Faculty Bibliography

We present a hierarchical integrated model of self-regulation in which executive function is the cognitive component of the model, together with emotional, behavioral, physiological, and genetic components. These five components in the model are reciprocally and recursively related. The model is supported by empirical evidence, primarily from a single longitudinal study with good measurement at each level of the model. We also find that the model is consistent with current thinking on related topics such as cybernetic theory, the theory of allostasis and allostatic load, and the theory of skill development in harsh and unpredictable environments, referred to as "hidden talents." Next, we present literature that the integrative processes are susceptible to environmental adversity, poverty-related risk in particular, while positive social interactions with caregivers (e.g., maternal sensitivity) would promote self-regulatory processes or mitigate the adverse effect of early risk on the processes. A hierarchical integrative model of self-regulation advances our understanding of self-regulatory processes. Future research may consider broader social contexts of the integrative self-regulation system, such as neighborhood/community contexts and structural racism. This can be an integral step to provide children with equitable opportunities to thrive, even among children living in socioeconomically and psychosocially disadvantaged environments.

The present study investigated associations between prenatal mother-father cortisol linkage and infant executive functions. Data come from an international sample (N = 358) of predominantly white and middle- to upper-class first-time parents. During late pregnancy, parents collected diurnal salivary cortisol samples and reported on levels of psychological stress. At 24 months, children completed a battery of executive function tasks. Parent cortisol linkage was operationalized as the time-dependent, within-dyad association between maternal and paternal diurnal cortisol. Results indicated that prenatal linkage was positively related to infant executive functions, suggesting that stronger mother-father cortisol linkage was associated with higher executive function scores. Additionally, this relation was moderated by paternal average cortisol levels such that executive function scores were lower when fathers had higher average cortisol levels and linkage was weak. This association suggests that elevated paternal cortisol amplifies the negative relation between lower cortisol linkage and lower infant executive function scores. Importantly, these findings were observed while controlling for observational measures of caregiving and self-report measures of psychosocial functioning and infant social-emotional behavior. These results suggest that prenatal linkage of mother's and father's stress physiology plays a potentially important part in programming and regulating infant neurocognitive development.

We identified family risk profiles at 6 months using socioeconomic status (SES) and maternal mental health indicators with data from the Family Life Project (N = 1,292). We related profiles to executive function (EF) at 36 months (intercept) and growth in EF between 36 and 60 months. Latent profile analysis revealed five distinct profiles, characterized by different combinations of SES and maternal mental health symptoms. Maternal sensitivity predicted faster growth in EF among children in the profile characterized by deep poverty and the absence of maternal mental health symptoms. Maternal sensitivity also predicted higher EF intercept but slower EF growth among children in the profile characterized by deep poverty and maternal mental health symptoms, and children in the near poor (low SES), mentally healthy profile. Maternal sensitivity also predicted higher EF intercept but had no effect on growth in EF in the near poor, mentally distressed profile. In contrast, maternal sensitivity did not predict the intercept or growth of EF in the privileged SES/mentally healthy profile. Our findings using a person-centered approach provide a more nuanced understanding of the role of maternal sensitivity in the growth of EF, such that maternal sensitivity may differentially affect the growth of EF in various contexts.

One pathway by which environments of socioeconomic risk are thought to affect cognitive development is through stress physiology. The biological systems underpinning stress and attention undergo a sensitive period of development during infancy. Psychobiological theory emphasizes a dynamic pattern of context-dependent development, however, research has yet to examine how basal cortisol and attention dynamically covary across infancy in ecologically valid contexts. Thus, to address these gaps, we leveraged longitudinal, multilevel analytic methods to disentangle between- from within-person associations of hypothalamic-pituitary-adrenal (HPA) axis activity and executive attention behaviors across infancy. We use data from a large longitudinal sample (N = 1,292) of infants in predominantly low-income, nonurban communities at 7-, 15-, and 24-months of age. Using multilevel models, we investigated longitudinal associations of infant attention and basal cortisol levels and examined caregiving behaviors as moderators of this relationship. Results indicated a negative between- and within-person association between attention and cortisol across infancy and a within-person moderation by caregiver responsiveness. In other words, on the within-person level, higher levels of cortisol were concomitantly associated with lower infant attention across the first 2 years of life. However, variation in the caregiver's level of responsiveness either buffered or sensitized the executive attention system to the negative effects of physiological stress.

Income, education, and cumulative-risk indices likely obscure meaningful heterogeneity in the mechanisms through which poverty impacts child outcomes. This study draws from contemporary theory to specify multiple dimensions of poverty-related adversity and resources, with the aim of better capturing these nuances. Using data from the Family Life Project (N = 1,292), we leveraged moderated nonlinear factor analysis (Bauer, 2017) to establish group- and longitudinally invariant environmental measures from infancy to early adolescence. Results indicated three latent factors-material deprivation, psychosocial threat, and sociocognitive resources-were distinct from each other and from family income. Each was largely invariant across site, racial group, and development and showed convergent and discriminant relations with age-twelve criterion measures. Implications for ensuring socioculturally valid measurements of poverty are discussed.

This study examines whether changes in classroom quality predict within-child changes in achievement and behavioral problems in elementary school (ages spanning approximately 6-11 years old). Drawing on data from a longitudinal study of children in predominantly low-income, nonurban communities (n = 1,078), we relied on child fixed effects modeling, which controlled for stable factors that could bias the effects of classroom quality. In general, we found that changes in classroom quality had small and statistically nonsignificant effects on achievement and behavior. However, we found that moving into a high-quality classroom, particularly those rated as high in Classroom Organization, had positive effects on achievement and behavior for children with significant exposure to poverty in early life.

Left censoring in salivary bioscience data occurs when salivary analyte determinations fall below the lower limit of an assay's measurement range. Conventional statistical approaches for addressing censored values (i.e., recoding as missing, substituting or extrapolating values) may introduce systematic bias. While specialized censored data statistical approaches (i.e., Maximum Likelihood Estimation, Regression on Ordered Statistics, Kaplan-Meier, and general Tobit regression) are available, these methods are rarely implemented in biobehavioral studies that examine salivary biomeasures, and their application to salivary data analysis may be hindered by their sensitivity to skewed data distributions, outliers, and sample size. This study compares descriptive statistics, correlation coefficients, and regression parameter estimates generated via conventional and specialized censored data approaches using salivary C-reactive protein data. We assess differences in statistical estimates across approach and across two levels of censoring (9% and 15%) and examine the sensitivity of our results to sample size. Overall, findings were similar across conventional and censored data approaches, but the implementation of specialized censored data approaches was more efficient (i.e., required little manipulations to the raw analyte data) and appropriate. Based on our review of the findings, we outline preliminary recommendations to enable investigators to more efficiently and effectively reduce statistical bias when working with left-censored salivary biomeasure data.

Best practice standards for measuring analyte levels in saliva recommend that all biospecimens be tested in replicate with mean concentrations used in statistical analyses. This approach prioritizes minimizing laboratory-based measurement error but, in the process, expends considerable resources. We explore the possibility that, due to advances in salivary assay precision, the contribution of laboratory-based measurement error in salivary analyte data is very small relative to more important and meaningful variability in analyte levels across biological replicates (i.e., between different specimens). To evaluate this possibility, we examine the utility of the repeatability intra-class correlation (rICC) as an additional index of salivary analyte data precision. Using randomly selected subsamples (Ns=200 and 60) of salivary analyte data collected as part of a larger epidemiologic study, we compute the rICCs for seven commonly assayed salivary measures in biobehavioral research - cortisol, alpha-amylase, c-reactive protein, interlekin-6, uric acid, secretory immunoglobulin A, and testosterone. We assess the sensitivity of rICC estimates to assay type and the unique distributions of the underlying analyte data. We also use simulations to examine the bias, precision, and coverage probability of rICC estimates calculated for small to large sample sizes. For each analyte, the rICCs revealed that less than 5% of variation in analyte levels was attributable to laboratory-based measurement error. rICC estimates were similar across all analytes despite differences in analyte levels, average intra-assay coefficients of variation, and in the distributional properties of the data. Guidelines for calculating rICC are provided to enable investigators and laboratory staff to apply this metric and more accurately quantify, and communicate, the magnitude of laboratory-based measurement error in their data. By helping investigators scale measurement error relative to more scientifically meaningful variability between biological replicates, the application of the rICC has the potential to influence research strategies and tactics such that resources (e.g., finances, effort, number/volume of biospecimens) are allocated more efficiently and effectively.

Although policies to remove lead from gasoline have resulted in a substantial reduction in airborne lead, multiple industries are known to generate lead that is released in the air. The present study examines the extent to which residential proximity to a documented source of airborne lead is associated with intellectual and executive function in children. Data were available for n = 849 children from the Family Life Project. Geolocation for children's residences between birth and 36 months were referenced against the Environmental Protection Agency's Risk Screening Environmental Indicators (RSEI) database, which estimates exposure for each ½ mile grid in the contiguous United States. Instrumental variable models were employed to estimate causal associations between exposure and cognitive outcomes measured at 36, 48, and 60 months, using census-documented density of manufacturing employment as the instrument. Models of continuous lead dosage indicated small negative effects for both child IQ and executive function (EF). These results indicate that RSEI estimates of airborne lead exposure are meaningfully associated with decrements in cognitive development.

OBJECTIVE:The aim of this study was to identify longitudinal trajectories of conjoint development of executive function (EF) and obesity among a diverse sample of poor, rural youth and to evaluate individual differences in infant growth, parental BMI, and cumulative risk. METHODS:Participants included 948 youth from the Family Life Project. Child anthropometrics were measured at 2 and 6 months and at 2, 3, 4, 5, 7, and 12 years. EF tasks were administered at 3, 4, and 5 years. Mothers reported youth birth weight, parental height and weight, and cumulative risk indicators. RESULTS:Multidimensional growth mixture modeling identified three classes: "High EF - High Obesity Resilience"; "Low EF - Delayed-Onset Severe Obesity"; and "Low EF - Early-Onset Severe Obesity." Youth in the low-EF, early-onset class displayed higher birth weight and BMI at 6 months, whereas the low-EF, delayed-onset class had rapid weight gain during infancy, parents with class II obesity, and greater cumulative risk and was more likely to be Black and female. CONCLUSIONS:Despite increased obesity risk among this sample, the majority of youth exhibited higher EF and some degree of obesity resilience. Youth with EF deficits displayed the greatest risk for severe obesity but had differing BMI trajectories and obesity risk profiles, which has implications for obesity intervention.