A model of food reward learning with dynamic reward exposure

Introduction Greater distance to full-service supermarkets and low income may impair access to healthy diets and contribute to chronic kidney disease (CKD) and hypertension. The study aim was to determine relationships among residence in a “food desert,” low income, CKD, and blood pressure. Methods Adults in the 2003–2010 National Health and Nutrition Examination Survey (N=22,173) were linked to food desert data (www.ers.usda.gov) by Census Tracts. Food deserts have low median income and are further from a supermarket or large grocery store (>1 mile in urban areas, >10 miles in rural areas). Weighted regression was used to determine the association of residence in a food desert and family income with dietary intake, systolic blood pressure (SBP), and odds of CKD. Data analysis was performed in 2014–2015. Results Compared with those not in food deserts, participants residing in food deserts had lower levels of serum carotenoids (p<0.01), a biomarker of fruit and vegetable intake, and higher SBP (1.53 mmHg higher, 95% CI=0.41, 2.66) after adjustment for demographics and income. Residence in a food desert was not associated with odds of CKD (OR=1.20, 95% CI=0.96, 1.49). Lower, versus higher, income was associated with lower serum carotenoids (p<0.01) and higher SBP (2.00 mmHg higher for income–poverty ratio ≤1 vs >3, 95% CI=1.12, 2.89), but also greater odds of CKD (OR=1.76 for income–poverty ratio ≤1 vs >3, 95% CI=1.48, 2.10). Conclusions Limited access to healthy food due to geographic or financial barriers could be targeted for prevention of CKD and hypertension.

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“…Exposure to adverse food environments in childhood may have even stronger effects on dietary behavior. 41 …”

Section: Discussionmentioning

confidence: 99%

Food Access, Chronic Kidney Disease, and Hypertension in the U.S.

Suarez

Isakova

Anderson

et al. 2015

American Journal of Preventive Medicine

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“…ABMs simulate the simultaneous interactions of multiple agents to recreate and predict complex phenomena and processes. Studies using ABMs have provided insight into the determinants of individual food consumption behaviors, which can be influenced by early exposures to certain foods that have a "lock-in" effect, 59 as well as by peer influence among high schoolers. 60 Other studies have utilized systems models to translate changes on one scale (e.g., individual) to other scales (e.g., population), such as a system dynamics model developed by Fallah-Fini et al 61 that captured the relationship between individual energy gaps and population-level trends in obesity.…”

Section: Effort 3: Utilizing Systems Methodsmentioning

confidence: 99%

“…Agents have a set of decision points throughout the day, and parameters associated with these decision points are informed by a range of data sources including the US Census, National Health and Nutrition Examination Survey, InfoUSA, and expert input. Each agent has an embedded temporal difference reward-learning model that reinforces habits 59 ; for example, choosing unhealthy food will reinforce such behavior and lead to a higher probability of choosing unhealthy food later. Each agent also has an embedded metabolic model that represents the metabolic processes that link caloric intake and expenditures to changes in body mass index and perturb age-and gender-specific US Centers for Disease Control and Prevention growth curves.…”

Section: Example Of a Systems Approach To Obesitymentioning

confidence: 99%

A systems approach to obesity

Lee¹,

Bartsch²,

Mui³

et al. 2017

Nutr Rev

131

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Obesity has become a truly global epidemic, affecting all age groups, all populations, and countries of all income levels. To date, existing policies and interventions have not reversed these trends, suggesting that innovative approaches are needed to transform obesity prevention and control. There are a number of indications that the obesity epidemic is a systems problem, as opposed to a simple problem with a linear cause-and-effect relationship. What may be needed to successfully address obesity is an approach that considers the entire system when making any important decision, observation, or change. A systems approach to obesity prevention and control has many benefits, including the potential to further understand indirect effects or to test policies virtually before implementing them in the real world. Discussed here are 5 key efforts to implement a systems approach for obesity prevention: 1) utilize more global approaches; 2) bring new experts from disciplines that do not traditionally work with obesity to share experiences and ideas with obesity experts; 3) utilize systems methods, such as systems mapping and modeling; 4) modify and combine traditional approaches to achieve a stronger systems orientation; and 5) bridge existing gaps between research, education, policy, and action. This article also provides an example of how a systems approach has been used to convene a multidisciplinary team and conduct systems mapping and modeling as part of an obesity prevention program in Baltimore, Maryland.

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“…By relaxing this assumption, it is possible to observe the dynamic evolution of obesogenic eating behaviors beyond simply explaining correlations between variables, as statistical models typically do. Unlike most other agent-based models that have studied food systems, 24,36 our model is based on existing theories and an empirical database. A baseline validation was conducted to increase the model's reliability.…”

Section: Discussionmentioning

confidence: 99%

Impact of Different Policies on Unhealthy Dietary Behaviors in an Urban Adult Population: An Agent-Based Simulation Model

et al. 2014

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The literature on policy interventions to address obesogenic dietary behaviors can be divided into 3 distinct categories. The first is the use of economic measures to alter food consumption, such as taxing unhealthy ingredients and subsidizing healthy foods, 1---4 in light of studies that have shown the price of a calorie obtained from unhealthful foods is lower than the price of a calorie from more healthful foods. 5,6 The second is targeting the food environment through zoning polices, including increasing the number of healthy food vendors in "food desert" communities 7 and restricting the opening of new fast-food restaurants. 8The third and final category is related to combating unhealthy eating norms, given research showing the power of food marketing to change dietary behaviors and proposing restrictions on the time, place, and manner in which obesogenic foods are marketed. 9,10 Conversely, pro-nutritional marketing focuses on education as a means of increasing consumers' awareness of dietary health (e.g., nutrition disclosure on menus and the issuing of dietary guidelines). 11, 12The research to date focusing on the effects of these various approaches has incorporated theoretical and empirical techniques that rely on the stable unit treatment value assumption, according to which there are no interactions among people who experience an intervention that would alter the effectiveness of the intervention. However, this assumption is known to be violated in the case of obesity-related behaviors.13, 14 What is therefore not clear from existing regression-based and experimental empirical work is the potential magnitude of the population-level impact of these policies if they were implemented in the real world. We performed simulations to contrast the potential of different approaches aiming at tackling unhealthy dietary behaviors in a population of urban US adults. Simulations involving systems dynamics or agent-based modeling (ABM) are increasingly being used in public health, 15,16 We developed a computer model explicitly representing how individuals make decisions to examine the impact of policies on their food consumption. Our model was based on a multilevel theory of population health that emphasizes the role of cognitive habits in human behaviors. 25 According to this theory, individual beliefs are influenced by incentivesas in rational-choice theory-but also shaped by cognitive habits that are reinforced within a population by social norms and culture. Thus, our model examined how individual beliefs are influenced by interventions either in the social network or in the food environment. METHODSOur agent-based model contained 2 kinds of agents: individuals and food outlets. Individuals make dietary choices, and food outlets adapt to those choices. In our model, a single time period was defined as 1 day, and each simulation was run for more than 3 years (1100 days).In our simulations, individuals were assigned demographic characteristics (age, gender, Objectives. Unhealthy eating is a complex-system prob...

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A model of food reward learning with dynamic reward exposure

Cited by 25 publications

References 58 publications

Food Access, Chronic Kidney Disease, and Hypertension in the U.S.

Food Access, Chronic Kidney Disease, and Hypertension in the U.S.

A systems approach to obesity

Impact of Different Policies on Unhealthy Dietary Behaviors in an Urban Adult Population: An Agent-Based Simulation Model

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