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.
Keywords: food composition database; food supply; nutrient profiling; reformulation.