we matched records of all live births in Arkansas with state-mandated data on childhood BMI collected in public schools (from August 18, 2003 to June 2, 2011). The cohort included 42,133 women who had more than one singleton pregnancy and their 91,045 offspring. We examined how differences in weight gain that occurred during two or more pregnancies for each woman predicted her children's BMI and odds ratio (OR) of being overweight or obese (BMI≥85th percentile) at a mean age of 11.9 years, using a within-family design. For every additional kg of pregnancy weight gain, childhood BMI increased by 0.0220 (95% CI 0.0134-0.0306, p<0.0001) and the OR of overweight/obesity increased by 1.007 (CI 1.003-1.012, p = 0.0008). Variations in pregnancy weight gain accounted for a 0.43 kg/m(2) difference in childhood BMI. After adjustment for birth weight, the association of pregnancy weight gain with childhood BMI was attenuated but remained statistically significant (0.0143 kg/m(2) per kg of pregnancy weight gain, CI 0.0057-0.0229, p = 0.0007).

CONCLUSIONS

High pregnancy weight gain is associated with increased body weight of the offspring in childhood, and this effect is only partially mediated through higher birth weight. Translation of these findings to public health obesity prevention requires additional study. Please see later in the article for the Editors' Summary.