An action‐oriented framework for systems‐based solutions aimed at childhood obesity prevention in US Latinx and Latin American populations

Childhood obesity in US Latinx and Latin American populations is a persistent, complex public health issue and, as such, requires solutions grounded on systems science theory and methods. In this paper, we introduce an action‐oriented framework to design, implement, evaluate, and sustain whole‐of‐community systems changes for childhood obesity prevention in US Latinx and Latin American populations. Our framework covers six action steps: (1) foster multisectoral team; (2) map the system, its context, and drivers; (3) envision system‐wide changes; (4) effect system‐wide changes; (5) monitor, learn, and adapt; and (6) scale and sustain. We also propose 10 principles that put human and environmental rights and systems thinking at the center of these systems‐based solutions. For each action step, we provide a list of concrete activities, methods, approaches, and examples that can be used to guide and inform the work needed to achieve the expected outputs. Finally, we discuss how a wider adoption of systems science for childhood obesity prevention among US Latinx and Latin American populations can be encouraged and sustained.

[1]  O. Sarmiento,et al.  Implementation of childhood obesity prevention and control policies in the United States and Latin America: Lessons for cross‐border research and practice , 2021, Obesity reviews : an official journal of the International Association for the Study of Obesity.

[2]  M. Pratt,et al.  Capacity for childhood obesity research in Latin American and US Latino populations: State of the field, challenges, opportunities, and future directions , 2021, Obesity reviews : an official journal of the International Association for the Study of Obesity.

[3]  B. Swinburn,et al.  Understanding the dynamics of obesity prevention policy decision-making using a systems perspective: A case study of Healthy Together Victoria , 2021, PloS one.

[4]  A. King,et al.  Community-Based Approaches to Reducing Health Inequities and Fostering Environmental Justice through Global Youth-Engaged Citizen Science , 2021, International journal of environmental research and public health.

[5]  H. Skouteris,et al.  Reframing the early childhood obesity prevention narrative through an equitable nurturing approach , 2020, Maternal & child nutrition.

[6]  Ariella R. Korn,et al.  Implementing Group Model Building With the Shape Up Under 5 Community Committee Working to Prevent Early Childhood Obesity in Somerville, Massachusetts , 2020, Journal of public health management and practice : JPHMP.

[7]  K. Wiesner,et al.  What is a complex system? , 2020, What Is a Complex System?.

[8]  Jylana L. Sheats,et al.  Employing Participatory Citizen Science Methods to Promote Age-Friendly Environments Worldwide , 2020, International journal of environmental research and public health.

[9]  Ross A. Hammond,et al.  Integrating Complex Systems Methods to Advance Obesity Prevention Intervention Research , 2020, Health education & behavior : the official publication of the Society for Public Health Education.

[10]  Ross A. Hammond,et al.  Design and methods of Shape Up Under 5: Integration of systems science and community-engaged research to prevent early childhood obesity , 2019, PloS one.

[11]  S. Allender,et al.  Translating systems thinking into practice for community action on childhood obesity , 2019, Obesity reviews : an official journal of the International Association for the Study of Obesity.

[12]  M. Clarke,et al.  National action plans to tackle NCDs: role of stakeholder network analysis , 2019, British medical journal.

[13]  Chris M. Smith,et al.  The characteristics of problem structuring methods: A literature review , 2019, Eur. J. Oper. Res..

[14]  Vincent Marchau,et al.  Decision Making under Deep Uncertainty: From Theory to Practice , 2019 .

[15]  P. Estabrooks,et al.  Dissemination and Implementation Science for Public Health Professionals: An Overview and Call to Action , 2018, Preventing chronic disease.

[16]  Ross A. Hammond,et al.  Engaging Coalitions in Community-Based Childhood Obesity Prevention Interventions: A Mixed Methods Assessment. , 2018, Childhood obesity.

[17]  Mark C. Pachucki,et al.  Social network analysis of stakeholder networks from two community-based obesity prevention interventions , 2018, PloS one.

[18]  Jill A. Kuhlberg,et al.  Understanding a successful obesity prevention initiative in children under 5 from a systems perspective , 2018, PloS one.

[19]  Ambuj Tewari,et al.  Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support , 2017, Annals of behavioral medicine : a publication of the Society of Behavioral Medicine.

[20]  M. Petticrew,et al.  The need for a complex systems model of evidence for public health , 2017, The Lancet.

[21]  J. Mayne Theory of Change Analysis: Building Robust Theories of Change , 2017 .

[22]  J. Tschann,et al.  Obstacles to preventing obesity in children aged 2 to 5 years: Latino mothers’ and fathers’ experiences and perceptions of their urban environments , 2017, International Journal of Behavioral Nutrition and Physical Activity.

[23]  J. Rivera,et al.  Prevention of childhood obesity and food policies in Latin America: from research to practice , 2017, Obesity reviews : an official journal of the International Association for the Study of Obesity.

[24]  Jylana L. Sheats,et al.  Using Citizen Scientists to Gather, Analyze, and Disseminate Information About Neighborhood Features That Affect Active Living , 2016, Journal of Immigrant and Minority Health.

[25]  Christina D. Economos,et al.  Designing an Agent-Based Model for Childhood Obesity Interventions: A Case Study of ChildObesity180 , 2016, Preventing chronic disease.

[26]  Gemma Carey,et al.  Systems science and systems thinking for public health: a systematic review of the field , 2015, BMJ Open.

[27]  Amy H Auchincloss,et al.  Brief introductory guide to agent-based modeling and an illustration from urban health research. , 2015, Cadernos de saude publica.

[28]  G. Carey,et al.  Adaptive Policies for Reducing Inequalities in the Social Determinants of Health , 2015, International journal of health policy and management.

[29]  Warren E. Walker,et al.  Developing dynamic adaptive policy pathways: a computer-assisted approach for developing adaptive strategies for a deeply uncertain world , 2015, Climatic Change.

[30]  G. Robins Doing Social Network Research: Network-based Research Design for Social Scientists , 2015 .

[31]  Steven Cummins,et al.  ‘Dark logic’: theorising the harmful consequences of public health interventions , 2014, Journal of Epidemiology & Community Health.

[32]  Peter S. Hovmand,et al.  Community Based System Dynamics , 2013 .

[33]  Warren E. Walker,et al.  Dynamic adaptive policy pathways: A method for crafting robust decisions for a deeply uncertain world , 2013 .

[34]  Tim Blackman,et al.  Using Qualitative Comparative Analysis to understand complex policy problems , 2013 .

[35]  A. Renzaho,et al.  Community energy balance: a framework for contextualizing cultural influences on high risk of obesity in ethnic minority populations. , 2012, Preventive medicine.

[36]  Robin Gregory,et al.  Structured Decision Making: A Practical Guide to Environmental Management Choices , 2012 .

[37]  Richard Hummelbrunner Systems thinking and evaluation , 2011 .

[38]  David J. Weerts,et al.  Community Engagement and Boundary-Spanning Roles at Research Universities , 2010, The Journal of Higher Education.

[39]  J. Kwadijk,et al.  Using adaptation tipping points to prepare for climate change and sea level rise: a case study in the Netherlands , 2010 .

[40]  Sreeja Nair,et al.  Seven tools for creating adaptive policies , 2010 .

[41]  Marion Nestle,et al.  Can the food industry play a constructive role in the obesity epidemic? , 2008, JAMA.

[42]  Branda Nowell,et al.  Putting the system back into systems change: a framework for understanding and changing organizational and community systems , 2007, American journal of community psychology.

[43]  F. Butterfoss Coalitions and Partnerships in Community Health , 2007 .

[44]  S. Straus,et al.  Lost in knowledge translation: Time for a map? , 2006, The Journal of continuing education in the health professions.

[45]  W. Trochim,et al.  Practical challenges of systems thinking and modeling in public health. , 2006, American journal of public health.

[46]  J. Sterman Learning from evidence in a complex world. , 2006, American journal of public health.

[47]  S. Zaza,et al.  Evidence-Based Public Health , 2016, BioMed research international.

[48]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[49]  J Swanson,et al.  Business Dynamics—Systems Thinking and Modeling for a Complex World , 2002, J. Oper. Res. Soc..

[50]  R. Crosby,et al.  Emerging theories in health promotion practice and research , 2002 .

[51]  Warren E. Walker,et al.  Adaptive policies, policy analysis, and policy-making , 2001, Eur. J. Oper. Res..

[52]  P. Checkland Soft Systems Methodology: A Thirty Year Retrospective a , 2000 .

[53]  G. Long,et al.  Structured Decision Making , 2020 .

[54]  A. Bauman,et al.  Identifying opportunities to develop the science of implementation for community-based non-communicable disease prevention: A review of implementation trials. , 2019, Preventive medicine.

[55]  Jan H. Kwakkel,et al.  Dynamic Adaptive Policy Pathways (DAPP) , 2019, Decision Making under Deep Uncertainty.

[56]  N. Wallerstein,et al.  Improving health through community engagement, community organization, and community building. , 2015 .

[57]  D. Booth,et al.  Taking responsibility for complexity How implementation can achieve results in the face of complex problems , 2011 .

[58]  Carl D. Shapiro,et al.  Adaptive management: The U.S. Department of the Interior technical guide , 2009 .