The Urban Environment and Cardiometabolic Health.

Urban environments contribute substantially to the rising burden of cardiometabolic diseases worldwide. Cities are complex adaptive systems that continually exchange resources, shaping exposures relevant to human health such as air pollution, noise, and chemical exposures. In addition, urban infrastructure and provisioning systems influence multiple domains of health risk, including behaviors, psychological stress, pollution, and nutrition through various pathways (eg, physical inactivity, air pollution, noise, heat stress, food systems, the availability of green space, and contaminant exposures). Beyond cardiometabolic health, city design may also affect climate change through energy and material consumption that share many of the same drivers with cardiometabolic diseases. Integrated spatial planning focusing on developing sustainable compact cities could simultaneously create heart-healthy and environmentally healthy city designs. This article reviews current evidence on the associations between the urban exposome (totality of exposures a person experiences, including environmental, occupational, lifestyle, social, and psychological factors) and cardiometabolic diseases within a systems science framework, and examines urban planning principles (eg, connectivity, density, diversity of land use, destination accessibility, and distance to transit). We highlight critical knowledge gaps regarding built-environment feature thresholds for optimizing cardiometabolic health outcomes. Last, we discuss emerging models and metrics to align urban development with the dual goals of mitigating cardiometabolic diseases while reducing climate change through cross-sector collaboration, governance, and community engagement. This review demonstrates that cities represent crucial settings for implementing policies and interventions to simultaneously tackle the global epidemics of cardiovascular disease and climate change.

Making the invisible visible: Using a qualitative system dynamics model to map disparities in cumulative environmental stressors and children's neurodevelopment.

BACKGROUND: The combined effects of multiple environmental toxicants and social stressor exposures are widely recognized as important public health problems, likely contributing to health inequities. However, US policy makers at state and federal levels typically focus on one stressor exposure at a time and have failed to develop comprehensive strategies to reduce multiple co-occurring exposures, mitigate cumulative risks and prevent harm. This research aimed to move from considering disparate environmental stressors in isolation to mapping the links between environmental, economic, social and health outcomes as a dynamic complex system using children's exposure to neurodevelopmental toxicants as an illustrative example. Such a model can be used to support a broad range of child developmental and environmental health policy stakeholders in improving their understanding of cumulative effects of multiple chemical, physical, biological and social environmental stressors as a complex system through a collaborative learning process. METHODS: We used system dynamics (SD) group model building to develop a qualitative causal theory linking multiple interacting streams of social stressors and environmental neurotoxicants impacting children's neurodevelopment. A 2 1/2-day interactive system dynamics workshop involving experts across multiple disciplines was convened to develop the model followed by qualitative survey on system insights. RESULTS: The SD causal map covered seven interconnected themes: environmental exposures, social environment, health status, education, employment, housing and advocacy. Potential high leverage intervention points for reducing disparities in children's cumulative neurotoxicant exposures and effects were identified. Workshop participants developed deeper level of understanding about the complexity of cumulative environmental health risks, increased their agreement about underlying causes, and enhanced their capabilities for integrating diverse forms of knowledge about the complex multi-level problem of cumulative chemical and non-chemical exposures. CONCLUSION: Group model building using SD can lead to important insights to into the sociological, policy, and institutional mechanisms through which disparities in cumulative impacts are transmitted, resisted, and understood.

Community coalition efforts to prevent childhood obesity: two-year results of the Shape Up Under 5 study.

BACKGROUND: Cross-sector collaborations and coalitions are promising approaches for childhood obesity prevention, yet there is little empirical evidence about how they affect change. We hypothesized that changes in knowledge of, and engagement with, childhood obesity prevention among coalition members can diffuse through social networks to influence policies, systems, and environments. METHODS: We studied a community coalition (N = 16, Shape Up Under 5 "SUU5 Committee") focused on early childhood obesity prevention in Somerville, MA from 2015-17. Knowledge, engagement, and social network data were collected from Committee members and their network contacts (n = 193) at five timepoints over two years. Policy, systems, and environment data were collected from the SUU5 Committee. Data were collected via the validated COMPACT Stakeholder-driven Community Diffusion survey and analyzed using regression models and social network analysis. RESULTS: Over 2 years, knowledge of (p = 0.0002), and engagement with (p = 0.03), childhood obesity prevention increased significantly among the SUU5 Committee. Knowledge increased among the Committee's social network (p = 0.001). Significant changes in policies, systems, and environments that support childhood obesity prevention were seen from baseline to 24 months (p = 0.003). CONCLUSION: SUU5 had positive effects on "upstream" drivers of early childhood obesity by increasing knowledge and engagement. These changes partially diffused through networks and may have changed "midstream" community policies, systems, and environments.

System dynamics modelling to engage community stakeholders in addressing water and sugar sweetened beverage consumption.

BACKGROUND: Participatory approaches to develop community-based system dynamics models to tackle complexity are promising, but research is needed in how simulation models can be developed with community stakeholders to yield significant system insights. This study presents the results of a community-based system dynamics modelling process to increase water consumption and decrease sugar sweetened beverage consumption in Portland, Victoria, a regional town in Australia. METHODS: A series of group model building workshops with 11 community stakeholders addressing the topic of water and sugar sweetened beverage consumption was conducted in Portland. A simulating system dynamics model was built with stakeholders to inform action planning. RESULTS: A system dynamics model was created to provide insight into water and sugar sweetened beverage consumption in Portland. The model included six feedback loops describing the causal effects of sugar sweetened beverage consumption habits and norms, water taste, water consumption norms, public water availability, and public health benefits. For example, the sugar sweetened beverage consumption norm loop modelled how people overestimating others' consumption may motivate an increase in their own consumption, feeding back and further amplifying an increase in sugar sweetened beverage consumption. The model contributed to the foundation of a strong partnership to improve the taste of water and educate the public on water consumption. CONCLUSIONS: Engaging stakeholders in system dynamics modelling about water and sugar sweetened beverage consumption increased engagement and collaboration to address the problem among community stakeholders.

Suicide attempts during adolescence: Testing the system dynamics of the interpersonal theory of suicide.

INTRODUCTION: Despite increased efforts to prevent suicide, attempts to die by suicide are rising amongst youth in the United States. Testing causal theories that depict suicide attempts from an adolescent development perspective could bolster prevention and intervention efforts. This study using system dynamics modeling to appraise whether a prevalent theory of suicide, the Interpersonal Theory of Suicide, predicts suicide attempts across adolescence. METHODS: A system dynamics computational simulation model was conceptualized based on the Interpersonal Theory of Suicide, as described by Joiner and Van Orden et al. This model was parameterized with representative longitudinal data on adolescents in the United States who attempted suicide across four waves from the National Longitudinal Survey of Adolescent and Adult Health. RESULTS: Though able to predict exponential growth in suicide attempts for early adolescents, the Interpersonal Theory of Suicide, when specified as a dynamic theory, did not adequately predict the nonlinear changes in suicide attempts from adolescence into adulthood. The theory was amended with potential feedback loops from literature and tested for fit. CONCLUSIONS: The study builds on a field of emerging views that suicide dynamics should be tested to account for nonlinear feedback effects. Results suggest that the Interpersonal Theory of Suicide should be amended to include the effect of interventions after an attempt and the dynamic developmental processes during adolescence that affect suicide behaviors over time.

Implementing Group Model Building With the Shape Up Under 5 Community Committee Working to Prevent Early Childhood Obesity in Somerville, Massachusetts.

OBJECTIVE: To describe our process of using group model building (GMB) with the Shape Up Under 5 Committee; measure the effects on Committee members; and describe the community-wide health messaging campaign that resulted from the process. DESIGN: Pilot study. SETTING: Somerville, Massachusetts. PARTICIPANTS: Members of the Shape Up Under 5 Committee, a multisector group of professionals. INTERVENTION: Research team convened the Committee and facilitated GMB from October 2015 to June 2017. MAIN OUTCOME MEASURES: Boundary objects produced during GMB activities; committee members' perspectives on early childhood obesity in their community; and Committee members' knowledge, engagement, and trust at the conclusion of each meeting. RESULTS: Working together using GMB activities and with support from the research team, the Committee created a community-wide campaign that provided evidence-based messages to reach an entire city that emphasized diversity and reaching immigrants and community members who spoke languages other than English. More than 80% of Committee members reported changes in their perspectives related to early childhood obesity at the conclusion of the pilot test. Six perspective shift themes emerged from interviews and open-ended survey items: exposure to new perspectives about challenges community members face; increased awareness of others working on similar issues; increased knowledge about early childhood obesity; seeing value in creating a space to work across sectors; appreciating complexity and linkages between early childhood obesity prevention and other community issues; and how participation in committee influences members' priorities in their own work. Knowledge of and engagement with early childhood obesity prevention varied at the conclusion of each meeting, as did increases in trust among Committee members. CONCLUSION: Group model building is a promising approach to support multisector groups working to address early childhood obesity in their community. Meeting activities may have had differential impacts on members' knowledge of and engagement with early childhood obesity.

Using Community-Based System Dynamics to Address Structural Racism in Community Health Improvement.

CONTEXT: Structural racism is a profound determinant of health resulting in pervasive health inequities for people of color. Despite the recognition of structural racism as a complex, dynamic system, we lack a shared vision of the system that would enable identification of solutions for equitable systems transformation. POLICY: Through a public health-led community health improvement planning process, a cross-sector consortium implemented community-based system dynamics to provide a systems science lens to guide efforts to eliminate structural racism. IMPLEMENTATION: In group model building sessions involving diverse stakeholders, community-based system dynamics was used to bring together cross-sector stakeholders to create causal loop diagrams of the system of structural racism. Participants identified potential leverage points for actionable focus to eliminate structural racism. EVALUATION: Causal loop diagrams of structural racism generated through group model building demonstrate complex dynamics in the areas of criminal justice, education and economic opportunity, health and health care, quality of life, racial trauma and healing, and a promising system transformative solution through perspective transformation. DISCUSSION: Community-based system dynamics, employed in the context of local community health improvement planning, engages stakeholders in systems thinking through sharing lived experience to create system maps of structural racism and identify leverage points and transportable solutions that foster health equity. These informal maps serve as the foundation for formal computer simulation models that will guide systemic action on high-yield, community-driven solutions to eliminate structural racism.

Application of systems dynamics and group model building to identify barriers and facilitators to acute care delivery in a resource limited setting.

BACKGROUND: Group model building (GMB) is a method to facilitate shared understanding of structures and relationships that determine system behaviors. This project aimed to determine the feasibility of GMB in a resource-limited setting and to use GMB to describe key barriers and facilitators to effective acute care delivery at a tertiary care hospital in Malawi. METHODS: Over 1 week, trained facilitators led three GMB sessions with two groups of healthcare providers to facilitate shared understanding of structures and relationships that determine system behaviors. One group aimed to identify factors that impact patient flow in the paediatric special care ward. The other aimed to identify factors impacting delivery of high-quality care in the paediatric accident and emergency room. Synthesized causal maps of factors influencing patient care were generated, revised, and qualitatively analyzed. RESULTS: Causal maps identified patient condition as the central modifier of acute care delivery. Severe illness and high volume of patients were identified as creating system strain in several domains: (1) physical space, (2) resource needs and utilization, (3) staff capabilities and (4) quality improvement. Stress in these domains results in worsening patient condition and perpetuating negative reinforcing feedback loops. Balancing factors inherent to the current system included (1) parental engagement, (2) provider resilience, (3) ease of communication and (4) patient death. Perceived strengths of the GMB process were representation of diverse stakeholder viewpoints and complex system synthesis in a visual causal pathway, the process inclusivity, development of shared understanding, new idea generation and momentum building. Challenges identified included time required for completion and potential for participant selection bias. CONCLUSIONS: GMB facilitated creation of a shared mental model, as a first step in optimizing acute care delivery in a paediatric facility in this resource-limited setting.

Solving Homelessness from a Complex Systems Perspective: Insights for Prevention Responses.

Homelessness represents an enduring public health threat facing communities across the developed world. Children, families, and marginalized adults face life course implications of housing insecurity, while communities struggle to address the extensive array of needs within heterogeneous homeless populations. Trends in homelessness remain stubbornly high despite policy initiatives to end homelessness. A complex systems perspective provides insights into the dynamics underlying coordinated responses to homelessness. A constant demand for housing assistance strains service delivery, while prevention efforts remain inconsistently implemented in most countries. Feedback processes challenge efficient service delivery. A system dynamics model tests assumptions of policy interventions for ending homelessness. Simulations suggest that prevention provides a leverage point within the system; small efficiencies in keeping people housed yield disproportionately large reductions in homelessness. A need exists for policies that ensure reliable delivery of coordinated prevention efforts. A complex systems approach identifies capacities and constraints for sustainably solving homelessness.

Housing and Child Welfare: Emerging Evidence and Implications for Scaling up Services.

Inadequate housing threatens family stability in communities across the United States. This study reviews emerging evidence on housing interventions in the context of scale-up for the child welfare system. In child welfare, scale-up refers to the extent to which fully implemented interventions sustainably alleviate family separations associated with housing instability. It incorporates multiple aspects beyond traditional measures of effectiveness including costs, potential reach, local capacities for implementation, and fit within broader social services. The framework further encompasses everyday circumstances faced by service providers, program administrators, and policymakers who allocate resources under conditions of scarcity and uncertainty. The review of current housing interventions reveals a number of systemic constraints for scale-up in child welfare. Reliance on rental assistance programs limits capacity to address demand, while current practices that target the most vulnerable families may inadvertently diminish effectiveness of the intervention and increase overall demand. Alternative approaches that focus on homelessness prevention and early intervention must be tested in conjunction with community initiatives to increase accessibility of affordable housing. By examining system performance over time, the scalability framework provides an opportunity for more efficient coordination of housing services within and outside of the child welfare system.

A participatory model of the paradox of primary care.

PURPOSE: The paradox of primary care is the observation that primary care is associated with apparently low levels of evidence-based care for individual diseases, but systems based on primary care have healthier populations, use fewer resources, and have less health inequality. The purpose of this article is to explore, from a complex systems perspective, mechanisms that might account for the effects of primary care beyond disease-specific care. METHODS: In an 8-session, participatory group model-building process, patient, caregiver, and primary care clinician community stakeholders worked with academic investigators to develop and refine an agent-based computer simulation model to test hypotheses about mechanisms by which features of primary care could affect health and health equity. RESULTS: In the resulting model, patients are at risk for acute illness, acute life-changing illness, chronic illness, and mental illness. Patients have changeable health behaviors and care-seeking tendencies that relate to their living in advantaged or disadvantaged neighborhoods. There are 2 types of care available to patients: primary and specialty. Primary care in the model is less effective than specialty care in treating single diseases, but it has the ability to treat multiple diseases at once. Primary care also can provide disease prevention visits, help patients improve their health behaviors, refer to specialty care, and develop relationships with patients that cause them to lower their threshold for seeking care. In a model run with primary care features turned off, primary care patients have poorer health. In a model run with all primary care features turned on, their conjoint effect leads to better population health for patients who seek primary care, with the primary care effect being particularly pronounced for patients who are disadvantaged and patients with multiple chronic conditions. Primary care leads to more total health care visits that are due to more disease prevention visits, but there are reduced illness visits among people in disadvantaged neighborhoods. Supplemental appendices provide a working version of the model and worksheets that allow readers to run their own experiments that vary model parameters. CONCLUSION: This simulation model provides insights into possible mechanisms for the paradox of primary care and shows how participatory group model building can be used to evaluate hypotheses about the behavior of such complex systems as primary health care and population health.

Systems thinking in 49 communities related to healthy eating, active living, and childhood obesity.

BACKGROUND: Community partnerships to promote healthy eating and active living in order to prevent childhood obesity face a number of challenges. Systems science tools combined with group model-building techniques offer promising methods that use transdisciplinary team-based approaches to improve understanding of the complexity of the obesity epidemic. This article presents evaluation methods and findings from 49 Healthy Kids, Healthy Communities sites funded to implement policy, system, and environmental changes from 2008 to 2014. METHODS: Through half-day group model-building sessions conducted as part of evaluation site visits to each community between 2010 and 2013, a total of 50 causal loop diagrams were produced for 49 communities (1 community had 2 causal loop diagrams representing different geographic regions). The analysis focused on the following evaluation questions: (1) What were the most prominent variables in the causal loop diagrams across communities? (2) What were the major feedback structures across communities? (3) What implications from the synthesized causal loop diagram can be translated to policy makers, practitioners, evaluators, funders, and other community representatives? RESULTS: A total of 590 individuals participated with an average of 12 participants per session. Participants' causal loop diagrams included a total of 227 unique variables in the following major subsystems: healthy eating policies and environments, active living policies and environments, health and health behaviors, partnership and community capacity, and social determinants. In a synthesized causal loop diagram representing variables identified by at least 20% of the communities, many feedback structures emerged and several themes are highlighted with respect to implications for policy and practice as well as assessment and evaluation. CONCLUSIONS: The application of systems thinking tools combined with group model-building techniques creates opportunities to define and characterize complex systems in a manner that draws on the authentic voice of residents and community partners.

Behavior-over-time graphs: assessing perceived trends in healthy eating and active living environments and behaviors across 49 communities.

CONTEXT: In the evaluation of the Healthy Kids, Healthy Communities initiative, investigators implemented Group Model Building (GMB) to promote systems thinking at the community level. As part of the GMB sessions held in each community partnership, participants created behavior-over-time graphs (BOTGs) to characterize their perceptions of changes over time related to policies, environments, collaborations, and social determinants in their community related to healthy eating, active living, and childhood obesity. OBJECTIVE: To describe the process of coding BOTGs and their trends. DESIGN: Descriptive study of trends among BOTGs from 11 domains (eg, active living environments, social determinants of health, funding) and relevant categories and subcategories based on the graphed variables. In addition, BOTGs were distinguished by whether the variables were positively (eg, access to healthy foods) or negatively (eg, screen time) associated with health. SETTING: The GMB sessions were held in 49 community partnerships across the United States. PARTICIPANTS: Participants in the GMB sessions (n = 590; n = 5-21 per session) included key individuals engaged in or impacted by the policy, system, or environmental changes occurring in the community. MAIN OUTCOME MEASURES: Thirty codes were developed to describe the direction (increasing, decreasing, stable) and shape (linear, reinforcing, balancing, or oscillating) of trends from 1660 graphs. RESULTS: The patterns of trends varied by domain. For example, among variables positively associated with health, the prevalence of reinforcing increasing trends was highest for active living and healthy eating environments (37.4% and 29.3%, respectively), partnership and community capacity (38.8%), and policies (30.2%). Examination of trends of specific variables suggested both convergence (eg, for cost of healthy foods) and divergence (eg, for farmers' markets) of trends across partnerships. CONCLUSIONS: Behavior-over-time graphs provide a unique data source for understanding community-level trends and, when combined with causal maps and computer modeling, can yield insights about prevention strategies to address childhood obesity.

A novel system dynamics model of female obesity and fertility.

OBJECTIVES: Our objective was to create a system dynamics model specific to weight gain and obesity in women of reproductive age that could inform future health policies and have the potential for use in preconception interventions targeting obese women. METHODS: We used our system dynamics model of obesity in women to test various strategies for family building, including ovulation induction versus weight loss to improve ovulation. Outcomes included relative fecundability, postpartum body mass index, and mortality. RESULTS: Our system dynamics model demonstrated that obese women who become pregnant exhibit increasing obesity levels over time with elevated morbidity and mortality. Alternatively, obese women who lose weight prior to pregnancy have improved reproductive outcomes but may risk an age-related decline in fertility, which can affect overall family size. CONCLUSIONS: Our model highlights important public health issues regarding obesity in women of reproductive age. The model may be useful in preconception counseling of obese women who are attempting to balance the competing risks associated with age-related declines in fertility and clinically meaningful weight loss.

The "long tail" and public health: new thinking for addressing health disparities.

The prevailing approach to improving population health focuses on shifting population means through a few targeted and universal interventions. The success of this approach for eliminating health disparities depends on an assumption about the distribution of demand for such interventions. We explored whether long tail thinking from business might yield greater progress in eliminating disparities. We examined 2011 to 2013 data from 513 state and local health agency representatives in 47 states who used an online system to create 4351 small media and client reminder products promoting colorectal cancer screening. Products in the long tail were more likely to target minority groups with higher rates of colorectal cancer and lower rates of screening than Whites. Long tail thinking could help improve the public's health and eliminate disparities.

Leveraging systems science and design thinking to advance implementation science: moving toward a solution-oriented paradigm.

Many public health challenges are characterized by complexity that reflects the dynamic systems in which they occur. Such systems involve multiple interdependent factors, actors, and sectors that influence health, and are a primary driver of challenges of insufficient implementation, sustainment, and scale of evidence-based public health interventions. Implementation science frameworks have been developed to help embed evidence-based interventions in diverse settings and identify key factors that facilitate or hinder implementation. These frameworks are largely static in that they do not explain the nature and dynamics of interrelationships among the identified determinants, nor how those determinants might change over time. Furthermore, most implementation science frameworks are top-down, deterministic, and linear, leaving critical gaps in understanding of both how to intervene on determinants of successful implementation and how to scale evidence-based solutions. Design thinking and systems science offer methods for transforming this problem-oriented paradigm into one that is solution-oriented. This article describes these two approaches and how they can be integrated into implementation science strategies to promote implementation, sustainment, and scaling of public health innovation, ultimately resulting in transformative systems changes that improve population health.

The 2011-2016 Transdisciplinary Research on Energetics and Cancer (TREC) initiative: rationale and design.

PURPOSE: Recognition of the complex, multidimensional relationship between excess adiposity and cancer control outcomes has motivated the scientific community to seek new research models and paradigms. METHODS: The National Cancer Institute developed an innovative concept to establish a center grant mechanism in nutrition, energetics, and physical activity, referred to as the Transdisciplinary Research on Energetics and Cancer (TREC) Initiative. This paper gives an overview of the 2011-2016 TREC Collaborative Network and the 15 research projects being conducted at the centers. RESULTS: Four academic institutions were awarded TREC center grants in 2011: Harvard University, University of California San Diego, University of Pennsylvania, and Washington University in St. Louis. The Fred Hutchinson Cancer Research Center is the Coordination Center. The TREC research portfolio includes three animal studies, three cohort studies, four randomized clinical trials, one cross-sectional study, and two modeling studies. Disciplines represented by TREC investigators include basic science, endocrinology, epidemiology, biostatistics, behavior, medicine, nutrition, physical activity, genetics, engineering, health economics, and computer science. Approximately 41,000 participants will be involved in these studies, including children, healthy adults, and breast and prostate cancer survivors. Outcomes include biomarkers of cancer risk, changes in weight and physical activity, persistent adverse treatment effects (e.g., lymphedema, urinary and sexual function), and breast and prostate cancer mortality. CONCLUSION: The NIH Science of Team Science group will evaluate the value added by this collaborative science. However, the most important outcome will be whether this transdisciplinary initiative improves the health of Americans at risk of cancer as well as cancer survivors.

Using Systems Science for Strategic Planning of Obesity Prevention and Treatment: The Roundtable on Obesity Solutions Experience.

The sustained multi-decade increase in the prevalence of obesity calls for a new approach on addressing this public health concern. The Roundtable on Obesity Solutions (ROOS) (of the National Academies of Sciences, Engineering, and Medicine NASEM), a multisector group comprised of members from a variety of organizations and institutions, initiated a year-long effort to build a strategic plan and roadmap for action that would drive a paradigm shift for the ROOS in pursuing obesity solutions. Following a review of obesity prevention and treatment recommendations with sufficient actionable-evidence by authoritative organizations, the ROOS deployed systems science methods. Members engaged in group model building (GMB) exercises to develop an obesity systems map based on determinants and drivers from a multi-sector perspective and overlaid with aligned solutions. To expand the understanding of systems science approaches and methods, 3 public workshops were held in tandem with the development of the map. The causal map was refined, and solutions were ranked using a leverage-point framework to inform a strategic plan and narrative roadmap for action. For the ROOS, structural racism and social justice, biased mental models and social norms, and effective health communications were prioritized as the leverage points most likely to have a significant impact in addressing obesity. Complementary to the mission, vision, and guiding principles of the ROOS, the obesity systems map, and narrative roadmap will drive the ROOS activities over the next 3-6 years and serve as a resource for researchers, organizations, and institutions involved with policy, prevention, and treatment of obesity.