If you’ve ever wondered about the real impact of those little black-and-white nutrition labels, or felt that perhaps food labeling could be more meaningful, consider the results of a new study, published recently in The American Journal of Public Health.
A team of researchers from Johns Hopkins Bloomberg School of Public Health wanted to know what makes people change their habits – specifically, low-income black adolescents. In 2012 – the most recent year of CDC data – obesity was more prevalent among both African-Americans and low-income groups than the general population. (But remember that the relationship between income and obesity varies by poverty level, gender and race is a complicated one.)
The study (n=4516, analyzed with multivariate regression models) tracked the teens’ consumption of sugar-sweetened beverages (SSBs) at six corner stores around Baltimore, Md., based on four different types of brightly colored signage posted at the beverage cases:
- Calorie content: “Did you know that a bottle of soda or fruit juice has about 250 calories?”
- Sugar content: “Did you know that a bottle of soda or fruit juice has about 16 teaspoons of sugar?”
- Exercise equivalents: “Did you know that working off a bottle of soda or fruit juice takes about 50 minutes of running?,” or, “Did you know that working off a bottle of soda or fruit juice takes about 5 miles of walking?”
The researchers examined the total number of calories consumed, if an SSB was purchased, and if so, whether it was a “large-volume” SSB. “Large-volume” was greater than 16 ounces. That cutoff point wasn’t based on a specific nutritional recommendation, but on the controversy surrounding former New York City Mayor Michael Bloomberg’s failed plan to ban sodas over 16 ounces.
The results? Out of 4,516 purchases analyzed, soda was purchased less often – 30 percent of the time compared to 44 percent at baseline. Purchases of diet soda, water and fruit juice all went up. Large sodas over 16 ounces were purchased 16 percent of the time, compared to 27 percent at baseline.
In terms of statistical significance, the intervention resulted in some impressive p-values (most intervention categories showed p <.01 and three showed p <.05 – respectively, that’s a 99 percent and 95 percent likelihood that the results are due to factors other than random chance).
But these results might not be applicable to every community. Only six corner stores in Baltimore were included, and the exercise equivalents were based on metabolic averages for teenagers. Each store went through a “control period,” but there was no control store – and some teens could have been sampled more than once.
In general, though, the results are compelling. They might make you curious about what’s going on in your community with food labels and nutritional awareness. If so, talk to a city councilperson or local nutritionist. Ask if it’s an issue on the table, or an issue the community is concerned about.
Also, consider exploring food deserts in your community – areas where healthy food is inaccessible or unavailable. And stay tuned – my next blog post will cover resources on how to evaluate your community’s food environment and how to find food deserts.
