Heavy alcohol drinking is an important public health issue. In the United States, over 88,000 people die every year from alcohol-related causes.
In a recent study conducted by The Ohio State University, social workers and engineers used mathematical models to help explain the factors that cause high-risk alcohol drinking.
They find that people decide whether they’ve had enough to drink the same way the cruise control on a car “decides” whether to accelerate or hit the brakes.
The finding is published in IEEE Transactions on Cybernetics. Researchers collected data from 1,500 students at parties and bars in San Diego.
At the start of the evening, the researchers quizzed the students about how drunk they intended to get. Then they tested the students’ blood alcohol content (BAC) several times over the following hours.
Blood alcohol content is a percentage measure of alcohol in the blood.
The data showed that students who reported wanting to feel “buzzed” adjusted their consumption to maintain a blood alcohol content around 0.05, while those who said they planned to get “very drunk” averaged around 0.1.
Researchers suggest that people drink until they attain a certain level of drunkenness, and then adjust the pace of their drinking—sipping versus gulping, for example, or switching to a non-alcoholic beverage—at different times throughout the night to maintain that level.
This decision making process is the same as cruise control on a car.
This study provides a proof of concept for a new study about to begin on the Ohio State Columbus campus, one that will create very large and complex data sets on the scale of big data.
In that new study, Ohio State residents—belonging to several different social groups consisting of friends who go out drinking together on the weekends—will wear trans-dermal blood alcohol monitors, so that the researchers can get more precise data on how their blood alcohol content varies over an entire night out.
The monitors are being provided by SCRAM Systems, a company that supplies similar ankle bracelets to law enforcement. The sensors are about the size of a hockey puck, and measure blood alcohol content through the wearer’s sweat.
The ultimate goal is to develop a smartphone app that will alert anyone when they’ve had enough to drink.
Citation: Giraldo LF, et al. (2016). Dynamics of Metabolism and Decision Making During Alcohol Consumption: Modeling and Analysis. IEEE Transactions on Cybernetics, published online. DOI: 10.1109/TCYB.2016.2593009.
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