are likely to be contributing to a large fraction of disease in most populations. Key to the success of research on these interactions is the conduct of such research in a collaborative and transdisciplinary manner, which “implies the conception of research questions that transcend the individual departments or specialized knowledge bases because they are intended to solve … research questions that are, by definition, beyond the purview of the individual disciplines” (IOM, 2003). Furthermore, more comprehensive, predictive models of etiologically heterogeneous disease are needed, and this requires the development and implementation of new modeling strategies and the use of profiling approaches. In order to ensure that findings are applicable beyond a small population, research must be conducted in diverse groups and settings (Chapter 6). Animal models, which are explored in Chapter 7, have a great deal to offer in understanding the effects of interactions of social, behavioral, and genetic factors on health.
A clear formulation of the concept of interaction, and an understanding of research designs that can be used to test for it, are central to progress in assessing the impact on health of interactions among multiple factors. This report discusses several steps that are needed to advance the science of testing interactions (Chapter 8). These include new, accessible statistical software for implementing tests for interaction on an additive scale and research on developing study designs that are efficient at testing interactions, including variations in interactions over time and development.
Transdisciplinary research on the impact on health of interactions among social, behavioral, and genetic factors places several demands on the research infrastructure, including the need for education and training of researchers, the enhancement and development of appropriate datasets, and the creation of incentives and rewards that will encourage investigators to move beyond the single discipline approach to research. Approaches that the National Institutes of Health can use to address these barriers include providing individual and senior fellowships, transdisciplinary institutional grants, short courses, and datasets that can be enhanced to provide the necessary information. The development of new datasets for topics that have high potential for showing interactions also would be valuable. Other incentives that foster the transdisciplinary research discussed in this report address hiring, promotion and tenure policies, peer review, and the allocation of credit for collaborative research (Chapter 9).
Finally, research that elucidates how social, behavioral, and genetic factors interact to influence health raises important ethical and legal issues, including those involving how individuals and groups understand and use complex scientific findings, as well as the potential impact such findings might have on policy development (Chapter 10).
Furthermore, studying interactions among variations in social, behavioral, and genetic factors requires the collection of information that could