Does point-of-sale nutrition information improve the nutritional quality of food choices?

Econ Hum Biol. 2019 Dec:35:133-143. doi: 10.1016/j.ehb.2019.07.001. Epub 2019 Jul 10.

Abstract

Point-of-sale nutrition information has been adopted by numerous grocery stores to respond to the demand for easy-to-understand nutrition labeling by consumers. Although there is conflicting evidence regarding the effectiveness of providing nutrition information, previous research indicates simplified shelf nutrition labels may lead to healthier choices. However, these studies have not examined how different consumer segments respond to these labels, nor the differential impacts across foods. Using household purchase data from a store that voluntarily adopted the (now defunct) NuVal shelf nutrition labels (a 1-100 numeric score derived from a nutrition-profiling algorithm), we assess NuVal impacts across different consumers and foods. NuVal scores potentially influence not only purchase quantity but also likelihood of buying. Thus, the effect of NuVal was measured by estimating a two-part model and predicting consumers' unconditional purchase responses. We found evidence of heterogeneous impacts of NuVal across consumers and foods. High-income households and households with children shifted their yogurt and frozen dinner purchases to more healthful items. In contrast, households with children and households headed by heads with college education slightly shifted their canned soup purchases to less healthful options. Our findings suggest that specific foods and consumer segments are influenced by simplified shelf nutrition information and further research is necessary to better understand its effect on consumer dietary quality.

Keywords: NuVal; Nutrition profiling; Purchase intention; Shelf nutrition labels; Summary nutrition information.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Choice Behavior
  • Consumer Behavior
  • Diet
  • Environment
  • Food Labeling / methods*
  • Food Labeling / statistics & numerical data*
  • Food Preferences / psychology*
  • Food Supply
  • Humans
  • Nutritional Status
  • Nutritive Value*
  • Socioeconomic Factors