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.

Food Insecurity and Blood Pressure in a Multiethnic Population.

Food insecurity is a social determinant of health and is increasingly recognized as a risk factor for hypertension. Native Hawaiians bear a disproportionate burden of hypertension and known risk factors. Despite this, the relative effects of food insecurity and financial instability on blood pressure have yet to be investigated in this population. This study examines the relative effects of food insecurity and financial instability on blood pressure, controlling for potential confounders in a multiethnic sample. Participants (n = 124) were recruited from a U.S. Department of Agriculture-funded study called the Children's Healthy Living Center of Excellence. Biometrics (i.e., blood pressure, weight, and height) were measured. Demographics, physical activity, diet, psychosocial variables, food insecurity, and financial instability were assessed via self-report questionnaires. Hierarchical linear regression models were conducted. Model 1, which included sociodemographic variables and known biological risk factors, explained a small but significant amount of variance in systolic blood pressure. Model 2 added physical activity and daily intake of fruit, fiber, and whole grains, significantly improving the model. Model 3 added financial instability and food insecurity, further improving the model (R2 = 0.37, F = 2.67, p = 0.031). Food insecurity, female sex, and BMI were significantly and independently associated with increased systolic blood pressure. These results suggest a direct relationship between food insecurity and systolic blood pressure, which persisted after controlling for physical activity, consumption of fruits, fiber, and whole grains, and BMI. Efforts to reduce food insecurity, particularly among Native Hawaiians, may help reduce hypertension in this high-risk population.

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.

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.

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.

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.

Meeting housing needs of child welfare-involved families: Policy insights from simulation modeling.

BACKGROUND: Inadequate housing contributes to the risk of family separation in nearly one-quarter of child maltreatment investigations. Child welfare struggles to identify and address the demand for housing assistance. A range of housing interventions shows promise for stabilizing families. Still, aid remains difficult to access, and little evidence exists for prioritizing households to interventions. Inefficient decisions about who to serve with scarce housing resources threaten to diminish resources and unintentionally place children at greater risk. OBJECTIVE: The present study leverages computational modeling to simulate the complex dynamics of coordinated child welfare response to inadequate housing. Simulations address the lack of microdata on current service delivery to inform policy-making that protects children from family insecurity. PARTICIPANTS AND SETTINGS: A series of simulated policy experiments test strategies for maximizing access to appropriate housing assistance and minimizing system-wide family separations using US estimates of housing insecurity and child welfare involvement. Models incorporate the feedback loops involved in seeking and waiting for needed services, using information on national rates of housing insecurity among child welfare-involved families. RESULTS: Results demonstrate population-level improvements in family stability from enhanced targeting of housing assistance to families most likely to benefit, plus expanded access to housing interventions. Neither improved screening procedures nor more housing supports alone improve child welfare outcomes. CONCLUSIONS: Findings emphasize the importance of data-driven upstream policies for protecting inadequately housed children at risk of maltreatment.

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.

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.

System Dynamics of Cognitive Vulnerabilities and Family Support Among Latina Children and Adolescents.

The paper describes an approach to developing a data-driven development of a feedback theory of cognitive vulnerabilities and family support focused on understanding the dynamics experienced among Latina children, adolescents, and families. Family support is understood to be a response to avoidant and maladaptive behaviors that may be characteristic of cognitive vulnerabilities commonly associated depression and suicidal ideation. A formal feedback theory is developed, appraised, and analyzed using a combination of secondary analysis of qualitative interviews (N = 30) and quantitative analysis using system dynamics modeling and simulation. Implications for prevention practice, treatment, and future research are discussed.

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 cause-effect graphs to elicit expert knowledge for cross-impact balance analysis.

Cross-impact balance (CIB) analysis leverages expert knowledge pertaining to the nature and strength of relationships between components of a system to identify the most plausible future 'scenarios' of the system. These scenarios, also referred to as 'storylines', provide qualitative insights into how the state of one factor can either promote or restrict the future state of one or multiple other factors in the system. This paper presents a novel, visually oriented questionnaire developed to elicit expert knowledge about the relationships between key factors in a system, for the purpose of CIB analysis. The questionnaire requires experts to make selections from a series of standardized cause-effect graphical profiles that depict a range of linear and non-linear relationships between factor pairs. The questionnaire and the process of translating the graphical selections into data that can be used for CIB analysis is described using an applied example which focuses on urban health in Latin American cities.

From causal loop diagrams to future scenarios: Using the cross-impact balance method to augment understanding of urban health in Latin America.

Urban health is shaped by a system of factors spanning multiple levels and scales, and through a complex set of interactions. Building on causal loop diagrams developed via several group model building workshops, we apply the cross-impact balance (CIB) method to understand the strength and nature of the relationships between factors in the food and transportation system, and to identify possible future urban health scenarios (i.e., permutations of factor states that impact health in cities). We recruited 16 food and transportation system experts spanning private, academic, non-government, and policy sectors from six Latin American countries to complete an interviewer-assisted questionnaire. The questionnaire, which was pilot tested on six researchers, used a combination of questions and visual prompts to elicit participants' perceptions about the bivariate relationships between 11 factors in the food and transportation system. Each participant answered questions related to a unique set of relationships within their domain of expertise. Using CIB analysis, we identified 21 plausible future scenarios for the system. In the baseline model, 'healthy' scenarios (with low chronic disease, high physical activity, and low consumption of highly processed foods) were characterized by high public transportation subsidies, low car use, high street safety, and high free time, illustrating the links between transportation, free time and dietary behaviors. In analyses of interventions, low car use, high public transport subsidies and high free time were associated with the highest proportion of factors in a healthful state and with high proportions of 'healthy' scenarios. High political will for social change also emerged as critically important in promoting healthy systems and urban health outcomes. The CIB method can play a novel role in augmenting understandings of complex urban systems by enabling insights into future scenarios that can be used alongside other approaches to guide urban health policy planning and action.

Defining and Intervening on Cumulative Environmental Neurodevelopmental Risks: Introducing a Complex Systems Approach.

BACKGROUND: The combined effects of multiple environmental toxicants and social stressor exposures are widely recognized as important public health problems contributing to health inequities. However cumulative environmental health risks and impacts have received little attention from U.S. policy makers at state and federal levels to develop comprehensive strategies to reduce these exposures, mitigate cumulative risks, and prevent harm. An area for which the inherent limitations of current approaches to cumulative environmental health risks are well illustrated is children's neurodevelopment, which exhibits dynamic complexity of multiple interdependent and causally linked factors and intergenerational effects. OBJECTIVES: We delineate how a complex systems approach, specifically system dynamics, can address shortcomings in environmental health risk assessment regarding exposures to multiple chemical and nonchemical stressors and reshape associated public policies. DISCUSSION: Systems modeling assists in the goal of solving problems by improving the "mental models" we use to make decisions, including regulatory and policy decisions. In the context of disparities in children's cumulative exposure to neurodevelopmental stressors, we describe potential policy insights about the structure and behavior of the system and the types of system dynamics modeling that would be appropriate, from visual depiction (i.e., informal maps) to formal quantitative simulation models. A systems dynamics framework provides not only a language but also a set of methodological tools that can more easily operationalize existing multidisciplinary scientific evidence and conceptual frameworks on cumulative risks. Thus, we can arrive at more accurate diagnostic tools for children's' environmental health inequities that take into consideration the broader social and economic environment in which children live, grow, play, and learn. https://doi.org/10.1289/EHP7333.

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.

Understanding Mechanisms Driving Family Homeless Shelter Use and Child Mental Health.

Homeless shelters throughout the U.S. are overcrowded and under-resourced. Families with children face substantial barriers to timely, successful shelter exit, and prolonged shelter stays threaten child mental health. This community-based system dynamics study explored barriers to timely, successful shelter exit and feedback mechanisms driving length of stay and child mental health risk. Group model building - a participatory systems science tool - and key informant interviews were conducted with clients (N = 37) and staff (N = 6) in three family homeless shelters in a Midwestern region. Qualitative content analysis with emergent coding identified key themes feedback loops. Findings indicated overcrowding delayed successful shelter exit; longer stays exacerbated crowding and stress in a vicious cycle. Furthermore, longer stays exacerbated child risk for mental disorder both directly and indirectly via crowding and caregiver stress. Capacity constraints limited families served, while contributing to ongoing unmet need. Future research should investigate the roles of these dynamic feedback relationships in the persistent vulnerability of homeless families. Service design should prioritize interventions that alleviate crowding and subsequent threats to mental health such as private or scattered-site shelter accommodations, affordable child care, and homelessness prevention to facilitate successful shelter exit and mitigate child mental health risk.

Systems Science Approaches for Global Environmental Health Research: Enhancing Intervention Design and Implementation for Household Air Pollution (HAP) and Water, Sanitation, and Hygiene (WASH) Programs.

BACKGROUND: Two of the most important causes of global disease fall in the realm of environmental health: household air pollution (HAP) and poor water, sanitation, and hygiene (WASH) conditions. Interventions, such as clean cookstoves, household water treatment, and improved sanitation facilities, have great potential to yield reductions in disease burden. However, in recent trials and implementation efforts, interventions to improve HAP and WASH conditions have shown few of the desired health gains, raising fundamental questions about current approaches. OBJECTIVES: We describe how the failure to consider the complex systems that characterize diverse real-world conditions may doom promising new approaches prematurely. We provide examples of the application of systems approaches, including system dynamics, network analysis, and agent-based modeling, to the global environmental health priorities of HAP and WASH research and programs. Finally, we offer suggestions on how to approach systems science. METHODS: Systems science applied to environmental health can address major challenges by a) enhancing understanding of existing system structures and behaviors that accelerate or impede aims; b) developing understanding and agreement on a problem among stakeholders; and c) guiding intervention and policy formulation. When employed in participatory processes that engage study populations, policy makers, and implementers, systems science helps ensure that research is responsive to local priorities and reflect real-world conditions. Systems approaches also help interpret unexpected outcomes by revealing emergent properties of the system due to interactions among variables, yielding complex behaviors and sometimes counterintuitive results. DISCUSSION: Systems science offers powerful and underused tools to accelerate our ability to identify barriers and facilitators to success in environmental health interventions. This approach is especially useful in the context of implementation research because it explicitly accounts for the interaction of processes occurring at multiple scales, across social and environmental dimensions, with a particular emphasis on linkages and feedback among these processes. https://doi.org/10.1289/EHP7010.