| Literature DB >> 28595659 |
Abstract
Nutrient profiling (NP) models rate the nutritional quality of individual foods, based on their nutrient composition. Their goal is to identify nutrient-rich foods, generally defined as those that contain more nutrients than calories and are low in fat, sugar and salt. NP models have provided the scientific basis for evaluating nutrition and health claims and regulating marketing and advertising to children. The food industry has used NP methods to reformulate product portfolios. To help define what we mean by healthy foods, NP models need to be based on published nutrition standards, mandated serving sizes and open-source nutrient composition databases. Specifically, the development and testing of NP models for public health should follow the seven decision steps outlined by the European Food Safety Authority. Consistent with this scheme, the nutrient-rich food (NRF) family of indices was based on a variable number of qualifying nutrients (from six to fifteen) and on three disqualifying nutrients (saturated fat, added sugar, sodium). The selection of nutrients and daily reference amounts followed nutrient standards for the USA. The base of calculation was 418·4 kJ (100 kcal), in preference to 100 g, or serving sizes. The NRF algorithms, based on unweighted sums of percent daily values, subtracted negative (LIM) from positive (NRn) subscores (NRn - LIM). NRF model performance was tested with respect to energy density and independent measures of a healthy diet. Whereas past uses of NP modelling have been regulatory or educational, voluntary product reformulation by the food industry may have most impact on public health.Entities:
Keywords: FDA Food and Drug Administration; FNDDS Food and Nutrient Database for Dietary Studies; NP nutrient profiling; NRF nutrient-rich food; RACC reference amounts customarily consumed; Nutrient profiling; Nutrient-rich food index; Nutrient-rich foods; Nutriscore
Mesh:
Year: 2017 PMID: 28595659 DOI: 10.1017/S0029665117000416
Source DB: PubMed Journal: Proc Nutr Soc ISSN: 0029-6651 Impact factor: 6.297