Using Simulation to Investigate Obesity and Type 2 Diabetes

According to Wikipedia, “A simulation is the imitation of the operation of a real-world process or system over time. Simulations require the use of models; the model represents the key characteristics or behaviors of the selected system or process, whereas the simulation represents the evolution of the model over time. Often, computers are used to execute the simulation.”

Simulation is beneficial for assessing public health concerns.
Indeed, simulation, using modeling, has been employed to forecast future levels of obesity and the relationship between obesity and type 2 diabetes as we age.

In one study, 41,567 children and adults' life paths were examined using simulation. And the researchers concluded that, "Given the current level of childhood obesity, the models predicted that a majority of today’s children, [approximately 57%] will be obese at the age of 35 years, and roughly half of the projected prevalence will occur during childhood.”

Additionally, another study employed simulation to analyze the incidence and trends of obesity, as well as the influence of obesity on the risk of type 2 diabetes in a computer model of Los Angeles-born children.

The researchers created the Virtual Los Angeles cohort-ViLA. This was a model calibrated to the Los Angeles County population. The model incorporated trends, causes, and effects of obesity, with a particular emphasis on diabetes as a significant obesity consequence over the duration of the participants represented in the simulation.

Each person depicted in the model engaged in both beneficial and not so beneficial behaviors that are known to be associated with obesity and diabetes. These behaviors included the intake of sugar-sweetened beverages, engagement or non-engagement in physical activity, fast-food consumption, and consumption of diets rich in fresh fruits and vegetables.

Additionally, the model used probability estimates to predict which modeled person might acquire or lose weight and develop type 2 diabetes, based on the person’s sociodemographic characteristics, historical activities, and previous weight or type 2 diabetes status. The researchers utilized the model to create a simulation of 98,230 residents ranging in age from birth to 65 years and residing in 235 Los Angeles County areas.

The simulation results indicated that obesity prevalence frequently increased from 10% to 30% across the life-course of the modeled individuals. And the prevalence of type 2 diabetes  typically increased from less than 2% in the 18-to-24 age group to 25% in the 40-to-49 age group.

As demonstrated, simulation can be beneficial for examining public health concerns. And obesity is a significant public health problem. Another significant public health problem is type 2 diabetes. The modeling experiments cited above indicate the magnitude of the health issues created by the combination of obesity and type 2 diabetes. Additionally, the research underscores the need for the healthcare sector to step up efforts to address obesity and diabetes.

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