Ross A. Hammond

Project Cerberus: Tobacco Industry Strategy to Create an Alternative to the Framework Convention on Tobacco Control

Between 1999 and 2001, British American Tobacco, Philip Morris, and Japan Tobacco International executed Project Cerberus to develop a global voluntary regulatory regime as an alternative to the Framework Convention on Tobacco Control (FCTC). They aimed to develop a global voluntary regulatory code to be overseen by an independent audit body and to focus attention on youth smoking prevention. The International Tobacco Products Marketing Standards announced in September 2001, however, did not have the independent audit body. Although the companies did not stop the FCTC, they continue to promote the International Tobacco Products Marketing Standards youth smoking prevention as an alternative to the FCTC. Public health civil society groups should help policymakers and governments understand the importance of not working with the tobacco industry.

Dynamic Interplay Among Homeostatic, Hedonic, and Cognitive Feedback Circuits Regulating Body Weight

Obesity is associated with a prolonged imbalance between energy intake and expenditure, both of which are regulated by multiple feedback processes within and across individuals. These processes constitute 3 hierarchical control systems-homeostatic, hedonic, and cognitive-with extensive interaction among them. Understanding complex eating behavior requires consideration of all 3 systems and their interactions. Existing models of these processes are widely scattered, with relatively few attempts to integrate across mechanisms. We briefly review available empirical evidence and dynamic models, discussing challenges and potential for better integration. We conclude that developing richer models of dynamic interplay among systems should be a priority in the future study of obesity and that systems science modeling offers the potential to aid in this goal.

A model of social influence on body mass index

In this paper, we develop an agent‐based model of social influence on body weight. The models assumptions are grounded in theory and evidence from physiology, social psychology, and behavioral science, and its outcomes are tested against longitudinal data from American youth. We discuss the implementation of the model, the insights it generates, and its implications for public health policy. By explicating a well‐grounded dynamic mechanism, our analysis helps clarify important dependencies for both efforts to leverage social influence for obesity intervention and efforts to interpret clustering of BMI in networks.

International trade versus public health during the FCTC negotiations, 1999-2003

Objective To examine why the Framework Convention on Tobacco Control did not include an explicit trade provision and delineate the central arguments in the debate over trade provision during the negotiations. Methods Triangulate interviews with participants in the FCTC negotiations, the FCTC negotiations documents, and tobacco industry documents. Results An explicit FCTC trade provision on relation between international trade and public health became a contentious issue during the negotiations. As a result, two conflicting positions, health-over-trade and opposition to health-over-trade emerged. Opposition to explicit trade language giving health priority was by both tobacco industry and countries that generally supported strong FCTC provisions because of concerns over ‘disguised protectionism’ and setting a precedent whereby governments could forfeit their obligations under pre-existing treaties. Owing to lack of consensus among political actors involved in the negotiations, a compromise position eliminating any mention of trade emerged, which was predicated on belief among some in the public health community that public health would prevail in future trade versus health conflicts. Conclusion The absence of an explicit FCTC trade provision was due to a political compromise rather than the impact of international trade agreements and decisions on public health and lack of consensus among health advocates. This failure to include an explicit trade provision in the FCTC suggests that the public health community should become more involved in trade and health issues at all levels of governance and press the FCTC Conference of the Parties for clarification of this critical issue.

Precision Treatment and Precision Prevention: Integrating “Below and Above the Skin”

In 2015, President Obama unveiled “a new research effort to revolutionize how we improve health and treat disease,” based on the premise that accounting for “individual differences in people’s genes, environments, and lifestyles” will improve both disease prevention and treatment.1,2 Most of the history and current application of these concepts, however, has focused on treatment over prevention. If the scientific community is not vigilant, emphasis on successful treatments for small subsets of patients may overshadow prevention efforts to improve the health of all Americans. We contend that integrating 2 paradigms of research, both of which aim to understand “what works, for whom, and under what circumstances,” can lead to a sounder balance of treatment and prevention. Advances in precision can benefit both halves of this effort and ultimately have the potential to integrate them. To date, precision medicine has focused on treating existing disease much more than preventing it in the first place; we call this precision treatment. At the risk of oversimplification, precision treatment is most concerned with finding the most efficacious and least harmful pharmaceutical treatments for avoiding highfrequency outcomes among patients with existing disease, such as relapse or death after a diagnosis of cancer. Using high-throughput technologies, precision treatment efforts typically interrogate individuals’ “below the skin” networks of metabolism, epigenetics, and genetics to guide personalized therapy.3 This approach characterizes the near-term goals of the new National Institutes of Health Precision Medicine Initiative.4 To date, precision treatment frequently emphasizes the “what” (eg, the best drug for this patient), more than the “how” (eg, delivery system reform to accommodate the increased need for genetic counseling). What we call precision prevention, on the other hand, has generally involved tailoring behavioral interventions to individuals’ characteristics. Historically, it has operated “above the skin” to overcome psychosocial barriers, emphasize achievable goals, or adapt to families’ differing economic or cultural circumstances. While precision prevention can aim to change individual behavior, it can also target “precise” groups or entire communities by modifying care delivery systems, optimizing transmission through social networks, or instituting targeted policy or macroenvironmental changes that are different from one community to the next.5 Precision prevention often emphasizes the “how” (eg, the most cost-effective implementation approach) as much as the “what” (which behaviors to target) or the “why” (the biological mechanisms that mediate prevention effectiveness). Despite these historical differences, we believe the nascent precision revolution can benefit both treatment and prevention alike. Three loci hold particular promise: mutual learning from each other’s research paradigms, sharing study designs, and transdisciplinary integration through innovative data analysis and modeling. First, taking lessons from across the “skin barrier” may increase effectiveness of both efforts. For precision treatment, this can mean invoking above-the-skin strategies for implementing and sustaining changes in practice, as is already beginning to happen. For example, a flood of ‘omics information to clinicians will require increased capacity for counseling, necessitating additional training, space, and funding—purviews of health services research. Another example is finding the best ways to ensure improving adherence to medicines, which is crucial for effectiveness and is determined by a host of psychological, economic, and social factors. For precision prevention, recognition of how powerfully biology may act as a mediator of societal-level effects transcends the skin barrier. We often think of how biological mechanisms mediate individual behaviors, for example, how maternal diet during pregnancy could affect preterm birth via changes in metabolomics. Socially patterned above-the-skin factors like stress, however, may directly embed themselves within below-theskin biology without invoking individuals’ behavior.6 Using ‘omics technologies to understand the mechanisms by which stress alters health outcomes such as preterm birth could lead to a more specific understanding of how different types of stress affect different people. This understanding could translate into more precise prevention strategies both within and outside medical care, conceivably narrowing disparities in health outcomes. A second locus revolves around sharing study designs and clinical epidemiologic principles. One of the stated promises of precision medicine is to distinguish individuals, either on prognosis or on potential response to intervention, often called prediction. This goal presents higher obstacles in precision prevention than treatment: the comparative infrequency of disease incidence in prevention renders positive predictive values relatively low for any index of personal characteristics. This is one reason why many prevention programs invoke broad environmental changes that affect large numbers of individuals rather than adopt interventions only for higher-risk people. To estimate the value of high-risk approaches, the precision prevention community must focus more on absolute than relative risks, a focus that already fits naturally in treatment paradigms. On the other hand, precision prevention has always relied on large populationbased cohorts. Now, “big cohort data” derived from medical care encounters from conception to old age, informed by judicious use of patient-empowered information from VIEWPOINT

Designing an Agent-Based Model for Childhood Obesity Interventions: A Case Study of ChildObesity180.

Complex systems modeling can provide useful insights when designing and anticipating the impact of public health interventions. We developed an agent-based, or individual-based, computation model (ABM) to aid in evaluating and refining implementation of behavior change interventions designed to increase physical activity and healthy eating and reduce unnecessary weight gain among school-aged children. The potential benefits of applying an ABM approach include estimating outcomes despite data gaps, anticipating impact among different populations or scenarios, and exploring how to expand or modify an intervention. The practical challenges inherent in implementing such an approach include data resources, data availability, and the skills and knowledge of ABM among the public health obesity intervention community. The aim of this article was to provide a step-by-step guide on how to develop an ABM to evaluate multifaceted interventions on childhood obesity prevention in multiple settings. We used data from 2 obesity prevention initiatives and public-use resources. The details and goals of the interventions, overview of the model design process, and generalizability of this approach for future interventions is discussed.

Advancing the Science of Dietary Patterns Research to Leverage a Complex Systems Approach

“D IETARY PATTERNS” REFERS TO A WAY OF conceptualizing numerous diet exposures as a multidimensional construct. Research in this area is growing and the 2015 Dietary Guidelines Advisory Committee focused on dietary patterns as the core of their conceptual model and framed their reviews, findings, and conclusions accordingly. The purpose of this commentary is to consider how approaches from complex systems science may complement existing dietary patterns methodologies and broaden the set of questions that can be addressed to yield novel insights regarding diet and health outcomes.

Designing effective and sustainable multifaceted interventions for obesity prevention and healthy communities

There is an urgency to find sustainable and scalable solutions (3) to confront and reverse the epidemic. Building on previous experience, the field is increasingly stressing the importance of 1) early childhood prevention; 2) multisector, multilevel “whole of community” approaches; 3) purposeful, sustainable, evidence-based initiative packages; 4) coordination and connections between sectors, levels, and initiatives using systems methodologies; and 5) rigorous design and evaluation procedures. Checking all 5 of these boxes in a single study remains elusive.

Toward optimal implementation of cancer prevention and control programs in public health: a study protocol on mis-implementation

BackgroundMuch of the cancer burden in the USA is preventable, through application of existing knowledge. State-level funders and public health practitioners are in ideal positions to affect programs and policies related to cancer control. Mis-implementation refers to ending effective programs and policies prematurely or continuing ineffective ones. Greater attention to mis-implementation should lead to use of effective interventions and more efficient expenditure of resources, which in the long term, will lead to more positive cancer outcomes.MethodsThis is a three-phase study that takes a comprehensive approach, leading to the elucidation of tactics for addressing mis-implementation. Phase 1: We assess the extent to which mis-implementation is occurring among state cancer control programs in public health. This initial phase will involve a survey of 800 practitioners representing all states. The programs represented will span the full continuum of cancer control, from primary prevention to survivorship. Phase 2: Using data from phase 1 to identify organizations in which mis-implementation is particularly high or low, the team will conduct eight comparative case studies to get a richer understanding of mis-implementation and to understand contextual differences. These case studies will highlight lessons learned about mis-implementation and identify hypothesized drivers. Phase 3: Agent-based modeling will be used to identify dynamic interactions between individual capacity, organizational capacity, use of evidence, funding, and external factors driving mis-implementation. The team will then translate and disseminate findings from phases 1 to 3 to practitioners and practice-related stakeholders to support the reduction of mis-implementation.DiscussionThis study is innovative and significant because it will (1) be the first to refine and further develop reliable and valid measures of mis-implementation of public health programs; (2) bring together a strong, transdisciplinary team with significant expertise in practice-based research; (3) use agent-based modeling to address cancer control implementation; and (4) use a participatory, evidence-based, stakeholder-driven approach that will identify key leverage points for addressing mis-implementation among state public health programs. This research is expected to provide replicable computational simulation models that can identify leverage points and public health system dynamics to reduce mis-implementation in cancer control and may be of interest to other health areas.