Association for Public Policy Analysis & Management

The objective of this research is to estimate the effects of two retail chains’ adoption of NuVal shelf nutrition labels on consumer food choices using scanner data collected from over 5,000 households over a 4-year period. Processed and packaged foods and beverages account for over 50% of total calories consumed by an average American (Eicher-Miller et al., 2012). Although calories from these products have declined in recent years (Ng & Popkin, 2014), significant socioeconomic status disparities in food purchasing and dietary intake persist in families with children (Ford et al., 2014).

Policy makers and health researchers have proposed a number of policy interventions aimed at reducing consumption of some of the least nutritious food products. Shelf nutrition labels, an important aspect of healthy food retail, are a tool that provides summary information on the overall nutrition quality of a food product. They provide nutrition cues to shoppers and may be effective in promoting healthy food choices at the point of purchase. These summary labels offer one of a small handful of practical policy tools to influence consumer nutrition behavior, especially among lower-income consumers who may benefit more from these interpretive nutrition labels. There are two major summary shelf nutrition label systems in U.S. supermarkets: Guiding Stars (a four-point system introduced in 2006) and NuVal (a 1 to 100 numeric system introduced in 2008). As of April 2016, 24 chain grocers have adopted NuVal shelf labels compared with 5 retail chains using Guiding Stars.

Research examining the impacts of summary multiple-level labels, the type IOM recommends, on actual food purchases in real-world settings is scarce. U.S. studies focus exclusively on Guiding Stars, which has shown some effect at encouraging sales of more healthful products relative to less healthful products (Sutherland et al., 2010; Rahkovsky et al., 2013) but has not shown significant absolute reductions in calories purchased (Cawley et al., 2014). This may result because Guiding Stars only classifies foods into one of four categories (zero to three stars). As a result, consumers are unable to identify and switch to products that may be on the healthier end within a star category. Contrarily, NuVal scores foods on a scale from 1 to 100 based on an algorithm that profiles the content of 21 nutrients and the quality of four nutrition factors. The algorithm penalizes nutrients (e.g., saturated fat, sodium, and sugar) and nutrition factors generally considered to have unfavorable health effects and rewards those (e.g., fiber, potassium) that are beneficial to health. Therefore, the higher the NuVal score, the healthier the food. Unlike Guiding Stars, this level of granularity provides an easy cue for consumers to identify healthier products even when the differences may be small. Yet, small differences compounded over repeat shopping trips can result in significant health effects. To date, the ability of NuVal to encourage healthier purchases has not been extensively tested in real-world settings.