Balanced Hybrid Nutrient Density Score Compared to Nutri-Score and Health Star Rating Using Receiver Operating Characteristic Curve Analyses - Drewnowski, Adam; Gonzalez, Tanhia D.; Rehm, Colin D. (Frontiers in Nutrition, 2022)
BACKGROUND: Nutrient profiling (NP) models used to assess nutrient density of foods can be based on a combination of key nutrients and desirable food groups. OBJECTIVE: To compare the diagnostic accuracy of a new Balanced Hybrid Nutrient Density Score (bHNDS) to Nutri-Score and Health Star Rating (HSR) front-of-pack systems using Receiver Operating Characteristic (ROC) curve analyses . The diet-level bHNDS was first validated against Healthy Eating Index (HEI-2015) using data from the 2017-18 National Health and Nutrition Examination Survey (2017-18 NHANES). Food-level bHNDS values were then compared to both Nutri-Score and Health Star Rating (HSR) using ROC curve analyses. RESULTS: The bHNDS was based on 6 nutrients to encourage (protein, fiber, calcium, iron, potassium, and vitamin D); 5 food groups to encourage (whole grains, nuts and seeds, dairy, vegetables, and fruit), and 3 nutrients (saturated fat, added sugar, and sodium) to limit. The algorithm balanced components to encourage against those to limit. Diet-level bHNDS values correlated well with HEI-2015 (r=0.67; p<0.001). Food-level correlations with both Nutri-Score (r=0.60) and with HSR (r=0.58) were significant (both p<0.001). ROC estimates of the Area Under the Curve (AUC) showed high agreement between bHNDS values and optimal Nutri-Score and HSR ratings (>0.90 in most cases). ROC analysis identified those bHNDS cutoff points that were predictive of A-grade Nutri-Score or 5-star HSR. Those cutoff points were highly category specific. CONCLUSION: The new bHNDS model showed high agreement with two front-of-pack labeling systems. Cross-model comparisons based on ROC curve analyses are the first step toward harmonization of proliferating NP methods that aim to “diagnose” high nutrient-density foods.