Personalized Nutrient Profiling of Food Patterns: Nestlé's Nutrition Algorithm Applied to Dietary Intakes from NHANES

Nutrient profiling (NP) models have been used to assess the nutritional quality of single foods. NP methodologies can also serve to assess the quality of total food patterns. The objective of this study was to construct a personalized nutrient-based scoring system for diet quality and optimal calories. The new Nestlé Nutrition Algorithm (NNA) is based on age and gender-specific healthy ranges for energy and nutrient intakes over a 24 h period. To promote nutrient balance, energy and nutrient intakes either below or above pre-defined healthy ranges are assigned lower diet quality scores. NNA-generated diet quality scores for female 2007⁻2014 National Health and Nutrition Examination Survey (NHANES) participants were compared to their Healthy Eating Index (HEI) 2010 scores. Comparisons involved correlations, joint contingency tables, and Bland Altman plots. The NNA approach showed good correlations with the HEI 2010 scores. NNA mean scores for 7 days of two exemplary menu plans (MyPlate and DASH) were 0.88 ± 0.05 (SD) and 0.91 ± 0.02 (SD), respectively. By contrast, diets of NHANES participants scored 0.45 ± 0.14 (SD) and 0.48 ± 0.14 on first and second days, respectively. The NNA successfully captured the high quality of MyPlate and Dietary Approaches to Stop Hypertension (DASH) menu plans and the lower quality of diets actually consumed in the US.