Reducing sugar-sweetened beverage consumption by providing caloric information: how Black adolescents alter their purchases and whether the effects persist

Abstract

Objectives: We examined the ways in which adolescents altered the type and size of their purchases of sugar-sweetened beverages (SSBs), together with whether the effects persisted after removing caloric information signs in stores.

Methods: We used a case-crossover design with 6 stores located in low-income Black neighborhoods in Baltimore, Maryland, from 2012 to 2013. The intervention used 1 of 4 randomly posted signs with caloric information: absolute calories, number of teaspoons of sugar, and number of minutes of running or miles of walking necessary to burn off a beverage. We collected data for 4516 purchases by Black adolescents, including both baseline and postintervention periods with no signs posted.

Results: We found that providing caloric information significantly reduced the number of total beverage calories purchased, the likelihood of buying an SSB, and the likelihood of buying an SSB greater than 16 ounces (P < .05). After removing the signs, the quantity, volume, and number of calories from SSB purchases remained lower than baseline (P < .05).

Conclusions: Providing caloric information was associated with purchasing a smaller SSB, switching to a beverage with no calories, or opting to not purchase a beverage; there was a persistent effect on reducing SSB purchases after signs were removed.

FIGURE 1—

Adjusted change in beverage purchases between baseline and intervention: Reducing Sugar-Sweetened Beverages Consumption by Providing Caloric Information; Baltimore, MD; 2012–2013. Note. SSB = sugar-sweetened beverage. The sample for this analysis is all purchases (including purchases without beverages) from 6 corner stores in low-income, predominantly Black neighborhoods of Baltimore. These predicted probabilities were from logistic regression models in which any SSB binary outcome variable was replaced with the specific beverage type (and no drink) as the binary outcome variable. These estimates were adjusted for gender, store, time of day (before or after 4 pm), and average monthly temperature.

FIGURE 2—

Adjusted change in sugar-sweetened beverage (SSB) purchases by volume between baseline and intervention: Reducing Sugar-Sweetened Beverages Consumption by Providing Caloric Information; Baltimore, MD; 2012–2013. Note. These predicted probability results came from re-running the logistic regression models for the SSB subsample and replacing the outcome variable with the specific SSB type and size as the outcome variable. Estimates are adjusted for gender, store, time of day (before or after 4 pm), and average monthly temperature.