Connecting micro dynamics and population distributions in system dynamics models

Caloric reductions needed to achieve obesity goals in Mexico for 2030 and 2040: A modeling study

BACKGROUND

In Mexico, obesity prevalence among adults increased from 23% in 2000 to 36% in 2018, approximately. Mexico has not defined short- or long-term obesity goals, obscuring the level of effort required to achieve a relevant impact. We aimed to explore potential obesity goals for 2030 and 2040 in Mexico and to estimate the required caloric reductions to achieve them.

METHODS AND FINDINGS

We obtained anthropometric and demographic information on the Mexican adult population (age ≥20 years) from the Health and Nutrition Surveys conducted in 2000, 2006, 2012, 2016, and 2018 (n = 137,907). Each survey wave is cross-sectional, multistage, and representative of the Mexican population at the national, regional, and urban/rural levels. Obesity prevalence was projected for 2030 and 2040 by combining population projections of energy intake by socioeconomic status (SES) with a weight-change microsimulation model taking into account individual-level information on sex, age, physical activity, and initial body weight and height. If current trends continue, Mexico's obesity prevalence is expected to increase from 36% (95% CI 35% to 37%) in 2018 to 45% (uncertainty interval [UI] 41% to 48%) in 2030 and to 48% (UI 41% to 55%) in 2040. Based on expert opinion, we identified 3 obesity goals scenarios: (1) plausible (38% in 2030 and 36% in 2040); (2) intermediate (33% in 2030 and 29% in 2040); and (3) ideal based on the average prevalence of Organization for Economic Co-operation and Development countries (OECD; 19%). We estimated the caloric reductions needed to achieve the goal scenarios using the microsimulation model. Obesity was projected to increase more rapidly in the low SES (around 34% in 2018 to 48% (UI 41% to 55%) in 2040), than in the middle (around 38% to 52% (UI 45% to 56%)), or high SES group (around 36% to 45% (UI 36% to 54%)). Caloric reductions of 40 (UI 13 to 60), 75 (UI 49 to 95), and 190 (UI 163 to 215) kcal/person/day would be needed to reach the plausible, intermediate, and the ideal (OECD) average scenarios for 2030, respectively. To reach the 2040 goals, caloric reductions of 74 (UI 28 to 114), 124 (UI 78 to 169), and 209 (UI 163 to 254) kcal/person/day would be required, respectively. Study limitations include assuming a constant and sedentary physical activity level, not considering cohort-specific differences that could occur in the future, and assuming the same caloric trends under no intervention and the obesity goal scenarios.

CONCLUSIONS

To reach the 3 obesity goals in 2040, caloric reductions between 74 and 209 kcal/day/person would be needed in Mexico. A package of new and stronger interventions should be added to existing efforts such as food taxes and warning labels on non-nutritious food.

Trends in adults' energy imbalance gaps over two decades in Belgium using system dynamics modelling

BACKGROUND

The energy imbalance gap (EIG) represents the average daily difference between energy intake and energy expenditure. The maintenance energy gap (MEG) captures the increased energy intake needed to maintain a higher average bodyweight compared with an initial distribution of bodyweight. This study quantified the dynamics of the EIG and MEG over time and across different genders/regions/BMI groups for Belgian adults.

METHODS

A validated system dynamics model was adapted to estimate the trends/dynamics of the EIG among different subpopulations over two decades in Belgium. The model was calibrated using data from the six Belgian national Health Interview Surveys (1997, 2001, 2004, 2008, 2013, 2018).

RESULTS

EIG was negative for all BMI groups among Belgian females in 2018, implying the start of a decrease in prevalence of overweight/obesity in this subpopulation. However, this was not the case among Belgian males. Flemish and Walloon males had positive EIGs across BMI groups in 2018, however, Brussels' males showed negative EIGs across BMI groups. Flemish and Brussels' females showed negative EIGs across all BMI groups in 2018, while Walloon females showed positive EIGs across almost all BMI groups. According to the MEG, Belgian men consumed (and expended) on average 59 kcal/day more in 2018 than in 1997 to maintain their heavier body weight. The MEG for Belgian women was 46 kcal/day in 2018, triple the MEG in 2004.

CONCLUSIONS

The detailed heterogeneous trends of the EIG describe the obesity patterns for different subpopulations in Belgium and could be used to model the differential effects of specific nutrition policies targeting energy intake.

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.

Trends in Energy Imbalance Gap and Body Weight Status in the Japanese Adult Population: A System Dynamics Approach

Background

The double burden of malnutrition is a growing public health problem in Japan. We estimated the dynamics of the energy imbalance gap (EIG) (average daily difference between energy intake and expenditure) to explain trends in the prevalence of underweight, overweight, and obese Japanese adults.

Methods

We used individual-level data on body height and weight from the National Health and Nutrition Surveys from 1975 to 2015. We calibrated a validated system dynamics model to estimate the EIG for Japanese adults aged 20 to 74 years by survey year, sex, and weight status classified by the body mass index (BMI).

Results

The overall EIG for men increased from 2.3 kcal/day in 1975 to 4.7 kcal/day in 1987 and then decreased to 2.3 kcal/day in 2015. The overall EIG for women consistently decreased from 4.3 kcal/day in 1975 to −0.5 kcal/day in 2015. By BMI class, the EIG for men with a BMI of <30 kg/m² began to decrease around 1990, indicating a deceleration in the prevalence of overweight and obese men. The EIG consistently decreased for women with a BMI of <25 kg/m² and reached negative values from the late 2000s to early 2010s, indicating a gradual decrease in the prevalence of overweight and obese women.

Conclusions

The dynamics of the EIG were different across sex and weight groups. Public health interventions should target a further decrease in the EIG for normal-weight, overweight, and obese men and a stop in the decreasing trends of the EIG in underweight and normal-weight women.

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

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

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.

Three Decades of New Zealand Adults Obesity Trends: An Estimation of Energy Imbalance Gaps Using System Dynamics Modeling

OBJECTIVE

The energy imbalance gap (EIG) captures the average daily excess energy intake and governs the speed of change in body mass. This study quantifies the dynamics of the EIG over time and across different ethnic, sex, and weight groups in New Zealand.

METHODS

A novel method in system dynamics was used to estimate the trends/dynamics of the EIG among Pacific, Māori, Asian, and European/other men and women over the past 3 decades in New Zealand. The model was calibrated using data from the national New Zealand Health Survey (1988-2014/15).

RESULTS

All ethnic/sex subpopulations except European/other women and Pacific men showed a drop in their EIGs starting in early to mid-2000. For European/other subpopulations, the EIG was positive in 2014/15 but lower than it was in previous years, meaning that the prevalence of obesity still increased but at a slower pace. For the Pacific subpopulation, increasing trends of the EIG across all BMI classes in 2014/15 implied that obesity prevalence for this subpopulation increased at a rate faster than before. Among Asian women, almost all BMI classes showed a negative EIG in 2012 to 2014/15, implying decreasing prevalence of obesity in this subpopulation. Māori populations with obesity showed a negative EIG in 2014/15.

CONCLUSIONS

The detailed heterogeneous trends of the EIG explain the obesity patterns for different ethnic, sex, and BMI subgroups in New Zealand and suggest the need for customizing targets/policy interventions for different subpopulations.

Applications of systems modelling in obesity research

Obesity is a complex system problem involving a broad spectrum of policy, social, economic, cultural, environmental, behavioural, and biological factors and the complex interrelated, cross-sector, non-linear, dynamic relationships among them. Systems modelling is an innovative approach with the potential for advancing obesity research. This study examined the applications of systems modelling in obesity research published between 2000 and 2017, examined how the systems models were developed and used in obesity studies and discussed related gaps in current research. We focused on the applications of two main systems modelling approaches: system dynamics modelling and agent-based modelling. The past two decades have seen a growing body of systems modelling in obesity research. The research topics ranged from micro-level to macro-level energy-balance-related behaviours and policies (19 studies), population dynamics (five studies), policy effect simulations (eight studies), environmental (10 studies) and social influences (15 studies) and their effects on obesity rates. Overall, systems analysis in public health research is still in its early stages, with limitations linked to model validity, mixed findings and its actual use in guiding interventions. Challenges in theory and modelling practices need to be addressed to realize the full potential of systems modelling in future obesity research and interventions.

A Co-flow Structure for Goal-Directed Internal Change

We describe a co-flow structure that models internal, goal-directed changes to an attribute (e.g., employee loyalty) of fundamental material (e.g., employees). This co-flow accommodates problems not adequately modeled with an existing, generic structure. Our structure builds on the co-flow proposed by Hines, which uses an information delay to model external change to an attribute. We use a first-order information delay to model both external changes to the attribute from the material stock and internal changes from an internal goal for the attribute. We provide an exact, dynamic solution for this co-flow enabling us to precisely describe its equilibrium and non-equilibrium behavior. Several examples are provided and discussed, including a situation where a management program is designed to increase average employee loyalty. In addition, we review applications of traditional and Hines co-flow structures to provide background and to describe our evolutionary path towards design of the new co-flow.

Integrating Systems Modelling and Data Science

Although System Dynamics modelling is sometimes referred to as data-poor modelling, it often is –or could be– applied in a data-rich manner. However, more can be done in the era of ‘big data'. Big data refers here to situations with much more available data than was until recently manageable. The field of data science makes big(ger) data manageable. This paper provides a perspective on the future of System Dynamics with a prominent place for bigger data and data science. It discusses different approaches for dealing with bigger data. It reviews methods, techniques and tools for dealing with bigger data in System Dynamics, and sheds light on the modelling phases for which data science is most useful. Finally, it provides several examples of current applications in which big data, data science, and System Dynamics modelling and simulation are being merged.

Modeling US adult obesity trends: a system dynamics model for estimating energy imbalance gap

OBJECTIVES

We present a system dynamics model that quantifies the energy imbalance gap responsible for the US adult obesity epidemic among gender and racial subpopulations.

METHODS

We divided the adult population into gender-race/ethnicity subpopulations and body mass index (BMI) classes. We defined transition rates between classes as a function of metabolic dynamics of individuals within each class. We estimated energy intake in each BMI class within the past 4 decades as a multiplication of the equilibrium energy intake of individuals in that class. Through calibration, we estimated the energy gap multiplier for each gender-race-BMI group by matching simulated BMI distributions for each subpopulation against national data with maximum likelihood estimation.

RESULTS

No subpopulation showed a negative or zero energy gap, suggesting that the obesity epidemic continues to worsen, albeit at a slower rate. In the past decade the epidemic has slowed for non-Hispanic Whites, is starting to slow for non-Hispanic Blacks, but continues to accelerate among Mexican Americans.

CONCLUSIONS

The differential energy balance gap across subpopulations and over time suggests that interventions should be tailored to subpopulations' needs.