Evaluation of food consumption according to the Nova Classification System: new metrics and technological innovation

• Grant number: 21/10993-3
• Support Opportunities: Regular Research Grants
• Start date: June 01, 2022
• End date: August 31, 2024
• Field of knowledge: Health Sciences - Nutrition - Nutritional Analysis of Population
• Principal Investigator: Maria Laura da Costa Louzada
• Grantee: Maria Laura da Costa Louzada
• Host Institution: Faculdade de Saúde Pública (FSP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated researchers: Carlos Augusto Monteiro ; Caroline dos Santos Costa ; Daniela Neri Gama de Almeida ; Eurídice Martínez Steele ; Fernanda Rauber ; Francine Silva dos Santos ; Jean-Claude Moubarac ; Josiane Steluti ; Renata Bertazzi Levy
• Associated research grant(s): 24/20190-3 - International Conference on Diet and Activity Methods (ICDAM), AR.EXT

Abstract

The Nova food classification system, which groups foods into categories according to the characteristics of industrial processing, caused a paradigm shift in nutrition science, proving to be relevant for understanding the epidemiology of diseases and the impacts of food systems worldwide. Despite the growing number of epidemiological studies that use this classification, a common limitation refers to the instruments for assessing food consumption, which are nonspecific for estimating food intake according to the Nova. Objective: To develop and validate instruments to assess food consumption according to the Nova classification system and to develop software for free availability of these tools. Methods: Three instruments will be developed and/or validated: a food frequency questionnaire (FFQ-Nova), a simplified questionnaire (Screener-Nova) and a Brazilian diet quality index (IQAB-Nova). All instruments will have their final validation stage conducted in the Nutrinet Brazil Cohort, a study carried out entirely through a digital platform that collects information on health status (including weight and height) and food intake through a 24-hour record (24hR) developed specifically for estimation of food consumption according to the characteristics of industrial processing. The FFQ-Nova will be a self-administered quantitative frequency questionnaire for Brazilian adults. Its list of foods will be developed from the analysis of the most commonly consumed foods in the 2017-2018 Household Budget Survey, grouped according to Nova. A sub-sample of the Nutrinet Brazil study will be invited to answer the instrument and its validation will be carried out by comparing the estimates of food consumption obtained in the FFQ-Nova with those of the R24h. Screener-Nova, in turn, consists of a self-administered questionnaire that assesses consumption the day before (yes/no) of a set of natural or minimally processed foods and ultra-processed foods. It will be answered by the participants of the Nutrinet Brazil study, and the score formed from the sum of their answers will be compared with food consumption estimates obtained in the R24h of the Nutrinet study. Finally, the IQAB-Nova will consist of an index that will provide a score that will represent a summarized measure of diet quality, being calculated from data collected by 24-hour recalls/registries or FFQs. Its items will be built from the recommendations of the Dietary Guidelines for the Brazilian Population, which are based on the Nova groups. The IQBA-Nova will be applied to the R24h of Nutrinet Brazil and submitted to validation through factor analysis and analyzes of the association between its score and the dietary nutrient profile and obesity indicators (weight gain and incidence of obesity). Implications: The project will contribute with a great innovation to nutrition science by producing adequate instruments for measuring food consumption and evaluating the diet quality according to the Nova classification. With the availability of questionnaires in the form of free software, it is expected that the instruments will be widely used to assess food consumption in surveys of different natures and, thus, contribute to the production of evidence to support public policies. (AU)