Author guidelines for journals could help to promote transparency, openness, and reproducibility

The global obesity epidemic has been on the rise for four decades, yet sustained prevention efforts have barely begun. An emerging science using quantitative models has provided key insights into the dynamics of this epidemic, and made it possible to combine different pieces of evidence and calculate the impact of behaviors, interventions and policies at multiple levels – from person to population. Forecasts indicate large effects of high levels of obesity on future population health and economic outcomes. Energy gap models have quantified the relationships of changes in energy intake and expenditure to weight change, and documented the dominant role of increasing intake on obesity prevalence. The empirical evidence base for effective interventions is limited but growing. Several cost-effective policies are identified that governments should prioritize for implementation. Systems science provides a framework for organizing the complexity of forces driving the obesity epidemic and has important implications for policy-makers. Multiple players (including governments, international organizations, the private sector, and civil society) need to contribute complementary actions in a coordinated approach. Priority actions include policies to improve the food and built environments, cross-cutting actions (such as leadership, health-in-all policies, and monitoring), and much greater funding for prevention programs. Increased investment in population obesity monitoring would improve the accuracy of forecasts and evaluations. Embedding actions within existing systems in both health and non-health sectors (trade, agriculture, transport, urban planning, development) can greatly increase impact and sustainability. We call for a sustained worldwide effort to monitor, prevent and control obesity.

Mobile, social, real-time: the ongoing revolution in the way people communicate has given rise to a new kind of epidemiology. Digital data sources, when harnessed appropriately, can provide local and timely information about disease and health dynamics in populations around the world. The rapid, unprecedented increase in the availability of relevant data from various digital sources creates considerable technical and computational challenges.

The problems targeted by preventive interventions are often complex, embedded in multiple levels of social and environmental context, and span the developmental lifespan. Despite this appreciation for multiple levels and systems of influence, prevention science has yet to apply analytic approaches that can satisfactorily address the complexities with which it is faced. In this article, we introduce a systems science approach to problem solving and methods especially equipped to handle complex relationships and their evolution over time. Progress in prevention science may be significantly enhanced by applying approaches that can examine a wide array of complex systems interactions among biology, behavior, and environment that jointly yield unique combinations of developmental risk and protective factors and outcomes. To illustrate the potential utility of a systems science approach, we present examples of current prevention research challenges, and propose how to complement traditional methods and augment research objectives by applying systems science methodologies.

Fueled by the rapid pace of discovery, humankind's ability to understand the ultimate causes of preventable common disease burdens and to identify solutions is now reaching a revolutionary tipping point. Achieving optimal health and well-being for all members of society lies as much in the understanding of the factors identified by the behavioral, social, and public health sciences as by the biological ones. Accumulating advances in mathematical modeling, informatics, imaging, sensor technology, and communication tools have stimulated several converging trends in science: an emerging understanding of epigenomic regulation; dramatic successes in achieving population health-behavior changes; and improved scientific rigor in behavioral, social, and economic sciences. Fostering stronger interdisciplinary partnerships to bring together the behavioral–social–ecologic models of multilevel “causes of the causes” and the molecular, cellular, and, ultimately, physiological bases of health and disease will facilitate breakthroughs to improve the public's health. The strategic vision of the Office of Behavioral and Social Sciences Research (OBSSR) at the National Institutes of Health (NIH) is rooted in a collaborative approach to addressing the complex and multidimensional issues that challenge the public's health. This paper describes OBSSR's four key programmatic directions (next-generation basic science, interdisciplinary research, systems science, and a problem-based focus for population impact) to illustrate how interdisciplinary and transdisciplinary perspectives can foster the vertical integration of research among biological, behavioral, social, and population levels of analysis over the lifespan and across generations. Interdisciplinary and multilevel approaches are critical both to the OBSSR's mission of integrating behavioral and social sciences more fully into the NIH scientific enterprise and to the overall NIH mission of utilizing science in the pursuit of fundamental knowledge about the nature and behavior of living systems and the application of that knowledge to extend healthy life and reduce the burdens of illness and disability.