Quantifying the contribution of foods with unfavourable nutrient profiles to nutritionally adequate diets

Br J Nutr. 2011 Apr;105(8):1133-7. doi: 10.1017/S0007114510004800. Epub 2010 Dec 9.

Abstract

That 'all foods can fit' into a healthy diet is a long-standing principle of dietetic practice. The present study quantified the relative contributions of foods to encourage and foods to limit, using new techniques of individual diet optimisation and nutrient profiling. Individual foods from every food group were assigned to four nutrient profile classes based on the French SAIN,LIM system. Foods with the most favourable nutrient profiles were in class 1, and foods with the least favourable nutrient profiles were in class 4. An optimised diet that met the recommendations for thirty-two nutrients and that respected the existing eating habits was designed for each adult in the nationally representative 'Enquête Individuelle et Nationale sur les Consommations Alimentaires 1' dietary survey (n 1171). The relative proportions of the four nutrient profiling classes were assessed before and after the optimisation process. The contribution of fruits and vegetables, whole grains, milk and fish was significantly increased, whereas the contribution of refined grains, meats, mixed dishes, sugars and fats was decreased. The optimised diets derived more energy (30 v. 21 % in the observed diets) from class 1 foods and less energy (41 v. 56 %) from class 4 foods. They also derived a higher amount of class 1 foods (61 v. 51 %) and a lower amount of class 4 foods (22 v. 32 %). Thus, nutrient adequacy was compatible with the consumption of foods with an unfavourable nutrient profile (one-fifth the basket weight), provided that the diet also contained almost two-thirds of foods with the most favourable profile. Translating these results into concrete and quantified advice may have very tangible public health implications.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Aged
  • Cross-Sectional Studies
  • Diet* / statistics & numerical data
  • Female
  • Food / classification
  • Food / statistics & numerical data
  • Food Analysis*
  • France
  • Health Promotion / methods
  • Humans
  • Male
  • Middle Aged
  • Nutrition Surveys
  • Nutritive Value
  • Young Adult