Validating a Nutrition Metric Using Low‐income Consumer Data

The Nutrition Metric (NM) is one of several food rating systems developed to help food industries and consumers make healthy choices. To test the utility of NM as a tool to assist research focused on improving the diets of low‐income consumers, it was applied in quadrant analysis of a market basket database compiled over 104 consecutive weeks of purchases made by 34,407 families with household income ≤ $35,000. The average NM score of the 400 most frequently purchased items in the database was −0.21 ± 2.1 with a range of −13 (ham hocks) to +8.7 (dried pinto beans). Performance of NM was compared with other rating systems. NM ratings of a quota sample of the high penetration food items showed significant correlation with models WXY (r = 0.89) and Go‐Slow‐Whoa (r = 0.70). Inherent advantages of NM were that it is a simple empirically derived mathematical model, exists in the public domain, and only requires input common to the US FDA Nutrition Facts Label. Further exploration of NM utility as a research tool should test its criterion validity using a dataset that includes objective data on consumers' health status.