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

Actions against the double burden of malnutrition in Peru: a community-informed system dynamics model

Background

Peru's progress in reducing stunting has stagnated since 2018, while the country is facing increasing levels of overnutrition, leading to a double burden of malnutrition. However, this shift in nutrition burden is not reflected in Peru's nutrition policy agenda. This study aims to identify leverage points for actions against population-level double burden of malnutrition in Peru.

Methods

We developed a system dynamics model that simulates changes in overweight and stunting over time in Peru through changes in food system drivers. The model was conceptually informed by policymakers, practitioners and community members in Peru and used quantitative and qualitative data from secondary sources and published literature.

Findings

The model indicated that several overnutrition policies, including policies targeting food availability and affordability, may decelerate but not halt the increase of overweight in the country, mainly due to industry resistance. However, in the long term, the reallocation of resources towards overnutrition policies may inadvertently hinder progress towards stunting targets. Transforming nutrition policy governance, from siloed overnutrition and undernutrition policies towards a common policy framework against the double burden of malnutrition was the only modelled scenario that halted the rise in overnutrition, while keeping Peru on course to reach its stunting goals.

Interpretation

Transition away from policy landscapes that focus on single nutrition outcomes towards synergistic actions that target malnutrition in all forms is a long-term solution towards achieving global nutrition goals. Such policy transitions are especially important in low and middle-income countries like Peru, which are affected by the double burden of malnutrition.

Funding

This study was supported by a research grant from the Biotechnology and Biological Sciences Research Council (BBSRC) (grant reference: BB/T009004/1).

Plant-based and sustainable diet: A systematic review of its impact on obesity

The food system significantly affects the environment through land use, emissions from livestock, deforestation, and food waste. Diet sustainability considers the environmental effects of food production, distribution, and consumption. Animal products emit more greenhouse gases than plant-based foods, prompting a shift towards plant-focused diets for reduced emissions. Sustainable diets, like the EAT-Lancet model, prioritize plant-based foods, adjusting for regional eating habits. These diets aim to be both environmentally friendly and conducive to human health, addressing concerns like obesity and chronic diseases. Obesity is a major global health challenge, and its complex relationship with food production and consumption patterns calls for sustainable solutions to reduce pressure on ecosystems and promote healthier lifestyles. Tackling obesity requires holistic strategies that address not only individual health but also the broader environmental impacts of food systems. A systematic review examined the link between plant-based diets and obesity focusing on studies assessing Body Mass Index (BMI) and body fat assessment. Despite limited research, evidence suggests that adherence to a plant-based diet, particularly a healthy one, is associated with lower obesity rates. More longitudinal and intervention studies are necessary for a stronger consensus on the matter.

Simulated retail food environments: A literature review of systems science approaches to advance equity in access to healthy diets

As researchers increasingly utilize systems science simulation modeling (SSSM), little is known about how and by whom SSSMs are being leveraged to address inequities in access to healthy diets. We evaluated the extent to which studies (n = 66) employing SSSM to examine retail food environments (RFEs): included three pillars of equity (social position, human capital, socioeconomic and political context) that shape RFEs and access to healthy diets; grounded model design and development in theory; engaged with diverse stakeholders and lived experiences related to RFEs; and translated model findings towards addressing inequities in RFEs. Most studies (n = 58) included some model characteristics related to social position (e.g., age). Characteristics related to human capital (e.g., meal planning skills) were the least integrated fundamental pillar (n = 15). All studies included some characteristics related to socioeconomic and political context; however, we found little to no incorporation of social contexts (e.g., cultural and societal norms). Regarding model design and development, less than one-third of studies specified theoretical frameworks or engaged with local domain experts and stakeholders. While certain research objectives and, consequently, model types lend themselves better than others to address key pillars that influence RFEs, findings show that models are not fully leveraging SSSMs to analyze the multiple, interacting dimensions - particularly social phenomena - influencing equity in access to healthy diets. Greater attention to engaging stakeholders and the role of human capital and social contexts will likely better equip models to more holistically examine equitable food access, including essential pathways and unintended consequences of programs and policies.

Integrating Australian Native Foods for a More Sustainable Food System: A Qualitative Co-Design Study with Aboriginal Communities

(1) Background: Integrating native foods into food systems has shown promising benefits for health, the environment, and the revitalisation of Aboriginal culture. This study aims to explore the benefits, facilitators, and barriers of integrating Australian native foods into the current food system and how traditional knowledge around these foods can be revitalised in a culturally safe way. (2) Methods: This qualitative co-design study involved the following four phases: (I) Relationship building with the communities and cultural training for the research team; (II) Establishment of the Aboriginal Reference Group (ARG) for community involvement and governance; (III) Data collection through interviews and focus groups with participants from two urban Aboriginal communities in Sydney and experts in native foods; and (IV) Collaborative data analysis using both deductive and inductive thematic analysis. (3) Results: We interviewed 22 participants who acknowledged the nutritional, health, cultural, environmental, and economic benefits of Australian native foods. They strongly identified the impact of colonisation and imposed Western culture as root barriers impacting other barriers at the structural, socioeconomic, social, and environmental levels. Participants aspire to achieve food security and sovereignty in a more sustainable food system including native foods. To achieve their aspirations, a framework based on Aboriginal values and principles was developed to guide multicomponent initiatives using native foods. (4) Conclusions: A compassionate food model based on emancipatory community-based and land-based education is essential, connecting ancient and contemporary knowledge to transform the food system. Future research should focus on implementing and evaluating the multicomponent interventions suggested by the participants.

Insights from a codesigned dynamic modelling study of child and adolescent obesity in Australia

Introduction

Child and adolescent obesity is associated with a range of immediate health issues and influences obesity in adulthood. The complex nature of health determinants that contribute to obesity makes it challenging to deliver effective public health interventions. This research presents insights from a system dynamics model of childhood and adolescent obesity aimed at supporting evidence-based decision-making.

Methods

A system dynamics model was developed using the best available evidence and data, with input from research and industry experts to map the hypothetical causal structure of the factors contributing to childhood and adolescent obesity in Australia. The model was calibrated to fit the historical prevalence of obesity (R 2 =0.97, mean squared error (MSE)=4.94E-04). Intervention-based scenarios were simulated to examine how changes in environmental factors and health-related behaviours may affect the prevalence of obesity. The potential economic benefits of the scenarios were estimated from changes in population healthcare spending and quality of life compared with base model projections.

Results

A series of interventions were explored in the model, including changes in early childhood behaviours, changes to diet and physical activity in childcare and school settings, financial support for organised sports and sugar-sweetened beverage taxation. The most promising individually implemented intervention scenario for reducing the prevalence of childhood and adolescent obesity was a sugar-sweetened beverage tax (0.57 percentage points and 0.61 percentage points, respectively) and government funding of organised sports (0.42 percentage points and 0.63 percentage points, respectively). When all interventions were implemented in combination, childhood obesity was reduced by 1.43 percentage points and 1.81 percentage points in adolescents.

Conclusions

The findings highlight the challenges faced by policy-makers and public health practitioners working to reduce childhood and adolescent obesity. Insights from the model emphasise the value of public health programmes over the life course. Implementing initiatives with broad reach that support healthy choices may reduce obesity, resulting in a healthier Australian population.

Understanding the obesity dynamics by socioeconomic status in Colombian and Mexican cities using a system dynamics model

Purpose

This paper aims to enrich understanding of the obesity transition among socioeconomic status (SES) strata by gender and age in cities of Colombia and Mexico. The study uses harmonized data from the Salud Urbana en América Latina (SALURBAL) study.

Methods

A population-level system dynamics model was developed using 2010 and 2015 data from Colombia and 2012 and 2016 data from Mexico (national health surveys). The model simulates the prevalence of different BMI categories (i.e., not overweight, overweight, obese) stratified by gender, age, and SES, in the SALURBAL cities (aggregated to the country level) of Colombia and Mexico from 2010 to 2050. Sample sizes for Colombia in 2010 and Mexico in 2012 were 7420 and 5785 children (<5 years), 21601 and 14413 children and adolescents (5-17 years), and 46597 and 20464 adults (18-64 years), respectively. Sample sizes for Colombia in 2015 and Mexico in 2016 were 4450 and 907 children, 12468 and 2350 children and adolescents, and 90430 and 3413 adults, respectively.

Results

For men in Colombia and Mexico, the burden of obesity is projected to increase among lower SES adults over time. Colombian women show similar patterns observed in men but the burden of obesity was already greater in the lower SES groups as early as 2012. In Mexican women, the burden of obesity in 2012 is higher in the lower SES population; however, the prevalence of obesity is projected to increase at a faster rate in the higher SES population. Patterns for children aged 0-14 years differed by gender and country.

Conclusions

The model suggests that the prevalence of obesity among SES strata by age and gender in SALURBAL cities of Colombia and Mexico are likely to change over time, and predicts their possible evolution through the different stages of the obesity transition.

Bridges and Mechanisms: Integrating Systems Science Thinking into Implementation Research

We present a detailed argument for how to integrate, or bridge, systems science thinking and methods with implementation science. We start by showing how fundamental systems science principles of structure, dynamics, information, and utility are relevant for implementation science. Then we examine the need for implementation science to develop and apply richer theories of complex systems. This can be accomplished by emphasizing a causal mechanisms approach. Identifying causal mechanisms focuses on the "cogs and gears" of public health, clinical, and organizational interventions. A mechanisms approach focuses on how a specific strategy will produce the implementation outcome. We show how connecting systems science to implementation science opens new opportunities for examining and addressing social determinants of health and conducting equitable and ethical implementation research. Finally, we present case studies illustrating successful applications of systems science within implementation science in community health policy, tobacco control, health care access, and breast cancer screening.

Mapping food system drivers of the double burden of malnutrition using community-based system dynamics: a case study in Peru

BACKGROUND

Peru is facing a double burden of malnutrition (DBM), characterized by the co-existence of undernutrition and overnutrition. Double-duty actions that concurrently target common drivers of undernutrition and overnutrition, while ensuring no unintended side effects, are recommended to effectively address the DBM. To understand these complex common mechanisms and design context-specific double-duty actions, there is a need for participatory systems approaches. This paper provides a case study of applying a community-based system dynamics approach to capture stakeholder perspectives of food system drivers of the DBM in two regions in Peru.

METHODS

We implemented a multi-stage community-based system dynamics approach, which included processes for research capacity building for systems approaches, and the designing, piloting, and implementation of stakeholder workshops. A total of 36 stakeholders, representing diverse perspectives, participated in five group model building workshops. Stakeholder views are presented in a causal loop diagram that showcases the feedback mechanisms between key food system drivers of overweight and stunting in Peru.

RESULTS

The causal loop diagram highlights that prioritization of undernutrition over overnutrition in the policymaking process, due to Peru's historically high levels of undernutrition, may undermine action against the DBM. It also describes potential mechanisms of unintended impacts of undernutrition policies on the DBM in Peru, including impacts related to within-family distribution and quality of food provided through food assistance programs, and unintended impacts due to regional dynamics.

CONCLUSIONS

This paper highlights the importance of a participatory approach to understand local needs and priorities when recommending double-duty actions in Peru and shares practical methodological guidance on applying participatory systems approaches in public health.

The current state of complex systems research on socioeconomic inequalities in health and health behavior-a systematic scoping review

BACKGROUND

Interest in applying a complex systems approach to understanding socioeconomic inequalities in health is growing, but an overview of existing research on this topic is lacking. In this systematic scoping review, we summarize the current state of the literature, identify shared drivers of multiple health and health behavior outcomes, and highlight areas ripe for future research.

METHODS

SCOPUS, Web of Science, and PubMed databases were searched in April 2023 for peer-reviewed, English-language studies in high-income OECD countries containing a conceptual systems model or simulation model of socioeconomic inequalities in health or health behavior in the adult general population. Two independent reviewers screened abstracts and full texts. Data on study aim, type of model, all model elements, and all relationships were extracted. Model elements were categorized based on the Commission on Social Determinants of Health framework, and relationships between grouped elements were visualized in a summary conceptual systems map.

RESULTS

A total of 42 publications were included; 18 only contained a simulation model, 20 only contained a conceptual model, and 4 contained both types of models. General health outcomes (e.g., health status, well-being) were modeled more often than specific outcomes like obesity. Dietary behavior and physical activity were by far the most commonly modeled health behaviors. Intermediary determinants of health (e.g., material circumstances, social cohesion) were included in nearly all models, whereas structural determinants (e.g., policies, societal values) were included in about a third of models. Using the summary conceptual systems map, we identified 15 shared drivers of socioeconomic inequalities in multiple health and health behavior outcomes.

CONCLUSIONS

The interconnectedness of socioeconomic position, multiple health and health behavior outcomes, and determinants of socioeconomic inequalities in health is clear from this review. Factors central to the complex system as it is currently understood in the literature (e.g., financial strain) may be both efficient and effective policy levers, and factors less well represented in the literature (e.g., sleep, structural determinants) may warrant more research. Our systematic, comprehensive synthesis of the literature may serve as a basis for, among other things, a complex systems framework for socioeconomic inequalities in health.

The long-term effectiveness and cost-effectiveness of public health interventions; how can we model behavior? A review

The effectiveness and cost of a public health intervention is dependent on complex human behaviors, yet health economic models typically make simplified assumptions about behavior, based on little theory or evidence. This paper reviews existing methods across disciplines for incorporating behavior within simulation models, to explore what methods could be used within health economic models and to highlight areas for further research. This may lead to better-informed model predictions. The most promising methods identified which could be used to improve modeling of the causal pathways of behavior-change interventions include econometric analyses, structural equation models, data mining and agent-based modeling; the latter of which has the advantage of being able to incorporate the non-linear, dynamic influences on behavior, including social and spatial networks. Twenty-two studies were identified which quantify behavioral theories within simulation models. These studies highlight the importance of combining individual decision making and interactions with the environment and demonstrate the importance of social norms in determining behavior. However, there are many theoretical and practical limitations of quantifying behavioral theory. Further research is needed about the use of agent-based models for health economic modeling, and the potential use of behavior maintenance theories and data mining.

System dynamics simulation models on overweight and obesity in children and adolescents: A systematic review

It has increasingly been recognized that developing successful obesity prevention policies and interventions requires understanding of the complex mechanisms driving the obesity pandemic and that models could be useful tools for simulating policies. This paper reviews system dynamics simulation models of mechanisms driving childhood overweight and obesity and/or testing of preventive interventions. A systematic literature search was conducted in six databases from inception to January 2023 using terms related to overweight/obesity, children, and system dynamics. Study descriptives, mechanisms, and where to intervene (the leverage points), as well as quality assessments of the simulation models were extracted by two researchers into a predetermined template and narratively synthesized. Seventeen papers describing 15 models were included. Models describing the mechanisms ranged from only intrapersonal factors to models cutting across multiple levels of the ecological model, but mechanisms across levels were lacking. The majority of interventions tested in the simulation models were changes to existing model parameters with less emphasis on models that alter system structure. In conclusion, existing models included mechanisms driving youth obesity at multiple levels of the ecological model. This is useful for developing an integrated simulation model combining mechanisms at multiple levels and allowing for testing fundamental system changes.

Understanding the dynamics emerging from the interplay among poor mental wellbeing, energy balance-related behaviors, and obesity prevalence in adolescents: A simulation-based study

Both obesity and poor mental wellbeing have a high prevalence in European youth. Adolescents in six countries identified mental wellbeing factors as main drivers of youth obesity through systems mapping. This study sought to (1) explore the dynamics of the interplay between poor mental wellbeing, energy balance-related behaviors, and adolescent overweight and obesity prevalence and (2) test the effect of intervention point scenarios to reduce adolescent obesity. Drawing on the youth-generated systems maps and a literature synthesis, we built a simulation model that represents the links from major feedback pathways for poor mental wellbeing to changes in dietary, physical activity, and sleep behaviors. The model was calibrated using survey data from Norway, expert input, and literature and shows a good fit between simulated behavior and available statistical data. The simulations indicate that adolescent mental wellbeing is harmed by socio-cultural pressures and stressors, which trigger reinforcing feedback mechanisms related to emotional/binge eating, lack of motivation to engage in physical activity, and sleep difficulty. Targeting a combination of intervention points that support a 25% reduction of pressure on body image and psychosocial stress showed potentially favorable effects on mental wellbeing-doubling on average for boys and girls and decreasing obesity prevalence by over 4%.

Combining systems thinking approaches and implementation science constructs within community-based prevention: a systematic review

BACKGROUND

Systems science offers methods for designing population health interventions while implementation science provides specific guidance for successful implementation. Integrating systems and implementation science may strengthen implementation and enhance and sustain systemic change to achieve system-level outcomes. Little is known about the extent to which these two approaches have been integrated to date. This review aimed to identify and synthesise the peer-reviewed literature that has reported the combined use of systems thinking approaches and implementation science constructs (within the same study), to deliver population health interventions.

METHODS

A systematic literature search of peer-reviewed original research was conducted across six databases from 2009 to 2021. Journal manuscripts were included if they: (1) reported on a population health study conducted in a community, (2) reported the use of a systems method in the design of the intervention, and (3) used an implementation science theory, framework or model in the delivery of the intervention. Data extracted related to the specific systems methods and definitions and implementation science constructs used. The Mixed Methods Appraisal Tool (MMAT) was used to assess study quality.

RESULTS

Of the 9086 manuscripts returned, 320 manuscripts were included for full-text review. Of these, 17 manuscripts that reported on 14 studies were included in the final extraction. The most frequently reported systems methods were a 'whole of community systems approach' (n = 4/14) and 'community-based system dynamics' (n = 2/14). Nineteen different implementation science theories, frameworks and models were used for intervention delivery, with RE-AIM being the only framework used in more than one study.

CONCLUSION

There are few published peer-reviewed studies using systems thinking and implementation science for designing and delivering population health interventions. An exploration of synergies is worthwhile to operationalise alignment and improve implementation of systems thinking approaches. Review protocol registration PROSPERO CRD42021250419.

Guidance on the use of complex systems models for economic evaluations of public health interventions

To help health economic modelers respond to demands for greater use of complex systems models in public health. To propose identifiable features of such models and support researchers to plan public health modeling projects using these models. A working group of experts in complex systems modeling and economic evaluation was brought together to develop and jointly write guidance for the use of complex systems models for health economic analysis. The content of workshops was informed by a scoping review. A public health complex systems model for economic evaluation is defined as a quantitative, dynamic, non-linear model that incorporates feedback and interactions among model elements, in order to capture emergent outcomes and estimate health, economic and potentially other consequences to inform public policies. The guidance covers: when complex systems modeling is needed; principles for designing a complex systems model; and how to choose an appropriate modeling technique. This paper provides a definition to identify and characterize complex systems models for economic evaluations and proposes guidance on key aspects of the process for health economics analysis. This document will support the development of complex systems models, with impact on public health systems policy and decision making.

Understanding Misimplementation in U.S. State Health Departments: An Agent-Based Model

INTRODUCTION

The research goal of this study is to explore why misimplementation occurs in public health agencies and how it can be reduced. Misimplementation is ending effective activities prematurely or continuing ineffective ones, which contributes to wasted resources and suboptimal health outcomes.

METHODS

The study team created an agent-based model that represents how information flow, filtered through organizational structure, capacity, culture, and leadership priorities, shapes continuation decisions. This agent-based model used survey data and interviews with state health department personnel across the U.S. between 2014 and 2020; model design and analyses were conducted with substantial input from stakeholders between 2019 and 2021. The model was used experimentally to identify potential approaches for reducing misimplementation.

RESULTS

Simulations showed that increasing either organizational evidence-based decision-making capacity or information sharing could reduce misimplementation. Shifting leadership priorities to emphasize effectiveness resulted in the largest reduction, whereas organizational restructuring did not reduce misimplementation.

CONCLUSIONS

The model identifies for the first time a specific set of factors and dynamic pathways most likely driving misimplementation and suggests a number of actionable strategies for reducing it. Priorities for training the public health workforce include evidence-based decision making and effective communication. Organizations will also benefit from an intentional shift in leadership decision-making processes. On the basis of this initial, successful application of agent-based model to misimplementation, this work provides a framework for further analyses.

Use of qualitative systems mapping and causal loop diagrams to understand food environments, diet and obesity: a scoping review protocol

INTRODUCTION

Food systems can shape dietary behaviour and obesity outcomes in complex ways. Qualitative systems mapping using causal loop diagrams (CLDs) can depict how people understand the complex dynamics, inter-relationships and feedback characteristic of food systems in ways that can support policy planning and action. To date, there has been no attempt to review this literature. The objectives of this review are to scope the extent and nature of studies using qualitative systems mapping to facilitate the development of CLDs by stakeholders to understand food environments, including settings and populations represented, key findings and the methodological processes employed. It also seeks to identify gaps in knowledge and implications for policy and practice.

METHODS AND ANALYSIS

This protocol describes a scoping review guided by the Joanna Briggs Institute manual, the framework by Khalil and colleagues and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist reporting guidelines. A search strategy was iteratively developed with two academic librarians and the research team. This strategy will be used to search six databases, including Ovid MEDLINE, Embase, EmCare, Web of Science, Scopus and ProQuest Central. Identified citations will be screened by two independent reviewers; first, by title and abstract, and then full-text articles to identify papers eligible for inclusion. The reference lists of included studies and relevant systematic reviews will be searched to identify other papers eligible for inclusion. Two reviewers will extract information from all included studies and summarise the findings descriptively and numerically.

ETHICS AND DISSEMINATION

The scoping review will provide an overview of how CLDs developed by stakeholders have been elicited to understand food environments, diet and obesity, the insights gained and how the CLDs have been used. It will also highlight gaps in knowledge and implications for policy and practice. The review will be disseminated through publication in an academic journal and conference presentations.

Assessing policies to reduce adolescent overweight and obesity: Insights from a system dynamics model using data from the Health Behavior in School-Aged Children study

Adolescent overweight and obesity (AdOWOB) in Europe has proven to be a persistent and complex problem, and appropriate systems methods may help in evaluating potential policy options. This paper describes the development of a system dynamics model of AdOWOB as part of the EU-funded CO-CREATE project. The model was developed using literature and data from the Health Behavior in School-Aged Children (HBSC) study across 31 European countries. We identified 10 HBSC variables that were included as direct or indirect drivers of AdOWOB in the dynamic model, seven at the level of the individual, and three related to the social environment. The model was calibrated to 24 separate cases based on four gender and perceived wealth segments for each of the five CO-CREATE countries (The Netherlands, Norway, Poland, Portugal, and the UK) and for Europe overall. Out of 10 possible intervention points tested, exercise, fruit, life dissatisfaction, school pressure, and skipping breakfast were identified as the top five most influential ones across the 24 cases. These model-based priorities can be compared with the policy ideas suggested by the CO-CREATE adolescents.

Modeling obesity in complex food systems: Systematic review

Obesity-related data derived from multiple complex systems spanning media, social, economic, food activity, health records, and infrastructure (sensors, smartphones, etc.) can assist us in understanding the relationship between obesity drivers for more efficient prevention and treatment. Reviewed literature shows a growing adaptation of the machine-learning model in recent years dealing with mechanisms and interventions in social influence, nutritional diet, eating behavior, physical activity, built environment, obesity prevalence prediction, distribution, and healthcare cost-related outcomes of obesity. Most models are designed to reflect through time and space at the individual level in a population, which indicates the need for a macro-level generalized population model. The model should consider all interconnected multi-system drivers to address obesity prevalence and intervention. This paper reviews existing computational models and datasets used to compute obesity outcomes to design a conceptual framework for establishing a macro-level generalized obesity model.

Tracing coalition changes in knowledge in and engagement with childhood obesity prevention to improve intervention implementation

BACKGROUND

While most coalition research focuses on studying the effects of peer relationship structure, this study examines the coevolution of coalition structure and behavior across three communities in the U.S. with the goal of identifying coalition dynamics that impact a childhood obesity prevention intervention.  METHODS: Over two years (2018-2020), three communities within the U.S. participated in a childhood obesity prevention intervention at different times. This intervention was guided by the Stakeholder-Driven Community Diffusion theory, which describes an empirically testable mechanism for promoting community change. Measures are part of the Stakeholder-driven Community Diffusion (SDCD) survey with demonstrated reliability, which include knowledge of and engagement with childhood obesity prevention and social networks. Data from three coalition-committees and their respective networks were used to build three different stochastic actor-oriented models. These models were used to examine the coevolution of coalition structure with coalition behavior (defined a priori as knowledge of and engagement with obesity prevention) among coalition-committee members and their nominated alters (Network A) and coalition-committee members only (Network B).  RESULTS: Overall, coalitions decrease in size and their structure becomes less dense over time. Both Network A and B show a consistent preference to form and sustain ties with those who have more ties. In Network B, there was a trend for those who have higher knowledge scores to increase their number of ties over time. The same trend appeared in Network A but varied based on their peers' knowledge in and engagement with childhood obesity prevention. Across models, engagement with childhood obesity prevention research was not a significant driver of changes in either coalition network structure or knowledge.

CONCLUSIONS

The trends in coalition Network A and B's coevolution models may point to context-specific features (e.g., ties among stakeholders) that can be leveraged for better intervention implementation. To that end, examining tie density, average path length, network diameter, and the dynamics of each behavior outcome (i.e., knowledge in and engagement with childhood obesity prevention) may help tailor whole-of-community interventions. Future research should attend to additional behavioral variables (e.g., group efficacy) that can capture other aspects of coalition development and that influence implementation, and to testing the efficacy of network interventions after trends have been identified.

A scoping review of systems approaches for increasing physical activity in populations

INTRODUCTION

The past decade has increasingly seen systems approaches as a featured theme in public health studies and policy documents. This trend is evident in the area of physical activity, which is a significant global health risk factor that is addressed in WHO's Global Action Plan on Physical Activity. We undertook a comprehensive scoping review to characterize the application of systems approaches to physical activity, to develop a typology of the objectives, themes and methods of research papers that purported to apply systems thinking to this issue.

METHODS

We searched electronic databases (PubMed, Web of Science, Scopus and PsycINFO) for studies published during the period 2010-2021 that explicitly applied systems approaches or methods to investigate and/or address population physical activity. A framework using systems-based methodological approaches was adapted to classify physical activity studies according to their predominant approach, covering basic descriptive, complex analytical and advanced forms of practice. We selected case studies from retained studies to depict the current "state of the art".

RESULTS

We included 155 articles in our narrative account. Literature reporting the application of systems approaches to physical activity is skewed towards basic methods and frameworks, with most attention devoted to conceptual framing and predictive modelling. There are few well-described examples of physical activity interventions which have been planned, implemented and evaluated using a systems perspective. There is some evidence of "retrofitted" complex system framing to describe programmes and interventions which were not designed as such.

DISCUSSION

We propose a classification of systems-based approaches to physical activity promotion together with an explanation of the strategies encompassed. The classification is designed to stimulate debate amongst policy-makers, practitioners and researchers to inform the further implementation and evaluation of systems approaches to physical activity.

CONCLUSION

The use of systems approaches within the field of physical activity is at an early stage of development, with a preponderance of descriptive approaches and a dearth of more complex analyses. We need to see movement towards a more sophisticated research agenda spanning the development, implementation and evaluation of systems-level interventions.

Applications of Complex Systems Models to Improve Retail Food Environments for Population Health: A Scoping Review

Retail food environments (RFEs) are complex systems with important implications for population health. Studying the complexity within RFEs comes with challenges. Complex systems models are computational tools that can help. We performed a systematic scoping review of studies that used complex systems models to study RFEs for population health. We examined the purpose for using the model, RFE features represented, extent to which the complex systems approach was maximized, and quality and transparency of methods employed. The PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) guidelines were followed. Studies using agent-based modeling, system dynamics, discrete event simulations, networks, hybrid, or microsimulation models were identified from 7 multidisciplinary databases. Fifty-six studies met the inclusion criteria, including 23 microsimulation, 13 agent-based, 10 hybrid, 4 system dynamics, 4 network, and 2 discrete event simulation models. Most studies (n = 45) used models for experimental purposes and evaluated effects of simulated RFE policies and interventions. RFE characteristics simulated in models were diverse, and included the features (e.g., prices) customers encounter when shopping (n = 55), the settings (e.g., restaurants, supermarkets) where customers purchase food and beverages (n = 30), and the actors (e.g., store managers, suppliers) who make decisions that influence RFEs (n = 25). All models incorporated characteristics of complexity (e.g., feedbacks, conceptual representation of multiple levels), but these were captured to varying degrees across model types. The quality of methods was adequate overall; however, few studies engaged stakeholders (n = 10) or provided sufficient transparency to verify the model (n = 12). Complex systems models are increasingly utilized to study RFEs and their contributions to public health. Opportunities to advance the use of these approaches remain, and areas to improve future research are discussed. This comprehensive review provides the first marker of the utility of leveraging these approaches to address RFEs for population health.

Knowledge Management as a Domain, System Dynamics as a Methodology

For decades, system dynamics has been utilised as a framework for evaluating and interpreting various types of systems with varying degrees of complexity and knowledge demands. Knowledge management is strongly related to system dynamics on a thematic level. We did a thorough review to identify potential applications and analysed system dynamics and knowledge management domains. The systematic review followed the PRISMA method. We identified two major groups and one subgroup of the combination of system dynamics and knowledge management after examining and categorising 45 papers. Articles were searched for on Web of Science, Scopus, and LENS. We then concentrated on the categorisation of articles by theme. We discovered that system dynamics models were used as a component of a decision support tool or a knowledge management system in some instances, or the integration of knowledge management processes into specific systems. This study contributes to the growth of system dynamics as a methodology capable of generating novel ideas, highlighting limitations, and providing analogies for future research in a variety of academic areas.

Agent-Based Modeling of Autosomal Recessive Deafness 1A (DFNB1A) Prevalence with Regard to Intensity of Selection Pressure in Isolated Human Population

An increase in the prevalence of autosomal recessive deafness 1A (DFNB1A) in populations of European descent was shown to be promoted by assortative marriages among deaf people. Assortative marriages became possible with the widespread introduction of sign language, resulting in increased genetic fitness of deaf individuals and, thereby, relaxing selection against deafness. However, the effect of this phenomenon was not previously studied in populations with different genetic structures. We developed an agent-based computer model for the analysis of the spread of DFNB1A. Using this model, we tested the impact of different intensities of selection pressure against deafness in an isolated human population over 400 years. Modeling of the "purifying" selection pressure on deafness ("No deaf mating" scenario) resulted in a decrease in the proportion of deaf individuals and the pathogenic allele frequency. Modeling of the "relaxed" selection ("Assortative mating" scenario) resulted in an increase in the proportion of deaf individuals in the first four generations, which then quickly plateaued with a subsequent decline and a decrease in the pathogenic allele frequency. The results of neutral selection pressure modeling ("Random mating" scenario) showed no significant changes in the proportion of deaf individuals or the pathogenic allele frequency after 400 years.

Applying a complex systems perspective to alcohol consumption and the prevention of alcohol-related harms in the 21st century: a scoping review

BACKGROUND AND AIMS

A complex systems perspective has been advocated to explore multi-faceted factors influencing public health issues, including alcohol consumption and associated harms. This scoping review aimed to identify studies that applied a complex systems perspective to alcohol consumption and the prevention of alcohol-related harms in order to summarize their characteristics and identify evidence gaps.

METHODS

Studies published between January 2000 and September 2020 in English were located by searching for terms synonymous with 'complex systems' and 'alcohol' in the Scopus, MEDLINE, Web of Science and Embase databases, and through handsearching and reference screening of included studies. Data were extracted on each study's aim, country, population, alcohol topic, system levels, funding, theory, methods, data sources, time-frames, system modifications and type of findings produced.

RESULTS

Eighty-seven individual studies and three systematic reviews were identified, the majority of which were conducted in the United States or Australia in the general population, university students or adolescents. Studies explored types and patterns of consumption behaviour and the local environments in which alcohol is consumed. Most studies focused on individual and local interactions and influences, with fewer examples exploring the relationships between these and regional, national and international subsystems. The body of literature is methodologically diverse and includes theory-led approaches, dynamic simulation models and social network analyses. The systematic reviews focused on primary network studies.

CONCLUSIONS

The use of a complex systems perspective has provided a variety of ways of conceptualizing and analyzing alcohol use and harm prevention efforts, but its focus ultimately has remained on predominantly individual- and/or local-level systems. A complex systems perspective represents an opportunity to address this gap by also considering the vertical dimensions that constrain, shape and influence alcohol consumption and related harms, but the literature to date has not fully captured this potential.

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.

Food environment solutions for childhood obesity in Latin America and among Latinos living in the United States

The food environment is a major contributor to unhealthy diets in children and, therefore, to the increasing rates of obesity. Acclaimed by scholars across the world, Latin American countries have been leaders in implementing policies that target different aspects of the food environment. Evidence on the nature and to what extent children are exposed and respond to unhealthy food environments in the region and among Latinos in the United States is, however, deficient. The objective of this review is to use the integrated International Network for Food and Obesity/noncommunicable diseases (NCDs) Research, Monitoring and Action Support (INFORMAS) framework to create healthy food environment to (i) compare the key elements of childhood obesity-related food environments in Latin America and for Latinos living in the United States; (ii) describe the evidence on solutions to improve childhood obesity-related food environments; and (iii) identify research priorities to inform solutions to fight childhood obesity in these populations. We found that an integrated body of evidence is needed to inform an optimal package of policies to improve food environments to which children in Latin America and Latino children in the United States are exposed and more efficiently translate policy solutions to help curb growing childhood obesity levels across borders.

Trends in the prevalence of adult overweight and obesity in Australia, and its association with geographic remoteness

The prevalence of overweight and obesity has been increasing globally and has become a significant public health concern in Australia in the two past decades. This study explores the most recent national prevalence and trends of adult overweight and obesity in Australia. It will also investigate geographic remoteness as a potential risk factor for an individual being overweight or obese in adulthood. A retrospective longitudinal study that utilised 14 successive waves (wave 6 through 19) of a nationally representative linked individual-level survey. Data was obtained from the Household, Income and Labour Dynamics in Australia survey. The data on 199,675 observations from 26,713 individuals aged ≥ 15 years over the period 2006 to 2019 was analysed. Random-effects logit model was employed to estimate the association between geographic remoteness and the risk of excessive weight gain. The results reveal that the prevalence of overweight, obesity and combined overweight and obesity among Australian adults in 2019 were 34%, 26% and 60%, respectively. The analysis shows that the prevalence of overweight and obesity varies by geographic remoteness. Adults from regional city urban (OR 1.53, 95% CI 1.16-2.03) and rural areas (OR 1.32, 95% CI 1.18-1.47) were more likely to be obese compared with their counterparts from major city urban areas. The results also show that adults living in major city urban areas, regional city urban areas, and regional city rural areas in Australia were 1.53 (OR 1.53, 95% CI 1.16-2.03), 1.32 (OR 1.32, 95% CI 1.18-1.47), and 1.18 (OR 1.18, 95% CI 1.08-1.29) times more likely to be overweight compared with their counterparts from major city urban areas in Australia. Substantial geographic variation in the prevalence of overweight and obesity exists among Australian adults and appears to be increasing. Public health measures should focus on contextual obesogenic factors and behavioural characteristics to curb the rising prevalence of adult obesity.

A systems map of the determinants of child health inequalities in England at the local level

Children and young people in the UK have worse health outcomes than in many similar western countries and child health inequalities are persistent and increasing. Systems thinking has emerged as a promising approach to addressing complex public health issues. We report on a systems approach to mapping the determinants of child health inequalities at the local level in England for young people aged 0-25, and describe the resulting map. Qualitative group concept mapping workshops were held in two contrasting English local authorities with a range of stakeholders: professionals (N = 35); children and young people (N = 33) and carers (N = 5). Initial area maps were developed, and augmented using data from qualitative interviews with professionals (N = 16). The resulting local maps were reviewed and validated by expert stakeholders in each area (N = 9; N = 35). Commonalities between two area-specific system maps (and removal of locality-specific factors) were used to develop a map that could be applied in any English local area. Two rounds of online survey (N = 21; N = 8) experts in public health, local governance and systems science refined the final system map displaying the determinants of child health inequalities. The process created a map of over 150 factors influencing inequalities in health outcomes for children aged 0-25 years at the local area level. The system map has six domains; physical environment, governance, economic, social, service, and personal. To our knowledge this is the first study taking a systems approach to addressing inequalities across all aspects of child health. The study shows how group concept mapping can support systems thinking at the local level. The resulting system map illustrates the complexity of factors influencing child health inequalities, and it may be a useful tool in demonstrating to stakeholders the importance of policies that tackle the systemic drivers of child health inequalities beyond those traditionally associated with public health.

Samnamul (Shoots of Aruncus dioicus) Inhibit Adipogenesis by Downregulating Adipocyte-Specific Transcription Factors in 3T3-L1 Adipocytes

Adipocyte-specific transcription factors and antioxidants are considered the best target of obesity. Aruncus dioicus var. kamtschaticus (A. dioicus, Samnamul) is easily available owing to edible and inexpensive. However, the anti-adipogenic effects of the underlying mechanism of A. dioicus extract (ADE) have not yet been reported. In the present study, we evaluate anti-adipogenic pathway in 3T3-L1 adipocytes, antioxidant activities and quantified phenolics using high-performance liquid chromatography of ADE. The results revealed ADE had reduced adipocyte differentiation (0.72-fold vs. MDI (media of differentiation) control), triglyceride (TG; 0.50-fold vs. MDI control, p < 0.001), and total cholesterol contents (0.77-fold vs. MDI control) by regulating adipocyte-specific transcription factors (C/EBPα, PPARγ, and SREBP1) and their downstream mRNA (AdipoQ, Ap2, SREBP1-c, and FAS) levels. Furthermore, ADE has higher total phenol and flavonoid contents and scavenging assay in the DPPH and ABTS+. In particularly, ADE contains chlorogenic acid (7.04 mg/kg), caffeic acid (20.14 mg/kg), ferulic acid (1.74 mg/kg), veratric acid (29.31 mg/kg), cinnamic acid (4.70 mg/kg), and quercetin (4.18 mg/kg). In conclusion, since these phenols, especially quercetin, in the ADE appear to reduce differentiation, TG and cholesterol content by regulating adipocyte-specific transcription factors in adipocytes, ADE has the potential to be developed into a new antioxidant and anti-obesity therapeutics.

Fetal and Placental Weight in Pre-Gestational Maternal Obesity (PGMO) vs. Excessive Gestational Weight Gain (EGWG)-A Preliminary Approach to the Perinatal Outcomes in Diet-Controlled Gestational Diabetes Mellitus

Both pre-gestational maternal obesity (PGMO) and excessive gestational weight gain (EGWG) increase the risk of gestational diabetes mellitus (GDM). Here, we conducted a retrospective study to comparatively examine the relation between fetal birth weight (FW) and placental weight (PW) in PGMO (n = 100) compared to EGWG (n = 100) with respect to perinatal outcomes in diet-controlled GDM. The control group was made up of 100 healthy pregnancies. The mean FW and the mean PW in EGWG were correlated with lowered fetal weight/placental weight ratio (FW/PW ratio). The percentage of births completed by cesarean section accounted for 47%, 32%, and 18% of all deliveries (EGWG, PGMO, and controls, respectively), with the predominance of FW-related indications for cesarean section. Extended postpartum hospital stays due to neonate were more frequent in EGWG, especially due to neonatal jaundice (p < 0.05). The results indicate the higher perinatal risk in mothers with EGWG compared to PGMO during GDM-complicated pregnancy. Further in-depth comparative studies involving larger patient pools are needed to validate these findings, the intent of which is to formulate guidelines for GDM patients in respect to management of PGMO and EGWG.

Using a system dynamics model to study the obesity transition by socioeconomic status in Colombia at the country, regional and department levels

OBJECTIVE

We study the obesity transition by socioeconomic status (SES), gender and age within the Colombian urban population at the country, regional and department levels.

DESIGN

The study is informed by cross-sectional data from the 2005 and 2010 ENSIN survey. We used these data to develop a system dynamics model that simulates the dynamics of obesity by body mass index (BMI) categories, gender and SES at the country, regional and department levels from 2005 to 2030.

PARTICIPANTS

The sample size of the 2005 ENSIN comprised 8515 children younger than 5 years, 32 009 children and adolescents aged 5-17 years and 48 056 adults aged 18-64 years. In 2010, the corresponding numbers were 11 368, 32 524 and 64 425, respectively.

PRIMARY AND SECONDARY OUTCOME MEASURE

The obesity prevalence ratio and prevalence rates for each BMI category.

RESULTS

The results show, at the country level, transitions from overweight to obesity were projected to increase sharply among lower SES adults, particularly among women, suggesting that these groups will undergo an obesity transition by 2030. The model projections also indicate that the regions of Colombia are in different stages of the obesity transition. In the case of women, five out of the six regions were expected to undergo an obesity transition by SES over time. For men, only one region was expected to undergo an obesity transition. However, at the department level, trends in the burden of obesity varied.

CONCLUSIONS

We evidence that the Colombian population could be experiencing an obesity transition where the increase in the GDP could be related to shifts in the burden of obesity from higher to lower SES, especially in women. These patterns support the need for policy planning that considers SES and gender, at the national and subnational levels, as important determinants of overweight and obesity among adults in Colombia.

Developing a Socioculturally Nuanced Systems Model of Childhood Obesity in Manhattan's Chinese American Community via Group Model Building

The purpose of this study was to develop a qualitative and socioculturally tailored systems model of childhood obesity in the Chinese American community in Manhattan's Chinatown. We utilized group model building (GMB) methodology as a form of participatory systems modeling. The study was conducted in Manhattan's Chinatown community. We recruited 16 Chinese American adults from the community. GMB workshops engendered a causal loop diagram (CLD), the visualization of a complex systems model illustrating the structures, feedbacks, and interdependencies among socioculturally specific pathways underlying childhood obesity, in Manhattan's Chinatown community. The analysis of CLD revealed that participants considered the following factors to influence childhood obesity: (1) traditional social norms affecting body image, how children are raised, parental pressure to study, and trust in health of traditional foods; (2) grandparents' responsibility for children; (3) limited time availability of parents at home; and (4) a significant amount of children's time spent indoors. GMB represents a novel method to understand the complexity of childhood obesity in culturally specific populations and contexts. The study identified sociocultural subsystems that may underlie the development and perpetuation of childhood obesity among Chinese American children. Insights from the study can be useful in the design of future empirical studies and interventions.