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.

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.

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.

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.

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.

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.

Scaling Up Housing Services Within the Child Welfare System: Policy Insights From Simulation Modeling

OBJECTIVES

Housing insecurity and homelessness contribute to risk of maltreatment among one in five of the nearly 3.5 million children annually investigated for maltreatment in the United States. The Family Unification Program (FUP)-a federal initiative-connects inadequately housed families involved in child welfare with long-term rental subsidies to avoid foster placement. However, FUP remains understudied and underutilized with funding levels that serve only a fraction of eligible households. The present study uses system dynamics modeling to inform decision-making by testing policies for scaling FUP.

METHOD

Simulations model delivery of FUP within child welfare from a feedback perspective. Calibrated on national data, models replicate trends in child welfare involvement from 2013 through 2016, and analyses forecast rates through 2019. Experiments test policies that enhance FUP. Outcomes track system-wide rates of family separation and returns on investment of expanded housing interventions.

RESULTS

Dramatic expansions of FUP benefit more families and improve marginal return on investment. Yet, scale-up fails to reduce system-wide rates of family separation or generates substantial cost-savings.

CONCLUSIONS

Simulations demonstrate structural challenges for scaling FUP. Constant demand for affordable housing constrains sustainable improvements in child protection. Child welfare responses to homelessness require innovations that reduce demand for housing services through prevention and earlier intervention.

A systematic review of system dynamics and agent-based obesity models: Evaluating obesity as part of the global syndemic

The problem of obesity has recently been reframed as part of the global syndemic-the co-occurring, interacting pandemics of obesity, undernutrition, and climate change that are driven by common underlying societal drivers. System science modeling approaches may help clarify how these shared drivers operate and the best ways to address them. The objective of this paper was to determine to what extent existing agent-based and system dynamics computational models of obesity provide insights into the shared drivers of the global syndemic. Peer-reviewed studies published until July 2018 were identified from Scopus, Web of Science, and PubMed databases. Thirty-eight studies representing 30 computational models were included. They show a growing use of system dynamics and agent-based modeling in the past decade. They most often examined mechanisms and interventions in the areas of social network-based influences on obesity, physiology and disease state mechanics, and the role of food and physical activity environments. Usefulness for identifying common drivers of the global syndemic was mixed; most models represented Western settings and focused on obesity determinants close to the person (eg, social circles, school settings, and neighborhood environments), with a relative paucity in models at mesolevel and macrolevel and in developing country contexts.

Design and methods of Shape Up Under 5: Integration of systems science and community-engaged research to prevent early childhood obesity

Shape Up Under 5 (SUU5) was a two-year early childhood obesity prevention pilot study in Somerville, Massachusetts (2015-2017) designed to test a novel conceptual framework called Stakeholder-driven Community Diffusion. For whole-of-community interventions, this framework posits that diffusion of stakeholders' knowledge about and engagement with childhood obesity prevention efforts through their social networks will improve the implementation of health-promoting policy and practice changes intended to reduce obesity risk. SUU5 used systems science methods (agent-based modeling, group model building, social network analysis) to design, facilitate, and evaluate the work of 16 multisector stakeholders ('the Committee'). In this paper, we describe the design and methods of SUU5 using the conceptual framework: the approach to data collection, and methods and rationale for study inputs, activities and evaluation, which together may further our understanding of the hypothesized processes within Stakeholder-driven Community Diffusion. We also present a generalizable conceptual framework for addressing childhood obesity and similar complex public health issues through whole-of-community interventions.

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.

Capability Traps Impeding Homeless Services: A Community-Based System Dynamics Evaluation

Continuums of Care (CoCs) are the primary coordinating bodies for homeless services in the United States. However, the complexities involved in delivering homeless services across interagency networks challenges coordination and system improvement. CoC governance, planning, and service provision have received little attention in academic literature, and thus, Continuums attempt to manage complex systems with little guidance. This evaluation applied community-based system dynamics with homeless consumers and service providers to (1) identify capability traps that impede services delivery and to (2) engage stakeholders in a structured system improvement process. Results revealed organizational structures for governance and planning that inhibit system outcomes. Insights led to policy and practice recommendations for the homeless system.

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.

Toward a Modern Science of Obesity at Washington University: How We Do It and What is the Payoff?

In our Cancer Prevention Program at Washington University in Saint Louis (WUSTL), we have made extraordinary efforts to create the kind of cancer prevention and control program that is both translational and transdisciplinary in nature, to accelerate the march from basic discoveries to population change. Here we present an overview of our obesity-related research currently ongoing in our Center, paying particular attention to both the translational- transdisciplinary process and to community-based participatory research. We end with our future directions for improving obesity-related cancer outcomes research. Cancer Prev Res; 9(7); 503-8. ©2016 AACR.

Understanding Global Cancer Disparities: The Role of Social Determinants from System Dynamics Perspective

BACKGROUND

In 2012, almost 57% of all cancer cases and 65% of cancer deaths occurred in low-and middle-income countries. If the current trend continues, the burden of cancer will increase to 22 million new cases annually by 2030, with 81% of new cases and almost 88% of mortality occurring in less developed countries.

METHODS

A qualitative review of the literature was conducted. This included a systematic search of eight electronic databases namely, PubMed, Academic Search Premier, CINAHL, Applied Social Sciences Index, EMBASE, SCOPUS, Cochrane and PsycINFO. The reference list of articles retrieved were also thoroughly searched. Inclusion criteria were studies that addressed global health, cancer disparities and global or economic development.

RESULTS

Thirty-one articles were identified that met the eligibility criteria. Results were synthesized in the form of a system dynamics causal loop diagram or map which led to identification of eight major stocks or system variables. These included, children and adult population, overall population health, pollution, quality of healthcare delivery, quality of neighborhood and built environment, social and community cohesiveness, healthy and social norms and attitudes, and literacy level. Based on this, a dynamic hypothesis of global health cancer disparities was developed. The causal loop diagram showed the role of multiple interacting feedback mechanisms as explanations for trends in global health cancer disparities and the underlying consequences.

CONCLUSIONS

Addressing these determinants of health requires an effective dynamic approach to improving global cancer health. Application of a systems thinking methodological approach has the potential to provide new understanding to how global development trends in combination with global health efforts to improve population health could shift cancer disparities and burden associated with the disease.

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.

Scaling-up impact in perinatology through systems science: Bridging the collaboration and translational divides in cross-disciplinary research and public policy

Despite progress over the past decade in reducing the global burden of newborn deaths, gaps in the knowledge base persist, and means of translating empirical findings into effective policies and programs that deliver life-saving interventions remain poorly understood. Articles in this issue highlight the relevance of transdisciplinary research in perinatology and calls for increased efforts to translate research into public policy and to integrate interventions into existing primary care delivery systems. Given the complexity and multi-causality of many of the remaining challenges in newborn health, and the effects that social and economic factors have over many newborn conditions, it has further been proposed that integrated, multi-sector public policies are also required. In this article, we discuss the application of systems science methods to advance transdisciplinary research and public policy-making in perinatology. Such approaches to research and public policy have been used to address various global challenges but have rarely been implemented in developing country settings. We propose that they hold great promise to improve not only our understanding of complex perinatology problems but can also help translate research-based insights into effective, multi-pronged solutions that deliver positive, intended effects. Examples of successful transdisciplinary science exist, but successes and failures are context specific, and there are no universal blueprints or formulae to reproduce what works in a specific context into different social system settings. Group model building is a tool, based in the field of System Dynamics, that we have used to facilitate transdisciplinary research and, to a lesser extent, policy formulation in a systematic and replicable way. In this article, we describe how group model building can be used and argue for scaling its use to further the translation of empirical evidence and insights into policy and action that increase maternal and neonatal survival and well-being.

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.

Sequence and timing of three community interventions to domestic violence

Community responses to domestic violence typically involve the introduction of multiple interventions. Yet very little is known about the impact of the timing and sequencing of these interventions on community outcomes. A reason for this is the inherent limitations of traditional methods in social science. New methods are needed to understand the effect of varying the sequence and timing of interventions. This study responds to the issue by introducing system dynamics as a method for modeling community interventions. The paper presents a model of domestic violence cases moving through a criminal justice response, and uses the simulation model to evaluate the impact of implementing three interventions-mandatory arrest, victim advocacy, and changes in level of cooperation-on two system-level outcomes: improving offender accountability and increasing victim safety. Results illustrate the complex nature of these relationships. Implications for community practice and future research are also discussed.