Literature DB >> 32878658

Prospective associations of the original Food Standards Agency nutrient profiling system and three variants with weight gain, overweight and obesity risk: results from the French NutriNet-Santé cohort.

Manon Egnell1, Louise Seconda1,2, Bruce Neal3,4,5, Cliona Ni Mhurchu3,6, Mike Rayner7, Alexandra Jones3,4, Mathilde Touvier1, Emmanuelle Kesse-Guyot1, Serge Hercberg1,8, Chantal Julia1,8.   

Abstract

Nutrient profiling systems (NPS) are used to classify foods according to their nutritional composition. However, investigating their prospective associations with health is key to their validation. The study investigated the associations of the original Food Standards Agency (FSA)-NPS and three variants (Food Standards Australia New Zealand Nutrient Profiling Scoring Criterion (NPSC), Health Star Rating NPS and the French High Council of Public Health NPS (HCSP-NPS)), with weight status. Individual dietary indices based on each NPS at the food level were computed to characterise the dietary quality of 71 403 French individuals from the NutriNet-Santé cohort. Associations of these indices with weight gain were assessed using mixed models and with overweight and obesity risks using Cox models. Participants with a higher dietary index (reflecting lower diet nutritional quality) were more likely to have a significant increase in BMI over time (β-coefficients positive) and an increased risk of overweight (hazard ratio (HR) T3 v. T1 = 1·27 (95 % CI 1·17, 1·37)) for the HCSP-Dietary Index, followed by the original FSA-Dietary Index (HR T3 v. T1 = 1·18 (95 % CI 1·09, 1·28)), the NPSC-Dietary Index (HR T3 v. T1 = 1·14 (95 % CI 1·06, 1·24)) and the Health Star Rating-Dietary Index (HR T3 v. T1 = 1·12 (95 % CI 1·04, 1·21)). Whilst differences were small, the HCSP-Dietary Index appeared to show significantly greater association with overweight risk. Overall, these results show the validity of NPS derived from the FSA-NPS, supporting their use in public policies for chronic disease prevention.

Entities:  

Keywords:  Cohort studies; Nutrient profiles; Nutrition policy; Nutritional quality; Weight status

Year:  2020        PMID: 32878658     DOI: 10.1017/S0007114520003384

Source DB:  PubMed          Journal:  Br J Nutr        ISSN: 0007-1145            Impact factor:   3.718


  8 in total

1.  Evaluating intake levels of nutrients linked to non-communicable diseases in Australia using the novel combination of food processing and nutrient profiling metrics of the PAHO Nutrient Profile Model.

Authors:  Priscila Machado; Gustavo Cediel; Julie Woods; Phillip Baker; Sarah Dickie; Fabio S Gomes; Gyorgy Scrinis; Mark Lawrence
Journal:  Eur J Nutr       Date:  2022-01-16       Impact factor: 5.614

2.  Cross-sectional comparisons of dietary indexes underlying nutrition labels: nutri-score, Canadian 'high in' labels and Diabetes Canada Clinical Practices (DCCP).

Authors:  Valérie Deschamps; Chantal Julia; Laura Paper; Mavra Ahmed; Jennifer J Lee; Emmanuelle Kesse-Guyot; Mathilde Touvier; Serge Hercberg; Pilar Galan; Benoît Salanave; Charlotte Verdot; Mary R L'Abbé
Journal:  Eur J Nutr       Date:  2022-08-12       Impact factor: 4.865

3.  Impact of the Front-of-Pack Label Nutri-Score on the Nutritional Quality of Food Choices in a Quasi-Experimental Trial in Catering.

Authors:  Chantal Julia; Nathalie Arnault; Cédric Agaësse; Morgane Fialon; Mélanie Deschasaux-Tanguy; Valentina A Andreeva; Léopold K Fezeu; Emmanuelle Kesse-Guyot; Mathilde Touvier; Pilar Galan; Serge Hercberg
Journal:  Nutrients       Date:  2021-12-17       Impact factor: 5.717

Review 4.  Front-of-pack (FOP) labelling systems to improve the quality of nutrition information to prevent obesity: NutrInform Battery vs Nutri-Score.

Authors:  Michele O Carruba; Antonio Caretto; Antonino De Lorenzo; Giuseppe Fatati; Andrea Ghiselli; Lucio Lucchin; Claudio Maffeis; Alexis Malavazos; Giuseppe Malfi; Enrica Riva; Chiara Ruocco; Ferruccio Santini; Marco Silano; Alessandra Valerio; Andrea Vania; Enzo Nisoli
Journal:  Eat Weight Disord       Date:  2021-10-19       Impact factor: 3.008

Review 5.  The Nutri-Score algorithm: Evaluation of its validation process.

Authors:  Daphne L M van der Bend; Manon van Eijsden; Michelle H I van Roost; Kees de Graaf; Annet J C Roodenburg
Journal:  Front Nutr       Date:  2022-08-15

6.  Associations Between the Modified Food Standard Agency Nutrient Profiling System Dietary Index and Cardiovascular Risk Factors in an Elderly Population.

Authors:  Nadine Khoury; Clara Gómez-Donoso; María Ángeles Martínez; Miguel Ángel Martínez-González; Dolores Corella; Montserrat Fitó; J Alfredo Martínez; Ángel M Alonso-Gómez; Julia Wärnberg; Jesús Vioque; Dora Romaguera; Ana León-Acuña; Francisco J Tinahones; José M Santos-Lozano; Luís Serra-Majem; Paloma Massó Guijarro; Josep A Tur; Vicente Martín Sánchez; Xavier Pintó; Miguel Delgado-Rodríguez; Pilar Matía-Martín; Josep Vidal; Clotilde Vázquez; Lidia Daimiel; Emili Ros; Maira Bes-Rastrollo; Rocio Barragan; Olga Castañer; Jose D Torres-Peña; Leyre Notario-Barandiaran; Carlos Muñoz-Bravo; Itziar Abete; Lara Prohens; Naomi Cano-Ibáñez; Lucas Tojal Sierra; José Carlos Fernández-García; Carmen Sayon-Orea; Maria Pascual; Jose V Sorli; Dolores Zomeño; Patricia J Peña-Orihuela; Antonio J Signes-Pastor; F Javier Basterra-Gortari; Helmut Schröeder; Jordi Salas Salvadó; Nancy Babio
Journal:  Front Nutr       Date:  2022-07-14

7.  Clinical Application of the Food Compass Score: Positive Association to Mediterranean Diet Score, Health Star Rating System and an Early Eating Pattern in University Students.

Authors:  Paraskevi Detopoulou; Dimitra Syka; Konstantina Koumi; Vasileios Dedes; Konstantinos Tzirogiannis; Georgios I Panoutsopoulos
Journal:  Diseases       Date:  2022-07-07

8.  Do Overweight People Have Worse Cognitive Flexibility? Cues-Triggered Food Craving May Have a Greater Impact.

Authors:  Shiqing Song; Qingqing Li; Yan Jiang; Yong Liu; Aidi Xu; Xinyuan Liu; Hong Chen
Journal:  Nutrients       Date:  2022-01-06       Impact factor: 5.717

  8 in total

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