Examining disparities in food accessibility among households in Columbus, Ohio: an agent-based model

A systematic review of the impact of food security governance measures as simulated in modelling studies

To effectively address food security, we need tools that assess governance measures (for example, strategic storage reserves, cash transfers or trade regulations) ex ante. Simulation models can estimate the impact of such measures via scenarios with differently governed food systems. On the basis of a systematic review of 110 simulation studies published over 2000-2021, we examined how food security governance has been represented, and identified needs for future simulation model development. We found that studies commonly used agent-based, system dynamics, and computable general equilibrium models; tended to be production, trade or consumption centric; assessed the impact of a wide variety of mostly treasure- or authority-based measures; and applied diverse food security indicators, mostly of access or availability. We also identified blind spots (for example, simulation of nodal measures) and proposed how to address these blind spots (for example, telecoupling) and to make food security governance simulation studies fit for meta-analyses (for example, harmonizing food security indicators for comparison).

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.

Smart city lifestyle sensing, big data, geo-analytics and intelligence for smarter public health decision-making in overweight, obesity and type 2 diabetes prevention: the research we should be doing

The public health burden caused by overweight, obesity (OO) and type-2 diabetes (T2D) is very significant and continues to rise worldwide. The causation of OO and T2D is complex and highly multifactorial rather than a mere energy intake (food) and expenditure (exercise) imbalance. But previous research into food and physical activity (PA) neighbourhood environments has mainly focused on associating body mass index (BMI) with proximity to stores selling fresh fruits and vegetables or fast food restaurants and takeaways, or with neighbourhood walkability factors and access to green spaces or public gym facilities, making largely naive, crude and inconsistent assumptions and conclusions that are far from the spirit of 'precision and accuracy public health'. Different people and population groups respond differently to the same food and PA environments, due to a myriad of unique individual and population group factors (genetic/epigenetic, metabolic, dietary and lifestyle habits, health literacy profiles, screen viewing times, stress levels, sleep patterns, environmental air and noise pollution levels, etc.) and their complex interplays with each other and with local food and PA settings. Furthermore, the same food store or fast food outlet can often sell or serve both healthy and non-healthy options/portions, so a simple binary classification into 'good' or 'bad' store/outlet should be avoided. Moreover, appropriate physical exercise, whilst essential for good health and disease prevention, is not very effective for weight maintenance or loss (especially when solely relied upon), and cannot offset the effects of a bad diet. The research we should be doing in the third decade of the twenty-first century should use a systems thinking approach, helped by recent advances in sensors, big data and related technologies, to investigate and consider all these factors in our quest to design better targeted and more effective public health interventions for OO and T2D control and prevention.

Evaluation of public health interventions from a complex systems perspective: A research methods review

INTRODUCTION

Applying a complex systems perspective to public health evaluation may increase the relevance and strength of evidence to improve health and reduce health inequalities. In this review of methods, we aimed to: (i) classify and describe different complex systems methods in evaluation applied to public health; and (ii) examine the kinds of evaluative evidence generated by these different methods.

METHODS

We adapted critical review methods to identify evaluations of public health interventions that used systems methods. We conducted expert consultation, searched electronic databases (Scopus, MEDLINE, Web of Science), and followed citations of relevant systematic reviews. Evaluations were included if they self-identified as using systems- or complexity-informed methods and if they evaluated existing or hypothetical public health interventions. Case studies were selected to illustrate different types of complex systems evaluation.

FINDINGS

Seventy-four unique studies met our inclusion criteria. A framework was developed to map the included studies onto different stages of the evaluation process, which parallels the planning, delivery, assessment, and further delivery phases of the interventions they seek to inform; these stages include: 1) theorising; 2) prediction (simulation); 3) process evaluation; 4) impact evaluation; and 5) further prediction (simulation). Within this framework, we broadly categorised methodological approaches as mapping, modelling, network analysis and 'system framing' (the application of a complex systems perspective to a range of study designs). Studies frequently applied more than one type of systems method.

CONCLUSIONS

A range of complex systems methods can be utilised, adapted, or combined to produce different types of evaluative evidence. Further methodological innovation in systems evaluation may generate stronger evidence to improve health and reduce health inequalities in our complex world.

The Food Environments of Fruit and Vegetable Consumption in East and Southeast Asia: A Systematic Review

Fruit and vegetable (FV) consumption benefits the health of populations. This can be especially the case in locations which have undergone significant changes in their food environments, such as East and Southeast Asian countries. This current systematic review is the first to study the food environments—facilitators, barriers, and moderators—associated with FV consumption in East and Southeast Asia. We consulted five electronic academic databases of English peer-reviewed papers published between 2010 and 2020 and found 31 studies. Results of these studies show that individuals strongly perceive FVs as being high-quality and safe, and having trust in their benefits. Food businesses with modernized systems have significantly fostered the consumption of FVs. A main barrier to FV consumption, however, is financial concerns, exacerbated by food businesses with FV unavailability and urbanization-induced FV price inflation and dietary patterns. Demographics and shopping patterns further hinder FV consumption. The fragmented and conditionalized findings of the 31 studies require standardized FV consumption measurements. Unlike the impact of FV consumption determinants and their interactions in Western countries, those in Asia, particularly countries other than China, have been substantially understudied. Therefore, as the research gaps in studies of food environments and FV consumption in East and Southeast Asia urgently demand scholarly attention, this paper proposes recommendations that favour the consumption of FVs.

The dynamics of food shopping behavior: Exploring travel patterns in low-income Detroit neighborhoods experiencing extreme disinvestment using agent-based modeling

Only a handful of studies have leveraged agent-based models (ABMs) to examine public health outcomes and policy interventions associated with uneven urban food environments. While providing keen insights about the role of ABMs in studying urban food environments, these studies underutilize real-world data on individual behavior in their models. This study provides a unique contribution to the ABM and food access literature by utilizing survey data to develop an empirically-rich spatially-explicit ABM of food access. This model is used to simulate and scrutinize individual travel behavior associated with accessing food in low-income neighborhoods experiencing disinvestment in Detroit (Michigan), U.S. In particular, the relationship between trip frequencies, mode of travel, store choice, and distances traveled among individuals grouped into strata based on selected sociodemographic characteristics, including household income and age, is examined. Results reveal a diversified picture of not only how income and age shape food shopping travel but also the different thresholds of tolerance for non-motorized travel to stores. Younger and poorer population subgroups have a higher propensity to utilize non-motorized travel for shopping than older and wealthier subgroups. While all groups tend to travel considerable distances outside their immediate local food environment, different sociodemographic groups maintain unique spatial patterns of grocery-shopping behavior throughout the city and the suburbs. Overall, these results challenge foundational tenets in urban planning and design, regarding the specific characteristics necessary in the built environment to facilitate accessibility to urban amenities, such as grocery stores. In neighborhoods experiencing disinvestment, sociodemographic conditions play a more important role than the built environment in shaping food accessibility and ultimately travel behavior.

Mapping disruption and resilience mechanisms in food systems

This opinion article results from a collective analysis by the Editorial Board of Food Security. It is motivated by the ongoing covid-19 global epidemic, but expands to a broader view on the crises that disrupt food systems and threaten food security, locally to globally. Beyond the public health crisis it is causing, the current global pandemic is impacting food systems, locally and globally. Crises such as the present one can, and do, affect the stability of food production. One of the worst fears is the impacts that crises could have on the potential to produce food, that is, on the primary production of food itself, for example, if material and non-material infrastructure on which agriculture depends were to be damaged, weakened, or fall in disarray. Looking beyond the present, and not minimising its importance, the covid-19 crisis may turn out to be the trigger for overdue fundamental transformations of agriculture and the global food system. This is because the global food system does not work well today: the number of hungry people in the world has increased substantially, with the World Food Programme warning of the possibility of a "hunger pandemic". Food also must be nutritious, yet unhealthy diets are a leading cause of death. Deepening crises impoverish the poorest, disrupt food systems, and expand "food deserts". A focus on healthy diets for all is all the more relevant when everyone's immune system must react to infection during a global pandemic. There is also accumulating and compelling evidence that the global food system is pushing the Earth system beyond the boundaries of sustainability. In the past twenty years, the growing demand for food has increasingly been met through the destruction of Earth's natural environment, and much less through progress in agricultural productivity generated by scientific research, as was the case during the two previous decades. There is an urgent need to reduce the environmental footprint of the global food system: if its performances are not improved rapidly, the food system could itself be one main cause for food crises in the near future. The article concludes with a series of recommendations intended for policy makers and science leaders to improve the resilience of the food system, global to local, and in the short, medium and long term.

Income Segregation and Access to Healthy Food

INTRODUCTION

Differences in diet quality across socioeconomic groups are a key contributor to health gradient. An agent-based model was developed to explore how income segregation affects food access for poor households under idealized circumstances where the poor have the same knowledge of and preferences for healthy food as the nonpoor.

METHODS

The agent-based model featured households with heterogeneous incomes and automobile ownership characteristics on the basis of 2016 U.S. Census Bureau data. Households had identical preferences and were perfectly informed about the prices and availability of food products in different grocery stores. The model featured 2 fully informed competing grocery stores that chose their locations, product lines, and prices to maximize profits. The model was simulated for different levels of income segregation. The model in this article was created and analyzed in 2019.

RESULTS

With no segregation, the rich and the poor households had comparatively equal access to grocery stores (in terms of travel distance) and healthy food (in terms of availability). With high segregation, poor households were forced to travel farther for groceries and may find healthy food unavailable at the grocery stores closest to their homes. Incentivizing grocery stores to locate equitably would require offering them substantial subsidies.

CONCLUSIONS

The model demonstrates that even under idealized conditions of perfect information and fully rational consumers, income segregation leads to adverse consequences for healthy food access by the poor. Agent-based modeling is useful to explore important hypothetical scenarios and should be considered as one of many worthwhile complementary frameworks to study complex topics.