Allostatic Load in Childhood, Adolescence, and Young Adulthood: Are Assumptions of Measurement Invariance Warranted?

OVERVIEW: Allostatic load represents the cumulative toll of chronic mobilization of the body's stress response systems, as indexed by biomarkers. Higher levels of stress and disadvantage predict higher levels of allostatic load, which, in turn, predict poorer physical and mental health outcomes. To maximize the efficacy of prevention efforts, screening for stress- and disadvantage-associated health conditions must occur before middle age-that is, during childhood, adolescence, and young adulthood. However, this requires that models of allostatic load display properties of measurement invariance across age groups. Because most research on allostatic load has featured older adults, it is unclear if these requirements can be met. METHODS: To address this question, we fit a series of exploratory and confirmatory analytic models to data on eight biomarkers using a nationally representative sample of N = 4260 children, adolescents, and young adults drawn from the National Health and Nutrition Examination Survey dataset. RESULTS: Exploratory and confirmatory models indicated that, consistent with allostatic load theory, a unidimensional model was a good fit to the data. However, this model did not display properties of measurement invariance; post-hoc analyses suggested that the biomarkers included in the final confirmatory model were most strongly intercorrelated among young adults and most weakly intercorrelated among adolescents. CONCLUSIONS: These results underscore the importance of testing assumptions about measurement invariance in allostatic load before drawing substantive conclusions about stress, disadvantage, and health by directly comparing levels of allostatic load across different stages of development, while underscoring the need to expand investigations of measurement invariance to samples of longitudinal data.

Four conservation challenges and a synthesis.

Conservation and management of biological systems involves decision-making over time, with a generic goal of sustaining systems and their capacity to function in the future. We address four persistent and difficult conservation challenges: (1) prediction of future consequences of management, (2) uncertainty about the system's structure, (3) inability to observe ecological systems fully, and (4) nonstationary system dynamics. We describe these challenges in terms of dynamic systems subject to different sources of uncertainty, and we present a basic Markovian framework that can encompass approaches to all four challenges. Finding optimal conservation strategies for each challenge requires issue-specific structural features, including adaptations of state transition models, uncertainty metrics, valuation of accumulated returns, and solution methods. Strategy valuation exhibits not only some remarkable similarities among approaches but also some important operational differences. Technical linkages among the models highlight synergies in solution approaches, as well as possibilities for combining them in particular conservation problems. As methodology and computing software advance, such an integrated conservation framework offers the potential to improve conservation outcomes with strategies to allocate management resources efficiently and avoid negative consequences.

Partial observability and management of ecological systems.

The actual state of ecological systems is rarely known with certainty, but management actions must often be taken regardless of imperfect measurement (partial observability). Because of the difficulties in accounting for partial observability, it is usually treated in an ad hoc fashion, or simply ignored altogether. Yet incorporating partial observability into decision processes lends a realism that has the potential to improve ecological outcomes significantly. We review frameworks for dealing with partial observability, focusing specifically on dynamic ecological systems with Markovian transitions, i.e., transitions among system states that are influenced by the current system state and management action over time. Fully observable states are represented in an observable Markov decision process (MDP), whereas obscure or hidden states are represented in a partially observable process (POMDP). POMDPs can be seen as a natural extension of observable MDPs. Management under partial observability generalizes the situation for complete observability, by recognizing uncertainty about the system's state and incorporating sequential observations associated with, but not the same as, the states themselves. Decisions that otherwise would depend on the actual state must be based instead on state probability distributions ("belief states"). Partial observability requires adaptation of the entire decision process, including the use of belief states and Bayesian updates, valuation that includes expectations over observations, and optimal strategy that identifies actions for belief states over a continuous belief space. We compare MDPs and POMDPs and highlight POMDP applications to some common ecological problems. We clarify the structure and operations, approaches for finding solutions, and analytic challenges of POMDPs for practicing ecologists. Both observable and partially observable MDPs can use an inductive approach to identify optimal strategies and values, with a considerable increase in mathematical complexity with POMDPs. Better understanding of POMDPs can help decision makers manage imperfectly measured ecological systems more effectively.

Deconstructing Cumulative Risk: Poverty and Aspects of Instability Relate Uniquely to Young Children's Basal Cortisol.

This study deconstructs cumulative risk to probe unique relations to basal cortisol for family income and four distinct aspects of poverty-related instability. Participants were 288 children aged 3-5 years who attended Head Start preschool. Parents reported on poverty risks. Children provided samples of salivary cortisol at four times of day on 6 days. Results of hierarchical linear modeling with piecewise latent growth curves representing basal cortisol indicated unique relations for family income, household chaos, neighborhood risk, attachment-disruptive residential changes, and non-attachment changes. The findings support an equifinality implied by cumulative risk models in demonstrating that multiple risks relate to cortisol dysregulation yet also suggest the utility of considering unique effects of different risks for neurophysiological stress response functioning.

Planting the Seeds: Orchestral Music Education as a Context for Fostering Growth Mindsets.

Growth mindset is an important aspect of children's socioemotional development and is subject to change due to environmental influence. Orchestral music education may function as a fertile context in which to promote growth mindset; however, this education is not widely available to children facing economic hardship. This study examined whether participation in a program of orchestral music education was associated with higher levels of overall growth mindset and greater change in levels of musical growth mindset among children placed at risk by poverty. After at least 2 years of orchestral participation, students reported significantly higher levels of overall growth mindset than their peers; participating students also reported statistically significant increases in musical growth mindset regardless of the number of years that they were enrolled in orchestral music education. These findings have implications for future research into specific pedagogical practices that may promote growth mindset in the context of orchestral music education and more generally for future studies of the extra-musical benefits of high-quality music education.

Economic instability and household chaos relate to cortisol for children in poverty.

The present study investigated relations among various aspects of economic adversity and cortisol levels for young children facing economic hardship. Specifically, the study examined relations to cortisol for variables representing family income, material hardship, financial strain, economic instability, and household chaos. Participants were 374 children, ages 3-5 years, who attended a Head Start preschool, as well as their primary caregivers. Nearly all children lived in households classified as poor or low-income, defined as less than two times the federal poverty threshold. Caregivers completed interviews about family demographics and economic adversity at the beginning of the school year. Child salivary cortisol was sampled in duplicate on two weekday mornings at the end of the school year. We hypothesized that economic instability would show direct statistical effects on child cortisol as well as indirect effects via household chaos. A structural equation model that corresponded to this hypothesis showed adequate fit for the sample data and revealed a statistically significant indirect effect of economic adversity on child cortisol via economic instability and household chaos, as well as statistically significant direct effects of economic instability and chaos on child cortisol, and a significant indirect effect of economic instability on cortisol via household chaos. Implications concern understanding mechanisms of poverty risk, including the impact of instability and chaos on stress physiology, and promoting physiological regulation for children facing economic hardship. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

The potential for citizen science to produce reliable and useful information in ecology.

We examined features of citizen science that influence data quality, inferential power, and usefulness in ecology. As background context for our examination, we considered topics such as ecological sampling (probability based, purposive, opportunistic), linkage between sampling technique and statistical inference (design based, model based), and scientific paradigms (confirmatory, exploratory). We distinguished several types of citizen science investigations, from intensive research with rigorous protocols targeting clearly articulated questions to mass-participation internet-based projects with opportunistic data collection lacking sampling design, and examined overarching objectives, design, analysis, volunteer training, and performance. We identified key features that influence data quality: project objectives, design and analysis, and volunteer training and performance. Projects with good designs, trained volunteers, and professional oversight can meet statistical criteria to produce high-quality data with strong inferential power and therefore are well suited for ecological research objectives. Projects with opportunistic data collection, little or no sampling design, and minimal volunteer training are better suited for general objectives related to public education or data exploration because reliable statistical estimation can be difficult or impossible. In some cases, statistically robust analytical methods, external data, or both may increase the inferential power of certain opportunistically collected data. Ecological management, especially by government agencies, frequently requires data suitable for reliable inference. With standardized protocols, state-of-the-art analytical methods, and well-supervised programs, citizen science can make valuable contributions to conservation by increasing the scope of species monitoring efforts. Data quality can be improved by adhering to basic principles of data collection and analysis, designing studies to provide the data quality required, and including suitable statistical expertise, thereby strengthening the science aspect of citizen science and enhancing acceptance by the scientific community and decision makers.

Potencial de la Ciencia Ciudadana para Producir Información Útil y Confiable en la Ecología Resumen Examinamos las características de la ciencia ciudadana que influyen sobre la calidad de datos, el poder inferencial, y la utilidad en la ecología. Consideramos temas como el muestreo ecológico (basado en probabilidad, deliberado, oportunista), la conexión entre la técnica de muestreo y la inferencia estadística (basada en diseño, basada en modelo) y los paradigmas científicos (confirmatorio, exploratorio) como trasfondo contextual para nuestra evaluación. Distinguimos varios tipos de investigación de ciencia ciudadana, desde investigación intensiva con protocolos rigurosos enfocados en preguntas claramente articuladas hasta proyectos de participación masiva en plataformas de internet con recolección de datos oportunistas carentes de un diseño de muestreo, y examinamos los objetivos generales, el diseño, el análisis, y la preparación de los voluntarios y el desempeño. Identificamos características clave que influyen sobre la calidad de los datos: los objetivos del proyecto, el diseño y el análisis, y la preparación y el desempeño de los voluntarios. Los proyectos con buenos diseños, voluntarios preparados, y supervisión profesional pueden cumplir con criterios estadísticos para producir datos de alta calidad con un fuerte poder inferencial, y por lo tanto son muy adecuados para los objetivos de investigación ecológica. Los proyectos con una recolección oportunista de datos, un diseño de muestreo ínfimo o nulo, y una preparación mínima de los voluntarios son más adecuados para los objetivos generales relacionados con la educación pública o la exploración de datos ya que la estimación estadística confiable puede ser complicada o imposible. En algunos casos los métodos analíticos estadísticamente sólidos, los datos externos, o ambos, pueden incrementar el poder inferencial de ciertos datos recolectados de manera oportunista. El manejo ecológico, en especial el que realizan las agencias gubernamentales, requiere frecuentemente de datos apropiados para una inferencia confiable. Con protocolos estandarizados, métodos analíticos modernos, y programas supervisados correctamente, la ciencia ciudadana puede contribuir de forma valiosa a la conservación al incrementar el alcance de los esfuerzos de monitoreo para una especie. La calidad de datos puede mejorarse si se adhiere a los principios básicos de la recolección y análisis de datos, se diseñan los estudios para que proporcionen la calidad requerida de datos, y si se incluye una pericia estadística adecuada, fortaleciendo así el aspecto científico de la ciencia ciudadana y aumentando su aceptación dentro de la comunidad científica y con quienes toman las decisiones.

Double-Loop Learning in Adaptive Management: The Need, the Challenge, and the Opportunity.

Adaptive management addresses uncertainty about the processes influencing resource dynamics, as well as the elements of decision making itself. The use of management to reduce both kinds of uncertainty is known as double-loop learning. Though much work has been done on the theory and procedures to address structural uncertainty, there has been less progress in developing an explicit approach for institutional learning about decision elements. Our objective is to describe evidence-based learning about the decision elements, as a complement to the formal "learning by doing" framework for reducing structural uncertainties. Adaptive management is described as a multi-phase approach to management and learning, with a set-up phase of identifying stakeholders, objectives, and other decision elements; an iterative phase that uses these elements in an ongoing cycle of technical learning about system structure and management impacts; and an institutional learning phase involving the periodic reconsideration of the decision elements. We describe a framework for institutional learning that is complementary to that of technical learning, including uncertainty metrics, propagation of change, and mechanisms and consequences of change over time. Operational issues include ways to recognize when the decision elements should be revisited, which elements should be adjusted, and how alternatives can be identified and incorporated based on experience and management performance. We discuss the application of this framework in decision making for renewable natural resources. As important as it is to learn about the processes driving resource dynamics, learning about the elements of the decision architecture is equally, if not more, important.

Can the Arts Get Under the Skin? Arts and Cortisol for Economically Disadvantaged Children.

This within-subjects experimental study investigated the influence of the arts on cortisol for economically disadvantaged children. Participants were 310 children, ages 3-5 years, who attended a Head Start preschool and were randomly assigned to participate in different schedules of arts and homeroom classes on different days of the week. Cortisol was sampled at morning baseline and after arts and homeroom classes on two different days at start, middle, and end of the year. For music, dance, and visual arts, grouped and separately, results of piecewise hierarchical linear modeling with time-varying predictors suggested cortisol was lower after an arts versus homeroom class at middle and end of the year but not start of the year. Implications concern the impact of arts on cortisol for children facing poverty risks.

Resilience and Resource Management.

Resilience is an umbrella concept with many different shades of meaning. The use of the term has grown over the past several decades to the point that by now, many disciplines have their own definitions and metrics. In this paper, we aim to provide a context and focus for linkages of resilience to natural resources management. We consider differences and similarities in resilience as presented in several disciplines relevant to resource management. We present a conceptual framework that includes environmental drivers, management interventions, and system responses cast in terms of system resilience, as well as a process for decision making that allows learning about system resilience through experience and incorporation of that learning into management. We discuss the current state of operational management for resilience, and suggest ways to improve it. Finally, we describe the challenges in managing for resilience and offer some recommendations about the scientific information needs and scientific issues relevant to making resilience a more meaningful component of natural resources management.

Adaptive management: from more talk to real action.

The challenges currently facing resource managers are large-scale and complex, and demand new approaches to balance development and conservation goals. One approach that shows considerable promise for addressing these challenges is adaptive management, which by now is broadly seen as a natural, intuitive, and potentially effective way to address decision-making in the face of uncertainties. Yet the concept of adaptive management continues to evolve, and its record of success remains limited. In this article, we present an operational framework for adaptive decision-making, and describe the challenges and opportunities in applying it to real-world problems. We discuss the key elements required for adaptive decision-making, and their integration into an iterative process that highlights and distinguishes technical and social learning. We illustrate the elements and processes of the framework with some successful on-the-ground examples of natural resource management. Finally, we address some of the difficulties in applying learning-based management, and finish with a discussion of future directions and strategic challenges.

Family adversity and inhibitory control for economically disadvantaged children: preschool relations and associations with school readiness.

This study examined longitudinal relations linking aspects of family adversity to inhibitory control and school readiness for 120 economically disadvantaged children attending a Head Start preschool. The aspects of family adversity included income-to-needs ratios and an adversity index representing family instability and family chaos. The results showed that the adversity index but not the income ratios contributed to explaining diversity in the development of inhibitory control over the course of the preschool year. Additionally, the adversity index predicted school readiness at the end of the year, and the results suggested that inhibitory control mediated this effect. The implications concern understanding family sources of diversity in inhibitory control for economically disadvantaged preschool children.

Chaotic living conditions and sleep problems associated with children's responses to academic challenge.

The ecology of economic disadvantage includes chaotic living conditions that may disrupt children's regulatory functioning and undermine mastery oriented responses to challenge. The present study examined chaotic living conditions, sleep problems, and responses to academic challenge for 96 economically disadvantaged children enrolled in a Head Start preschool. Caregiver interviews provided information regarding chaotic living conditions of residential crowding, noise, and family instability, as well as child sleep problems. Tasks individually administered to children provided measures of responses to academic challenge. Chaotic living conditions statistically predicted helpless/hopeless responses to academic challenge, and sleep problems partially mediated this relationship. Implications concern pathways of ecological risk and diversity in the school functioning of economically disadvantaged children.

Relation between reading problems and internalizing behavior in school for preadolescent children from economically disadvantaged families.

This longitudinal study of 105 economically disadvantaged children examined the relation between reading problems and internalizing behavior in 3rd- and 5th-grade assessments (8- to 12-year olds). The variable-centered results showed that reading problems predicted change in internalizing behavior in the context of child and family predictors. The person-centered results showed that children with reading problems in both grades had higher internalizing scores in 5th grade but not in 3rd grade than children with reading problems in 3rd grade or no problems. Child-reported negative emotion experiences varied similarly across grade. The results tie reading problems to emotional distress in school and support conclusions about the direction of effects and the internalization of academic difficulty for disadvantaged children.

Income poverty, poverty co-factors, and the adjustment of children in elementary school.

Since 1990, there have been great advances in how developmental researchers construct poverty. These advances are important because they may help inform social policy at many levels and help frame how American culture constructs poverty for children, both symbolically and in the opportunities children and families get to escape from poverty. Historically, developmental perspectives have embodied social address and main effects models, snapshot views of poverty effects at single points in time, and a rather narrow focus on income as the symbolic marker of the ecology of disadvantage. More recent views, in contrast, emphasize the diverse circumstances of disadvantaged families and diverse outcomes of disadvantaged children, the multiple sources of risk and the multiple determinants of poor outcomes for these children, dynamic aspects of that ecology, and change as well as continuity in outcome trajectories. The advances also consist of more powerful frames for understanding the ecology of disadvantage and the risk it poses for child outcomes. Most developmental researchers still tend to frame causal variables ultimately in terms of the dichotomy between social causation and social selection views, with a primary emphasis on the former. In part, this framing has reflected limitations of sample size and design, because the theoretical and empirical power of reciprocal selection models is clear (Kim et al., 2003). The conceptual advances that prompt such models include widespread acknowledgement of third variable problems in interpreting effects, of the clear need for multivariate approaches, and the need to pursue mechanisms and moderators of the relations between causal candidates and child outcomes. In the context of these advances, one of the core goals of our research program has been to construct robust representations of environmental adversity for disadvantaged families. Most of our research focuses on contextual co-factors at a family level (e.g., maternal relationship instability), which either have not been described by many researchers or have been described in a way that does not fit the ecology of disadvantage (e.g., marital status). We found that income poverty, key contextual co-factors, and endogenous child attributes tend to show independent and selective associations with child academic competence and externalizing behavior, and that co-factor effects tend to be direct rather than mediated by harsh parenting, tend to have effects that are episodic and concurrent, and are easily- and well-represented by multiple risk indexes that bear powerful relations to child problem behaviors. A second core goal has been to better understand the developmental construction of poor outcomes for disadvantaged children, which requires consideration of dynamic aspects of the ecology and the potential importance of the timing of risk experiences. We found that family instability and change in environmental circumstances predict increases in problem behaviors, and that dose of adversity seems to matter for some variables if it is recent, and not for other variables. Through person-centered research, we also are beginning to understand some factors that seem to underlie the convergence of adjustment problems over grade in school. Many of our co-factor findings and many of our developmental findings seem both complex and double-edged. One edge is that they encourage a certain pessimism in showing how environmental adversity progressively constructs poor outcomes for disadvantaged children in school. Overall, for instance, we saw more problems and more multi-dimensional problems in fifth grade than in first grade, and the impact of environmental change was mostly negative. The other edge, however, is more positive in reflecting the possibility of discontinuity in child adjustment problems associated with positive changes in family circumstances. Findings for minimal persistence and for the strength of recent and concurrent effects argue that the possibility of self-righting and emergent competence in school is robust through the fifth grade even for the most problematic disadvantaged children.

The relations between persistent poverty and contextual risk and children's behavior in elementary school.

Does persistent adversity over time have effects on children's behavior beyond the effects of intermittent or concurrent adversity? This study examined the relations between school behavior in 5th grade (mean age = 11 years 0 months) and indexes representing persistent poverty and contextual risk. The indexes described 2-year intervals of family adversity. The results showed effects for persistent risk over 2 consecutive intervals for several factors, but only for recent intervals (3rd and 5th grades), and the factors differed for externalizing behavior, internalizing behavior, and academic competence. The 3rd interval of risk added little to the outcomes, and most factors did not show persistence effects. The results highlight the need for caution in expecting and interpreting effects for persistent adversity.

The relations between contextual risk, earned income, and the school adjustment of children from economically disadvantaged families.

This longitudinal study examined the relations between multiple risk indexes representing contextual adversity, income-to-needs ratios, and the elementary school adjustment of children from economically disadvantaged families. The results provide evidence for volatility in family circumstances over 2-year intervals from preschool to 5th grade, for relations between the contextual risk indexes and change in externalizing behavior, and for relations between the income-to-needs ratios and change in academic competence. The results also show differences in the timing of the effects. Little evidence was found for persistence effects. Theoretical implications concern conceptualizations of the diverse and dynamic nature of the family circumstances experienced by disadvantaged children.

Maternal relationship instability and the school behavior of children from disadvantaged families.

This longitudinal study examined the relation between the instability of maternal intimate relationships and the school behavior of 3rd-grade children from economically disadvantaged families. After ecological correlates were controlled, chronic relationship instability predicted externalizing behavior for boys and girls and internalizing behavior for girls, but not academic competence. In addition, past and recent instability had independent effects: Recent instability moderated the relation for past instability, and child adjustment in highly unstable families varied with verbal ability and aspects of the family ecology. The theoretical implications concern conceptualizations of the diverse and dynamic nature of family arrangements experienced by disadvantaged children.

A test of pollinator specificity and morphological convergence between nectarivorous birds and rainforest tree flowers in New Guinea.

Interactions between flowering trees in a representative sample of vegetation, and the birds that fed at their flowers, were studied for 2 years in lowland tropical hill forest in New Guinea. All 2,200 trees in a 3-ha plot were tagged, identified, mapped, and monitored monthly. Approximately 60% of all individual trees flowered during the study; all species that these flowering individuals belonged to were evaluated for bird visitation. Approximately 13% of the 164 resident species of New Guinea avifauna at the study site, especially honeyeaters and parrots, visited flowers. In the forest inventory plot, approximately 15-22% of all 86 tree species that flowered during the study were visited by birds; most of these tree species were canopy species. Results showed that there was no statistically significant correlation between bird species grouped by bill morphology and flower species grouped as morphotypes and ranked by nectar accessibility, although strong but unexpected bird/plant associations were evident. These associations may be related to variables such as body mass or perch size. These results are discussed in comparison with results from the Neotropics and Australia, and in terms of morphological convergence and pollinator specificity in pollination systems.