• Leadership, in the case of the committee’s systems approach to accelerating obesity prevention, is a shared responsibility across sectors and levels, and one that may not follow typical hierarchical or individual sector-based approaches. It rests with all individuals, organizations, agencies, and sectors that can influence physical activity and food environments.
• The committee did not give priority to any one recommended action or set of actions above others. Rather, leaders are called on to identify priority actions over which they have control, using systems thinking in their implementation efforts.
• A greater awareness of the potential catastrophic consequences of the high rates of obesity, together with a common understanding that individuals and groups in every sector and at every level must play a critical role in prevention, will help catalyze the systemwide implementation of the committee’s recommendations.
• Resources will be required to effectively monitor the full impact of the committee’s recommendations and determine whether progress in obesity prevention is accelerating.
• The application of quantitative systems science to the examination of complex public health problems, including obesity in particular, holds great promise and offers enormous potential benefits.
The unique perspective that a systems approach brings to the issue of obesity is highlighted at the end of the previous chapters presenting the committee’s recommendations (Chapters 5-9). For example, Chapter 7, on message environments, points out some of the important intrasector and cross-sector insights that are gained by viewing these issues through a systems lens: “On their own, any one of these actions might help accelerate progress in obesity prevention, but together, their effect would be reinforced, amplified, and maximized. A social marketing campaign on its own, without a decrease in young people’s exposure to food and beverage marketing, would be less effective. Likewise, a shift in food and beverage marketing would be more powerful when accompanied by a vigorous social marketing campaign.” Likewise, Supplemental Nutrition Assistance Program (SNAP) Education (SNAP-Ed) would be much more effective if a sustained and targeted social marketing campaign were initiated and there were significant increases in food availability and affordability for SNAP recipients.
This unique perspective also influences the committee’s views on how leadership, prioritization, and assessment should be handled. A theme that recurs throughout this report is that each of the committee’s single recommendations, strategies, and potential actions has the potential to accelerate progress in obesity prevention, but that it is also important to view them as a whole system comprising the five critical areas depicted in Figure 10-1. As illustrated in the figure, this chapter addresses the important issues involved in the implementation of the committee’s recommendations for accelerating progress in obesity prevention, using a simplified systems perspective, by answering three important questions: How should leadership be identified, defined, and exercised in response to the systems-oriented recommendations presented in this report? How can the systems thinking represented in this report guide the way a leader should approach implementation of the recommendations and the associated strategies and potential actions? What are the priorities on which leaders should act within and among the five interacting critical areas?
This chapter also identifies a set of indicators—complementary to the more specific indicators in Chapters 5-9—that the committee recommends be used to assess progress in the implementation of its recommendations as a whole, an important step in effectively monitoring implementation and impact. The chapter concludes with suggestions for future systems research in obesity prevention.
The issue of leadership is dealt with throughout this report. In Chapters 5-9, the potential and obvious leaders for each of the committee’s recommendations are identified and called upon to take immediate action to accelerate progress in obesity prevention. These are typically the individuals, agencies, organizations, or sectors that are traditionally seen as having the knowledge, control, and responsibility for the particular environments, policies, and practices that must change. For example, the recommendations, strategies, and potential actions in Chapter 6 (on food and beverage environments) call on schools; the business community/private sector; nongovernmental organizations; federal, state, and local governments; the food and beverage industry; and health care providers to take leadership on specific actions.
The report also introduces new ways to think about leadership. For example, Chapter 1 identifies and calls on another set of leaders—individuals, families, communities, and the larger society—for engagement, involvement, and action at multiple levels, pointing out that these levels are interdependent, and all are necessary to achieve impact. Their engagement can lead to, and is a prerequisite for, the exercise of leadership at these different levels. The initial discussion in Chapter 1 also highlights the importance of taking collaborative approaches, involving those affected by an issue in addressing the issues that affect them, and reducing disparities in racial/ethnic minority and low-income communities through “robust and long-term community engagement and civic participation among these disadvantaged populations.” In addition, the chapter deals with the issue of responsibility, which is an important component of leadership, suggesting a new way to view personal responsibility—as a collective responsibility of the public and private sectors, and all those involved in each sector, to act to improve physical activity and nutrition environments. Chapter 3 includes some insights from systems thinking into new ways in which leaders can be identified or act, including the concepts of “facilitative leadership,” which is “not necessarily located at any particular level or organization and is likely to encourage bottom-up solutions and activities”; “local creativity,” which involves “mechanisms for local people to design locally relevant activities and solutions” and not “rigid requirements for activities imposed from outside the area”; and the possibility of “the visibility of obesity as an explicit policy goal or concern for nonhealth organizations.…”
A major premise that underlies all the points made above is that leadership in the case of the committee’s systems approach to accelerating obesity prevention is a shared responsibility across sectors and levels, and one that may not follow typical hierarchical or individual sector-based approaches. In the committee’s view, the
problem of obesity is so complex and so embedded in Americans’ everyday lives, culture, and physical environments that only integrated, systemic, cross-sector approaches to the problem will succeed. The committee’s systems approach to accelerating progress in obesity prevention calls on all individuals, organizations, agencies, and sectors that do or can influence the environments that control physical activity and food consumption to assess and begin to act on their important roles as leaders in prevention. Some traditional leaders may turn away from their logical or designated roles in helping to solve this problem, but other organizations that have previously been concerned with obesity prevention may increase their efforts or broaden the scope of their activities, and many other less likely, unexpected, or less well-known candidates for leadership may step forward to address issues in sectors where they are stakeholders or have influence. For example, the broad articulation of the committee’s system of recommendations will support ongoing organizational activity by groups such as county-level Cooperative Extension agencies that have nutrition expertise and strong community ties, while also encouraging many more leaders to identify themselves as important and willing actors, such as local banks that invest in community development or small businesses and faith-based organizations that provide services to their communities and congregations.
Leaders who are identified and called upon by this report to act and who seek to carry out their designated roles, or leaders who self-identify—whether a group of mothers of young children concerned about the foods available in their community or an environmental specialist who sees the connections between her work on clean air and the importance of making physical activity a routine part of life—will share the moment of saying to themselves, “I can do something about this, and I want to play a role.” From that point on, thinking about their role with a systems lens can guide their actions in new directions. They may consider various sectors, recommendations, strategies, and actions and find themselves on the systems “map” (as presented in Appendix B), figuratively or literally. However, they will act with new foresight—examining how what they plan to do will intersect with other actions that may be taken or are being taken already in various sectors.
They will examine actions by others, in their critical area or in the other four critical areas that are part of the whole system, that will help accelerate what they are attempting to accomplish. They may also see potential actions by others that, if taken, could advance them more rapidly toward their goals. This in turn may
lead them not only to implement actions they have already identified, but also to encourage others, sometimes in different sectors, to act in new ways that support their own efforts.
In addition, these leaders may identify ongoing actions that work against what they are attempting to accomplish. This may lead them to change their strategies or work toward removal of the barriers in their or other sectors. They will also want to make sure that what they are planning to do does not have any obvious adverse consequences, and if there are additional positive consequences (side benefits) of what they are attempting, they will want to let others know about them in order to enlist additional support within or across sectors.
Finally, these leaders will want to examine their efforts over time with an eye to what others in their or other sectors are doing as it relates to their goals and how things may be changing overall. They also may want to communicate their actions, goals, and views to others who are working in their or other sectors to implement related changes. Examination of current or potential actions of others within the system and the development of creative, coordinated intra- or cross-sector relationships can lead to more effective efforts and greater opportunities for success. Some leaders, because of their roles, capacities, and broader influence, will choose to focus on an examination of what is happening in the whole system, within and across sectors and critical areas, and will act to understand and influence changes throughout the system.
Implicit in the preceding discussion of leadership and implementation is the assumption that individual leaders will determine which recommendations, strategies, and potential actions are their priorities or that those who choose to follow their lead will play a major role in determining these priorities. These leaders will likely start from where they have the most influence and likelihood of success, a decision that will result from a unique assessment of a range of variables. This follows naturally from the committee’s systems perspective and definition and identification of leaders as described above, and from its approach to selecting recommendations, strategies, and potential actions as laid out in Chapter 4. The committee selected five major recommendations among hundreds of possibilities, with associated strategies and potential actions, for accelerating obesity prevention in the next decade. These are the committee’s priorities for action. Beyond that prioritization, the committee did not go further, as it saw the implementation (or continuing implementation) of the entire system of recommendations, to the greatest extent
possible, as the overarching priority. The committee did not give priority to any action or set of actions above any others, but rather envisioned leaders within sectors, and others, stepping up to implement different aspects of the system.
This report describes the public health crisis of obesity in stark terms. It points out that almost one-third of children and two-thirds of adults in the United States are overweight or obese. In certain demographic groups, rates reach even higher levels. There are devastating health and social consequences for individuals—the great potential for illness, disability, and early death; social ostracism; discrimination in employment and income; depression; and an overall poor quality of life for many millions. Some estimate that one-third of all children born today (and one-half of Latino and black children) will develop type 2 diabetes in their lifetime, and that obesity may lead to a generation with a shorter life span than that of their parents.
As this report points out, the estimated cost of obesity-related illness based on data from the Medical Expenditure Panel Survey for 2000-2005 is $190.2 billion annually (in 2005 dollars), which represents 20.6 percent of annual health care spending in the United States (Cawley and Meyerhoefer, 2011). The U.S. economy already struggles today to cope with health care spending; this struggle will grow progressively more difficult as today’s obese children mature.
Because of its views on leadership in accelerating obesity prevention, where that leadership resides, and how it is identified, the committee does not name or recommend one agent, leader, or “commission” to catalyze or lead the implementation of its system of recommendations for obesity prevention. Rather, it sees potential for many leaders across sectors and levels, from individuals working for improvements in physical activity at home and in their communities to federal agencies acting to prevent the negative effects of marketing on children’s risk of obesity. The committee sees the primary catalyst for activation of its system of recommendations as a heightened awareness of the potential catastrophic consequences of the high rates of obesity in the United States for quality of life and the national budget, and a common understanding of the critical role that must be played by individuals in every sector and at every level.
The committee also sees the issue of funding the numerous changes that may be involved in implementing its recommendations as related to its concepts of motivator and catalyst and to the potential consequences for funding of taking a systems perspective. Experience in the politics of democracy shows that if an issue is
truly understood as potentially catastrophic by citizens and their leaders, calls and support for change will emerge, and resources to engage in the battle will become more available. In addition, leaders will emerge at many levels, and their existing assets often will be brought into action or redeployed for new actions. Taking a systems perspective can help identify and open up new resources for funding from unexpected sources, and new assets that can support the cost of change can be discovered that would not otherwise be apparent. In addition, actions within a system can lead to alliances with individuals and sectors engaged in efforts that contribute significantly to obesity prevention but whose focus is related to another aspect of health or some other social outcome. The resources that can flow from these alliances have the potential to sustain obesity prevention efforts.
Once implemented, the recommendations, strategies, and actions proposed in this report will be even more useful if they are evaluated to determine their individual and collective impact. While the recommendations included herein are based on the best evidence available to the committee as it prepared this report, new evidence will emerge and new evaluation research will be needed to fully examine the impact of the committee’s individual and collective recommendations. However, such research will not happen without a sustained commitment on the part of decision makers to providing the resources necessary to support the work of monitoring the extent to which progress in obesity prevention is truly accelerating, as well as the impact of individual recommendations and the system of recommendations included in this report.
Using the framework developed in Chapter 4, the committee identified overarching (or system-level) indicators that focus on tracking progress toward reducing the incidence and prevalence of obesity and overweight in the United States. These indicators are intended for use in evaluating progress toward the adoption of the full system of strategies and actions described in Chapters 5 through 9. The committee also identified a foundational indicator focused on the broader dynamics of accelerating progress in obesity prevention, encompassing actions farther upstream from obesity prevention that are important for the successful implementation of all the recommended strategies and actions.
Notably, throughout the process of identifying indicators of progress, it became apparent to the committee that in many cases, national data sources do not yet exist for many of the proposed indicators. This is clearly an area of need going forward. More work is required to develop systems with which to monitor
progress on the recommendations and strategies included in this report. Clearly not all of the systems for monitoring progress will be based on federally funded data sources. Rather, the committee envisions the need for a partnership among federal agencies, state agencies, foundation sources, and commercial sources, among others, to develop the systems necessary to monitor progress on the implementation of the committee’s recommendations.
Indicators for Assessing Progress in Obesity Prevention with a Systems Perspective
• Reduction in the proportion of adults who are obese.
Source for measurement: NHANES
• Reduction in the proportion of adults who are overweight.
Source for measurement: NHANES
• Reduction in the proportion of children and adolescents who are considered obese.
Source for measurement: NHANES
• Reduction in the proportion of children and adolescents who are considered overweight.
Source for measurement: NHANES
• Increase in the proportion of young children (aged 2-5) that are of normal weight status.
Source for measurement: PNSS
• Increase in the proportion of adults who meet current federal physical activity guidelines.
Source for measurement: NHIS
• Increase in the proportion of children and adolescents who meet current federal physical activity guidelines.
Sources for measurement: YRBS, NYPAANS (for adolescents); source needed to measure proportion of children who meet current federal Physical Activity Guidelines
• Increase in engagement, communication, and leadership among all sectors to increase the development, implementation, and coordination of common messages, processes, and strategies.
Source needed for measurement of indicator.
NOTE: NHANES = National Health and Nutrition Examination Survey; NHIS = National Health Interview Survey; NYPAANS = National Youth Physical Activity and Nutrition Survey; PNSS = Pediatric Nutrition Surveillance System; YRBS = Youth Risk Behavior Survey.
As noted throughout the report and in Appendix B, a systems perspective consistently guided the committee’s work, from the development of its vision to the formulation of recommendations, strategies, and actions with the greatest potential to accelerate progress in obesity prevention. However, a systems approach can provide additional opportunities for research and decision making. The committee’s use of a systems perspective in viewing solutions to preventing obesity presents an important opportunity to create a research framework that takes this approach into account. This section offers a short discussion of quantitative systems-science methodologies that can be used to further test and refine the committee’s system of recommendations and in turn improve future decision making on this dynamic, complex problem. As described in Chapter 4 (and presented in further detail in Appendix B), the committee’s systems map serves many purposes, providing important information both to the committee and to readers of this report. In addition, it could in the future serve as a platform for the construction of more quantitative dynamic models. This type of dynamic systems model would enable the conduct of policy simulations exploring the impact over time of a sys-
tem of recommended strategies and the impact of the five critical areas in which action is needed on each other and on key outcomes of interest. Systems mapping often is an important prerequisite for construction of such a quantitative model by researchers.
Complex problems, such as obesity, typically have been approached using correlation-based analytic methods (e.g., regression). These methods are useful for identifying linear relationships, but are limited because of their inability to establish and test a web of interrelated causal relationships. While correlation-based analytic methods can be valuable in providing detailed information about various aspects of a problem, used alone they can be insufficient for understanding problems that are driven by interaction among a large number of factors. Moreover, these conventional methods give limited insight into the mechanisms that underlie observed relationships (Auchincloss and Diez-Roux, 2008; NIH, 2011b).
Systems-science quantitative methodologies enable investigators to examine the dynamic interrelationships among variables at multiple levels of analysis (e.g., from individuals to society) simultaneously, often taking into account causal feedback processes among variables while also studying impacts on the behavior of the system as a whole over time (Midgely, 2003). Such models that utilize data (real or simulated) can incorporate knowledge about individual decision making and biological effects as well as broader flows of information or distributions of effect between factors to take into account the complex “real world” of interest (Hammond, 2009). Systems-science quantitative modeling can even yield policy and scientific insights when a randomized experiment is impractical, expensive, or unethical. Examples of systems-science methodologies and their uses are provided in Box 10-1.
Many systems modeling methods are not new and indeed are now used routinely in such fields as corporate management, economics, engineering, physics, energy, ecology, and biology precisely because these methods add value relative to alternative techniques or unaided decision making (NIH, 2011b). As appreciation for the complexity of many problems in the public health sphere has grown, there have recently been a number of calls to use systems science to examine public health problems (Homer and Hirsch, 2006; Leischow et al., 2008; Mabry et al., 2010; Madon et al., 2007; Milstein et al., 2007), including obesity in particular (Auchincloss and Diez-Roux, 2008; Hammond, 2009; Huang and Glass, 2008; NIH, 2011a).
Examples of Systems-Science Methodologies and
Specific examples of systems-science methodologies include
• systems dynamics modeling (Homer and Hirsch, 2006; Sterman, 2006);
• agent-based modeling (Axelrod, 2006; Epstein, 2006; Miller and Page, 2007);
• discrete event simulation (Banks et al., 2010);
• network analysis (Scott, 2000; Wasserman and Faust, 1994);
• dynamic microsimulation modeling (Mitton et al., 2000); and
• Markov modeling (Sonnenberg and Beck, 1993).
These techniques, among others, are particularly well suited for
• understanding connections between a system’s structure and its behavior over time;
• anticipating a range of plausible futures based on explicit scenarios for action or inaction in certain areas;
• identifying unintended or counterintuitive consequences of interventions;
• evaluating both the short- and long-term effects of policy options; and
• guiding investments in new research or data collection to address critical information needs.
Auchincloss, A. H., and A. V. Diez-Roux. 2008. A new tool for epidemiology: The usefulness of dynamic-agent models in understanding place effects on health. American Journal of Epidemiology 168(1):1-8.
Axelrod, R. 2006. Agent-based modeling as a bridge between disciplines. In Handbook of computational economics. Vol. 2, edited by L. Tesfatsion and K. L. Judd. Amsterdam (NL): North-Holland. Pp. 1565-1584.
Banks, J., J. S. Carson II, B. L. Nelson, and D. M. Nicol. 2010. Discrete-event system simulation. 5th ed. Upper Saddle River, NJ: Pearson Prentice Hall.
Cawley, J., and C. Meyerhoefer. 2011. The medical care costs of obesity: An instrumental variables approach. Journal of Health Economics 31(1):219-230.
Epstein, J. M. 2006. Remarks on the foundations of agent-based generative social science. In Handbook of computational economics. Vol. 2, edited by L. Tesfatsion and K. L. Judd. Amsterdam (NL): North-Holland. Pp. 1585-1604.
Hammond, R. A. 2009. Complex systems modeling for obesity research. Preventing Chronic Disease 6(3):A97.
Homer, J. B., and G. B. Hirsch. 2006. System dynamics modeling for public health: Background and opportunities. American Journal of Public Health 96(3):452-458.
Huang, T. T., and T. A. Glass. 2008. Transforming research strategies for understanding and preventing obesity. Journal of the American Medical Association 300(15):1811-1813.
Leischow, S. J., A. Best, W. M. Trochim, P. I. Clark, R. S. Gallagher, S. E. Marcus, and E. Matthews. 2008. Systems thinking to improve the public’s health. American Journal of Preventive Medicine 35(Suppl. 2):S196-S203.
Mabry, P. L., S. E. Marcus, P. I. Clark, S. J. Leischow, and D. Mendez. 2010. Systems science: A revolution in public health policy research. American Journal of Public Health 100(7):1161-1163.
Madon, T., K. J. Hofman, L. Kupfer, and R. I. Glass. 2007. Public health. Implementation science. Science 318(5857):1728-1729.
Midgely, G. 2003. Systems thinking: Critical systems thinking and systemic perspectives on ethics, power and pluralism. Vol. 4. Thousand Oaks, CA: Sage Publications.
Miller, J. H., and S. E. Page. 2007. Complex adaptive systems: An introduction to computational models of social life. Princeton, NJ: Princeton University Press.
Milstein, B., A. Jones, J. B. Homer, D. Murphy, J. Essien, and D. Seville. 2007. Charting plausible futures for diabetes prevalence in the United States: A role for system dynamics simulation modeling. Preventing Chronic Disease 4(3):A52.
Mitton, L., H. Sutherland, and M. J. Weeks. 2000. Microsimulation modelling for policy analysis: Challenges and innovations. New York: Cambridge University Press.
NIH (National Institutes of Health). 2011a. Strategic plan for NIH obesity research: A report of the NIH Obesity Research Task Force. NIH publication no. 11-5493. Washington, DC: U.S. Department of Health and Human Services.
NIH. 2011b. Systems science. http://obssr.od.nih.gov/scientific_areas/methodology/systems_science/index.aspx (accessed November 18, 2011).
Scott, J. 2000. Social network analysis: A handbook. 2nd ed. London: Sage Publications.
Sonnenberg, F. A., and J. R. Beck. 1993. Markov models in medical decision making: A practical guide. Medical Decision Making 13(4):322-338.
Sterman, J. D. 2006. Learning from evidence in a complex world. American Journal of Public Health 96(3):505-514.
Wasserman, S., and K. Faust. 1994. Social network analysis: Methods and applications New York: Cambridge University Press.