Trentacosta, C, Davis-Kean, P.E., Mitchell, C, Hyde, L, Dolinoy, D. (2016). Environmental Contaminants and Child Development. Child Development Perspectives.
Abstract: Developmental scientists have long been interested in how the environment influences children’s development. However, with few exceptions, they have not researched how exposure to contaminants in the physical environment affects developmental processes. Children are uniquely at risk for exposure to contaminants because they drink more, eat more, and breathe more air than adults as a proportion of their body weight. In this article, we provide an ecosystems perspective to illustrate how contexts—from the prenatal environment and neighborhood-level exposure to laws and policies—contribute to children’s exposure to contaminants. We also discuss four mechanisms that account for how and when exposure to contaminants affects children, and we provide examples to spur research on these mechanisms. We conclude with recommendations to foster integrative science where developmental science interacts with environmental health and toxicology.
Falk, E B., Hyde, L.W., Mitchell, C., Faul, J., Gonzalez, R., Heitzeg, M., Keating, D.P., Langa, K. M., Martz, M.E., Maslowsky, J., Morrison, F. J., Noll, D.C., Patrick, M.E., Pfeffer, F.T., Reuter-Lorenz, P.A., Thomason, M. E. Davis-Kean, P. E., Christopher S. Monk, C. S., and Schulenberg, J. (2013). Neuroscience meets population science: What is a representative brain? Proceedings of the National Academy of Sciences, 110 (44), 17615-17622.
Abstract: The last decades of neuroscience research have produced immense progress in the methods available to understand brain structure and function. Social, cognitive, clinical, affective, economic, communication, and developmental neurosciences have begun to map the relationships between neuro-psychological processes and behavioral outcomes, yielding a new understanding of human behavior and promising interventions. However, a limitation of this fast moving research is that most findings are based on small samples of convenience. Furthermore, our understanding of individual differences may be distorted by unrepresentative samples, undermining findings regarding brain–behavior mechanisms. These limitations are issues that social demographers, epidemiologists, and other population scientists have tackled, with solutions that can be applied to neuroscience. By contrast, nearly all social science disciplines, including social demography, sociology, political science, economics, communication science, and psychology, make assumptions about processes that involve the brain, but have incorporated neural measures to differing, and often limited, degrees; many still treat the brain as a black box. In this article, we describe and promote a perspective—population neuroscience—that leverages interdisciplinary expertise to (i) emphasize the importance of sampling to more clearly define the relevant populations and sampling strategies needed when using neuroscience methods to address such questions; and (ii) deepen understanding of mechanisms within population science by providing insight regarding underlying neural mechanisms. Doing so will increase our confidence in the generalizability of the findings. We provide examples to illustrate the population neuroscience approach for specific types of research questions and discuss the potential for theoretical and applied advances from this approach across areas.