TY - JOUR
T1 - Testing the capacity of a Multi-Nutrient profiling system to guide food and beverage reformulation
T2 - Results from five national food composition databases
AU - Combet, Emilie
AU - Vlassopoulos, Antonis
AU - Molenberg, Famke
AU - Gressier, Mathilde
AU - Privet, Lisa
AU - Wratten, Craig
AU - Sharif, Sahar
AU - Vieux, Florent
AU - Lehmann, Undine
AU - Masset, Gabriel
PY - 2017
Y1 - 2017
N2 - Nutrient profiling ranks foods based on their nutrient composition, with applications in multiple aspects of food policy. We tested the capacity of a category-specific model developed for product reformulation to improve the average nutrient content of foods, using five national food composition datasets (UK, US, China, Brazil, France). Products (n = 7183) were split into 35 categories based on the Nestlé Nutritional Profiling Systems (NNPS) and were then classified as NNPS ‘Pass’ if all nutrient targets were met (energy (E), total fat (TF), saturated fat (SFA), sodium (Na), added sugars (AS), protein, calcium). In a modelling scenario, all NNPS Fail products were ‘reformulated’ to meet NNPS standards. Overall, a third (36%) of all products achieved the NNPS standard/pass (inter-country and inter-category range: 32%-40%, 5%-72%, respectively), with most products requiring reformulation in two or more nutrients. The most common nutrients to require reformulation were SFA (22%-44%) and TF (23%-42%). Modelled compliance with NNPS standards could reduce the average content of SFA, Na and AS (10%, 8% and 6%, respectively) at the food supply level. Despite the good potential to stimulate reformulation across the five countries, the study highlights the need for better data quality and granularity of food composition databases.
AB - Nutrient profiling ranks foods based on their nutrient composition, with applications in multiple aspects of food policy. We tested the capacity of a category-specific model developed for product reformulation to improve the average nutrient content of foods, using five national food composition datasets (UK, US, China, Brazil, France). Products (n = 7183) were split into 35 categories based on the Nestlé Nutritional Profiling Systems (NNPS) and were then classified as NNPS ‘Pass’ if all nutrient targets were met (energy (E), total fat (TF), saturated fat (SFA), sodium (Na), added sugars (AS), protein, calcium). In a modelling scenario, all NNPS Fail products were ‘reformulated’ to meet NNPS standards. Overall, a third (36%) of all products achieved the NNPS standard/pass (inter-country and inter-category range: 32%-40%, 5%-72%, respectively), with most products requiring reformulation in two or more nutrients. The most common nutrients to require reformulation were SFA (22%-44%) and TF (23%-42%). Modelled compliance with NNPS standards could reduce the average content of SFA, Na and AS (10%, 8% and 6%, respectively) at the food supply level. Despite the good potential to stimulate reformulation across the five countries, the study highlights the need for better data quality and granularity of food composition databases.
KW - Food composition database
KW - Food supply
KW - Nutrient profiling
KW - Reformulation
U2 - 10.3390/nu9040406
DO - 10.3390/nu9040406
M3 - Article
AN - SCOPUS:85018335217
VL - 9
JO - Nutrients
JF - Nutrients
SN - 2072-6643
IS - 4
M1 - 406
ER -