Literature DB >> 26850312

Construct and criterion-related validation of nutrient profiling models: A systematic review of the literature.

Sheri L Cooper1, Fiona E Pelly2, John B Lowe3.   

Abstract

Nutrient profiling (NP) is defined as the science of ranking foods according to their nutritional composition for the purpose of preventing disease or promoting health. The application of NP is ultimately to assist consumers to make healthier food choices, and thus provide a cost effective public health strategy to reduce the incidence of diet-related chronic disease. To our knowledge, no review has assessed the evidence to confirm the validity of NP models. We conducted a systematic review to investigate the construct and criterion-related validity of NP models in ranking food according to their nutritional composition for the purpose of preventing disease and promoting health. We searched peer-reviewed research published to 30 June 2015 and used PUBMED, Global Health (CABI), and SCOPUS databases. Within study bias was assessed using an adapted version of the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies -2) tool for all diagnostic studies and the Cochrane Collaboration's Risk of Bias tool for all non-diagnostic studies. The GRADE (Grades of Recommendation, Assessment, Development, and Evaluation) approach was used to guide our judgement of the quality of the body of evidence for each outcome measure. From a total of 83 studies, 69 confirmed the construct validity of NP models; however most of these studies contained methodological weaknesses. Six studies used objective external measures to confirm the criterion-related validity of NP models; which inherently improved quality. The overall quality of evidence on the accuracy of NP models was judged to be very low to moderate using the GRADE approach. Many carefully designed studies to establish both construct and criterion-related validity are necessary to authenticate the application of NP models and provide the evidence to support the current definition of NP.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Nutrient profiling; Nutrition labelling; Systematic review; Validity

Mesh:

Year:  2016        PMID: 26850312     DOI: 10.1016/j.appet.2016.02.001

Source DB:  PubMed          Journal:  Appetite        ISSN: 0195-6663            Impact factor:   3.868


  8 in total

1.  Nutrient Profile Models with Applications in Government-Led Nutrition Policies Aimed at Health Promotion and Noncommunicable Disease Prevention: A Systematic Review.

Authors:  Marie-Ève Labonté; Theresa Poon; Branka Gladanac; Mavra Ahmed; Beatriz Franco-Arellano; Mike Rayner; Mary R L'Abbé
Journal:  Adv Nutr       Date:  2018-11-01       Impact factor: 8.701

2.  Comparative Analysis of the Classification of Food Products in the Mexican Market According to Seven Different Nutrient Profiling Systems.

Authors:  Alejandra Contreras-Manzano; Alejandra Jáuregui; Anabel Velasco-Bernal; Jorge Vargas-Meza; Juan A Rivera; Lizbeth Tolentino-Mayo; Simón Barquera
Journal:  Nutrients       Date:  2018-06-07       Impact factor: 5.717

3.  Development of the Choices 5-Level Criteria to Support Multiple Food System Actions.

Authors:  Gianluca Tognon; Belen Beltramo; Rutger Schilpzand; Lauren Lissner; Annet J C Roodenburg; Rokiah Don; Krishnapillai Madhavan Nair; Ngozi Nnam; Bruce Hamaker; Herbert Smorenburg
Journal:  Nutrients       Date:  2021-12-16       Impact factor: 5.717

4.  Evaluation of the Mexican warning label nutrient profile on food products marketed in Mexico in 2016 and 2017: A cross-sectional analysis.

Authors:  Alejandra Contreras-Manzano; Carlos Cruz-Casarrubias; Ana Munguía; Alejandra Jáuregui; Jorge Vargas-Meza; Claudia Nieto; Lizbeth Tolentino-Mayo; Simón Barquera
Journal:  PLoS Med       Date:  2022-04-20       Impact factor: 11.069

5.  A Cross-Sectional Audit of Nutrition and Health Claims on Dairy Yoghurts in Supermarkets of the Illawarra Region of New South Wales, Australia.

Authors:  Sam-Reith S Wadhwa; Anne T McMahon; Elizabeth P Neale
Journal:  Nutrients       Date:  2021-05-27       Impact factor: 5.717

6.  Comparison of nutrient profiling models for assessing the nutritional quality of foods: a validation study.

Authors:  Theresa Poon; Marie-Ève Labonté; Christine Mulligan; Mavra Ahmed; Kacie M Dickinson; Mary R L'Abbé
Journal:  Br J Nutr       Date:  2018-07-17       Impact factor: 3.718

7.  Evaluation of the Nutritional Quality of Processed Foods in Honduras: Comparison of Three Nutrient Profiles.

Authors:  Adriana Hernandez Santana; Sharyl Waleska Bodden Andrade; Dina Rojas Aleman; Jean Pierre Enríquez; Adriana Beatriz Di Iorio
Journal:  Int J Environ Res Public Health       Date:  2020-09-27       Impact factor: 3.390

8.  Assessing the healthiness of UK food companies' product portfolios using food sales and nutrient composition data.

Authors:  Lauren Kate Bandy; Sven Hollowell; Richard Harrington; Peter Scarborough; Susan Jebb; Mike Rayner
Journal:  PLoS One       Date:  2021-08-04       Impact factor: 3.240

  8 in total

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