Reducing Income Inequalities in Food Consumption: Explorations With an Agent-Based Model

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.

Analysis of how a complex systems perspective is applied in studies on socioeconomic inequalities in health and health behaviour-a call for reporting guidelines

BACKGROUND

A complex systems perspective is gaining popularity in research on socioeconomic inequalities in health and health behaviour, though there may be a gap between its popularity and the way it is implemented. Building on our recent systematic scoping review, we aim to analyse the application of and reporting on complex systems methods in the literature on socioeconomic inequalities in health and health behaviour.

METHODS

Selected methods and results from the review are presented as a basis for in-depth critical reflection. A traffic light-based instrument was used to assess the extent to which eight key concepts of a complex systems perspective (e.g. feedback loops) were applied. Study characteristics related to the applied value of the models were also extracted, including the model evidence base, the depiction of the model structure, and which characteristics of model relationships (e.g. polarity) were reported on.

RESULTS

Studies that applied more key concepts of a complex systems perspective were also more likely to report the direction and polarity of relationships. The system paradigm, its deepest held beliefs, is seldom identified but may be key to recognize when designing interventions. A clear, complete depiction of the full model structure is also needed to convey the functioning of a complex system. We recommend that authors include these characteristics and level of detail in their reporting.

CONCLUSIONS

Above all, we call for the development of reporting guidelines to increase the transparency and applied value of complex systems models on socioeconomic inequalities in health, health behaviour and beyond.

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.

Economic Growth, Income Inequality and Food Safety Risk

Food safety risk, as an implicit cost of social and economic development, endangers the health of global residents, including China. To systematically understand the impact of socioeconomic development on food safety risk and to establish a sound modern governance system of food safety in China, this paper uses provincial panel data from 2011 to 2020 to explore the relationship between food safety risk and socio-economic development factors such as economic growth and income inequality by employing a two-way fixed effect model and moderating effect model. The results show that the food safety risk is a Kuznets curve, and the turning point is about RMB 58,104.59 per capita GDP (based on prices in 2011). However, under the moderating effect of income inequality, the turning point of the Kuznets curve of food safety risk will shift to the right, and the curve will be flattened. In other words, income inequality has a negative moderating effect on the "inverted U-shaped" relationship between economic growth and food safety risk. When dealing with food safety problems, the goal of stable and sustained economic growth and common prosperity should be incorporated into policy formulation to enhance the governance effectiveness of food safety risk.

Agent-Based Modelling of Health Inequalities following the Complexity Turn in Public Health: A Systematic Review

There is an increasing focus on the role of complexity in public health and public policy fields which has brought about a methodological shift towards computational approaches. This includes agent-based modelling (ABM), a method used to simulate individuals, their behaviour and interactions with each other, and their social and physical environment. This paper aims to systematically review the use of ABM to simulate the generation or persistence of health inequalities. PubMed, Scopus, and Web of Science (1 January 2013-15 November 2022) were searched, supplemented with manual reference list searching. Twenty studies were included; fourteen of them described models of health behaviours, most commonly relating to diet (n = 7). Six models explored health outcomes, e.g., morbidity, mortality, and depression. All of the included models involved heterogeneous agents and were dynamic, with agents making decisions, growing older, and/or becoming exposed to different health risks. Eighteen models represented physical space and in eleven models, agents interacted with other agents through social networks. ABM is increasingly contributing to our understanding of the socioeconomic inequalities in health. However, to date, the majority of these models focus on the differences in health behaviours. Future research should attempt to investigate the social and economic drivers of health inequalities using ABM.

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.

A Bibliometric Analysis on Research Regarding Residential Segregation and Health Based on CiteSpace

Considerable scholarly attention has been directed to the adverse health effects caused by residential segregation. We aimed to visualize the state-of-the-art residential segregation and health research to provide a reference for follow-up studies. Employing the CiteSpace software, we uncovered popular themes, research hotspots, and frontiers based on an analysis of 1211 English-language publications, including articles and reviews retrieved from the Web of Science Core Collection database from 1998 to 2022. The results revealed: (1) The Social Science & Medicine journal has published the most studies. Roland J. Thorpe, Thomas A. LaVeist, Darrell J. Gaskin, David R. Williams, and others are the leading scholars in residential segregation and health research. The University of Michigan, Columbia University, Harvard University, the Johns Hopkins School of Public Health, and the University of North Carolina play the most important role in current research. The U.S. is the main publishing country with significant academic influence. (2) Structural racism, COVID-19, mortality, multilevel modelling, and environmental justice are the top five topic clusters. (3) The research frontier of residential segregation and health has significantly shifted from focusing on community, poverty, infant mortality, and social class to residential environmental exposure, structural racism, and health care. We recommend strengthening comparative research on the health-related effects of residential segregation on minority groups in different socio-economic and cultural contexts.

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.

Effect of Household Income on Short-Term Outcomes Following Cerebellopontine Angle Tumor Resection

Objectives  The objective of this study is to elucidate the impact of income on short-term outcomes in a cerebellopontine angle (CPA) tumor resection population. Design  This is a retrospective regression analysis. Setting  This study was done at a single, multihospital, urban academic medical center. Participants  Over 6 years (from June 7, 2013, to April 24, 2019), 277 consecutive CPA tumor cases were reviewed. Main Outcome Measures  Outcomes studied included readmission, emergency department evaluation, unplanned return to surgery, return to surgery after index admission, and mortality. Univariate analysis was conducted among the entire population with significance set at a p -value <0.05. The population was divided into quartiles based on median household income and univariate analysis conducted between the lowest (quartile 1 [Q1]) and highest (quartile 4 [Q4]) socioeconomic quartiles, with significance set at a p -value <0.05. Stepwise regression was conducted to determine the correlations among study variables and to identify confounding factors. Results  Regression analysis of 273 patients demonstrated decreased rates of unplanned reoperation ( p  = 0.015) and reoperation after index admission ( p  = 0.035) at 30 days with higher standardized income. Logistic regression between the lowest (Q1) and highest (Q4) socioeconomic quartiles demonstrated decreased unplanned reoperation ( p  = 0.045) and decreasing but not significant reoperation after index admission ( p  = 0.15) for Q4 patients. No significant difference was observed for other metrics of morbidity and mortality. Conclusion  Higher socioeconomic status is associated with decreased risk of unplanned reoperation following CPA tumor resection.

Socioeconomic Inequalities in Food Consumption: A Cross-Sectional Study in Portuguese Adults

Background

Food is a major determinant of chronic noncommunicable diseases. Because of this, social inequalities in food consumption will likely produce social inequalities in disease and life expectancy.

Objectives

This study analyses the social inequalities in food consumption in Portugal and whether they differ between men and women and between younger and older people.

Methods

Following a cross-sectional observational study, we analyzed data from 11,085 individuals aged 25-64 years who participated in the 2014 National Health Interview Survey (NHIS). Logistic regression models were used to measure the association between socioeconomic conditions, i.e., education and income, and food consumption. The analysis was then stratified by sex and age.

Results

A positive gradient for income and education was observed in the consumption of fish, cakes, natural juices, and dairy products. The consumption of legumes and soft drinks was inversely related to income and education. A socioeconomic gradient for fruits and vegetables was observed only among women and older people. Worse-off people consumed less soup, and underprivileged women consumed fewer fast-food products.

Conclusion

The food consumption patterns of Portuguese adults are related to their socioeconomic condition, with few variations across demographic categories.

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.

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.

Place-Based Diminished Returns of Parental Educational Attainment on School Performance of Non-Hispanic White Youth

BACKGROUND

Youth educational outcomes are a function of a wide range of factors including parental education level. This effect, however, is shown to be smaller for African American, Hispanic, and Asian American youth, a pattern called Marginalization-related Diminished Returns (MDRs). It is, however, unknown if it is race/ethnicity or other conditions associated with race/ethnicity (e.g., poor neighborhood quality) which reduces the marginal returns of parental education for youth.

AIM

To explore whether MDRs are only due to race/ethnicity or if they also remain for non-Hispanic Whites in poor neighborhoods, we compared the association between parental education level and adolescents' school performance based on neighborhood quality in a nationally representative sample of non-Hispanic Whites in the United States.

METHODS

This cross-sectional study used wave 1 of the Add Health study, an ongoing nationally representative cohort, 1994-2019. Participants included 849 non-Hispanic White adolescents between the ages of 12 and 21 years and their parents. The independent variable was parental education level, which was treated as a continuous measure. Age, grade, gender, and parental marital status were the covariates. The dependent variable was school performance (sum of school grades in Math, English, History, and Science). Linear regression models were used for data analysis.

RESULTS

Overall, worse neighborhood quality was associated with worse school performance. Parental education level, however, was not directly associated with youth school performance. We found a statistically significant interaction between parental education level and neighborhood quality suggesting that the strength of the association between parental education and youth school performance weakens as neighborhood quality declines.

CONCLUSION

Parental education level is a more salient determinant of youth educational outcomes in better neighborhoods. The result suggests that MDRs may not be solely due to race/ethnicity but contextual factors that commonly covary with marginalization and poverty. These contextual factors may include segregation, concentration of poverty, and social and physical neighborhood disorder.

A narrative review of the use of agent-based modeling in health behavior and behavior intervention

Studies of health behaviors and behavior intervention have begun to explore the potential of agent-based modeling (ABM). A review of how ABMs have been used in health behavior, behavior intervention, and corresponding insights is warranted. The goal of this study was to provide a narrative review of the applications of ABMs in health behavior change and intervention. I will focus on two perspectives: (a) the mechanism of behavior and behavior change and (b) ABMs' use for behavior intervention. I identified and reviewed 17 ABMs applied to behaviors including physical activity, diet, alcoholic drinking, smoking, and drug use. Among these ABMs, I grouped their mechanisms of behavior change into four categories and evaluated the advantages and disadvantages of each mechanism. For behavior intervention, I evaluated the use of ABMs on levels of individual, interpersonal, and neighborhood environment. Various behavior change mechanisms and simplifications existed because of our limited knowledge of behaviors at the individual level. Utility maximization was the most frequently used mechanism. ABMs offered insights for behavior intervention including the benefits of upstream interventions and multilevel intervention, as well as balances among various factors, outcomes, and populations. ABMs have been used to model a diversity of behaviors, populations, and interventions. The use of ABMs in health behavior is at an early stage, and a major challenge is our limited knowledge of behaviors at the individual level.

Complex Systems Approaches to Diet: A Systematic Review

CONTEXT

Complex systems approaches can help to elucidate mechanisms that shape population-level patterns in diet and inform policy approaches. This study reports results of a structured review of key design elements and methods used by existing complex systems models of diet.

EVIDENCE ACQUISITION

The authors conducted systematic searches of the PubMed, Web of Science, and LILACS databases between May and September 2018 to identify peer-reviewed manuscripts that used agent-based models or system dynamics models to explore diet. Searches occurred between November 2017 and May 2018. The authors extracted relevant data regarding each study's diet and nutrition outcomes; use of data for parameterization, calibration, and validation; results; and generated insights. The literature search adhered to PRISMA guidelines.

EVIDENCE SYNTHESIS

Twenty-two agent-based model studies and five system dynamics model studies met the inclusion criteria. Mechanistic studies explored neighborhood- (e.g., residential segregation), interpersonal- (e.g., social influence) and individual-level (e.g., heuristics that guide food purchasing decisions) mechanisms that influence diet. Policy-oriented studies examined policies related to food pricing, the food environment, advertising, nutrition labels, and social norms. Most studies used empirical data to inform values of key parameters; studies varied in their approaches to calibration and validation.

CONCLUSIONS

Opportunities remain to advance the state of the science of complex systems approaches to diet and nutrition. These include using models to better understand mechanisms driving population-level diet, increasing use of models for policy decision support, and leveraging the wide availability of epidemiologic and policy evaluation data to improve model validation.

The impact of individual and environmental interventions on income inequalities in sports participation: explorations with an agent-based model

Background

Income inequalities in sports participation are shaped by a system in which individuals and the environment interact. We developed an agent-based model (ABM) that could represent this system and used it to provide a proof-of-concept of its potential to explore the impact of individual and environmental interventions on reducing inequalities in sports participation.

Methods

Our ABM simulates sports participation of individuals in the Dutch city of Eindhoven. In the model, sports participation is determined by an individual’s tendency to start sports (at a fitness center, sports club or self-organized), which is influenced by attributes of individuals (i.e. age, sex, income), sports facilities (i.e. price, accessibility) and the social environment (i.e. social cohesion, social influence). Sports facilities can adapt to changes in the demand by closures or startups, which in turn influence the tendency of individuals to participate in sport. We explored the impact of five interventions scenarios.

Results

Explorative results show that providing health education, increasing the availability of sports facilities, lowering prices of facilities and improving safety levels can increase sports participation and modestly reduce absolute income inequalities in sports participation. The largest gain can be attained through health education, if the effect and reach is sufficiently large. Environmental interventions alone have a modest impact. Marked effects are only achieved after five to 10 years.

Conclusions

ABMs have much potential to test the population-level effects of various interventions in the context of a system. Our study highlights the challenges of ABM development and reveals gaps in empirical data. With further refinements, our model could aid in understanding and finding optimal pathways to reduce income inequalities in sports participation.

Electronic supplementary material

The online version of this article (10.1186/s12966-018-0740-y) contains supplementary material, which is available to authorized users.

Complex adaptive systems: a new approach for understanding health practices

This article explores the potential of complex adaptive systems (CAS) theory to inform behaviour change research. A CAS describes a collection of heterogeneous agents interacting within a particular context, adapting to each other's actions. In practical terms, this implies that behaviour change is (1) socially and culturally situated; (2) highly sensitive to small baseline differences in individuals, groups, and intervention components; and (3) determined by multiple components interacting 'chaotically'. Two approaches to studying CAS are briefly reviewed. Agent-based modelling is a computer simulation technique that allows researchers to investigate 'what if' questions in a virtual environment. Applied qualitative research techniques, on the other hand, offer a way to examine what happens when an intervention is pursued in real-time, and to identify the sorts of rules and assumptions governing social action. Although these represent very different approaches to complexity, there may be scope for mixing these methods - for example, by grounding models in insights derived from qualitative fieldwork. Finally, I will argue that the concept of CAS offers one opportunity to gain a deepened understanding of health-related practices, and to examine the social psychological processes that produce health-promoting or damaging actions.

Designing an Agent-Based Model Using Group Model Building: Application to Food Insecurity Patterns in a U.S. Midwestern Metropolitan City

Recent advances in computing resources have increased interest in systems modeling and population health. While group model building (GMB) has been effectively applied in developing system dynamics models (SD), few studies have used GMB for developing an agent-based model (ABM). This article explores the use of a GMB approach to develop an ABM focused on food insecurity. In our GMB workshops, we modified a set of the standard GMB scripts to develop and validate an ABM in collaboration with local experts and stakeholders. Based on this experience, we learned that GMB is a useful collaborative modeling platform for modelers and community experts to address local population health issues. We also provide suggestions for increasing the use of the GMB approach to develop rigorous, useful, and validated ABMs.

Agent-Based Modeling in Public Health: Current Applications and Future Directions

Agent-based modeling is a computational approach in which agents with a specified set of characteristics interact with each other and with their environment according to predefined rules. We review key areas in public health where agent-based modeling has been adopted, including both communicable and noncommunicable disease, health behaviors, and social epidemiology. We also describe the main strengths and limitations of this approach for questions with public health relevance. Finally, we describe both methodologic and substantive future directions that we believe will enhance the value of agent-based modeling for public health. In particular, advances in model validation, comparisons with other causal modeling procedures, and the expansion of the models to consider comorbidity and joint influences more systematically will improve the utility of this approach to inform public health research, practice, and policy.

Rebates to Incentivize Healthy Nutrition Choices in the Supplemental Nutrition Assistance Program

Price incentives, or rebates, have been proposed as one promising strategy for improving diet quality among Supplemental Nutrition Assistance Program participants. This paper explores the existing evidence on effectiveness of rebates in this program. In particular, this paper considers findings from a recent RCT of Supplemental Nutrition Assistance Program rebates, the U.S. Department of Agriculture Healthy Incentives Pilot, in the context of the broader literature on rebate strategies. The paper concludes that rebates have a moderate impact on food intake, at moderate cost relative to alternative interventions. There is further evidence that implicit promotional effects may contribute to impacts of rebate interventions, beyond the impacts of price effects alone. However, existing studies on complementary effects of explicit promotion have been limited by relatively small sample sizes and correspondingly low power to detect differences. This appears to be a promising area for future research.

Social Determinants of Population Health: A Systems Sciences Approach

Population distributions of health emerge from the complex interplay of health-related factors at multiple levels, from the biological to the societal level. Individuals are aggregated within social networks, affected by their locations, and influenced differently across time. From aggregations of individuals, group properties can emerge, including some exposures that are ubiquitous within populations but variant across populations. By combining a focus on social determinants of health with a conceptual framework for understanding how genetics, biology, behavior, psychology, society, and environment interact, a systems science approach can inform our understanding of the underlying causes of the unequal distribution of health across generations and populations, and can help us identify promising approaches to reduce such inequalities. In this paper, we discuss how systems science approaches have already made several substantive and methodological contributions to the study of population health from a social epidemiology perspective.