Adjusting for protein quality by food source may affect nutrient density metrics

Area of Science:

• Nutrition Science
• Food Science
• Public Health Nutrition

Background:

• Nutrient profiling (NP) systems are essential tools for assessing food nutritional value.
• Protein content is a common component in NP algorithms, but protein quality is often not considered.
• Disparities in protein quality can affect public health, particularly in low- and middle-income countries.

Purpose of the Study:

• To evaluate the impact of adjusting nutrient density algorithms for protein quality.
• To assess how protein digestibility correction influences the classification of various food groups.
• To determine the implications of protein quality adjustments for NP models like Nutri-Score and Nutrient Rich Foods.

Main Methods:

• Analysis of 378 foods using the Fred Hutch food frequency questionnaire.
• Application of a simplified Protein Digestibility Corrected Amino Acid Score (PDCAAS) to adjust protein content.
• Evaluation of the effects of protein quality adjustment on point-based and continuous NP algorithms.

Main Results:

• Animal-source foods, soy products, and nuts were primary sources of high-quality protein (>20% DV per 100g or 100kcal).
• Most plant-based proteins (beans, legumes, grains, vegetables) provided lower protein density (<10% DV per 100g or 100kcal).
• Adjusting for protein quality altered the nutrient density scores of foods in NP models.

Conclusions:

• Quantitative NP methods relying solely on protein content may misrepresent food nutritional value.
• Protein quality adjustment is necessary for accurate nutrient density assessment, especially in populations with protein quality concerns.
• The findings have significant implications for public health nutrition strategies and food labeling in diverse global settings.