Artigos

INTRODUCTION
An adequate and healthy diet plays a fundamental role in promoting health and preventing and controlling chronic non-communicable diseases (NCDs), one of the biggest public health challenges in the world1. According to the Food Guide for the Brazilian Population, an adequate and healthy diet should be based on fresh, minimally processed foods and culinary preparations2.
The characterization of foods, according to the extent and purpose of industrial processing, generates the NOVA classification, which categorizes foods into four groups: 1) fresh or minimally processed foods, obtained directly from plants and animals or subjected to processes that do not add substances to the food original; 2) culinary ingredients, substances extracted from natural foods or nature itself and used to season and cook meals; 3) processed foods, manufactured by adding salt, sugar or other commonly used culinary substances, such as oil or vinegar, to natural or minimally processed foods; 4) ultra-processed foods, produced through various processing steps and techniques and generally involving many ingredients, many of which are for exclusive use by the industry3. The latter are characterized by their high energy density; and high levels of sugar, salt, and fat; in addition to reduced amounts of fiber, proteins, vitamins, and minerals; and should therefore be avoided4,5.
Recent reviews and meta-analyses demonstrate that high consumption of ultra-processed foods is associated with an increased risk of chronic diseases and mental health disorders. The most commonly observed conditions include a decline in kidney function, wheezing in children and adolescents, diabetes mellitus, overweight, obesity, depression, common mental disorders, cardiovascular diseases, and increased mortality6,7. Furthermore, other studies show a significant association between high consumption of these foods and the risk of developing cancer, including colorectal, breast, and pancreatic cancers8,9.
Information about the nutritional composition of packaged foods, such as the ingredient list and nutrition label, is available on labels to assist consumers in making more informed choices10. However, studies reveal that although many consumers read labels, this reading is often limited to the expiration date due to a low understanding and perception of the information, as well as a lack of technical guidance for interpreting the data presented on packaging by the general population10-12. Furthermore, research indicates that strategies such as front-of-pack warning labeling for critical nutrients in excess and the use of "traffic light" colors to classify products as healthier or less healthy facilitate the interpretation of labeling and influence consumer behavior, helping to promote healthier food choices13-16.
Faced with consumers' challenges in understanding the healthiness of packaged foods, health agencies have sought to standardize the information on labels and improve their understanding. An example is the implementation of Resolution of the Collegiate Board (RDC) No. 429 and Normative Instruction (IN) No. 75, of October 8, 2020, regulated by the National Health Surveillance Agency (ANVISA), which introduced in Brazil the front nutritional labeling of foods, with the use of visual symbols on the front of food packaging to indicate the presence of high levels of added sugars, saturated fat and sodium17,18.
In parallel with these government initiatives, technological tools to support consumers, such as food scoring applications, are emerging, intending to encourage healthier food choices19. Studies on these applications are carried out in Brazil20 and several countries, such as Australia21, the United States22, New Zealand23, and France24, showing that the employment of these applications reduces obstacles to adopting a healthy diet and increases consumers' self-confidence and knowledge on the topic25. These measures, both governmental and independent bodies, provide advances in promoting the population's health by supporting consumers to make more informed choices26.
In Brazil, in 2016, a food-scoring application called Desrotulando was launched, to help consumers identify less processed and nutritionally better-balanced foods. However, up to now, no studies have been identified that characterize this application and that show the most researched types of food and the profile of its users. Thus, this study provides an unprecedented analysis of the profile of foods and users of the Brazilian application. Additionally, it makes a significant contribution to current discussions on nutritional labeling, food composition, and levels of processing, while exploring technological innovations as tools for health support.
Carrying out studies on these consumer support tools can be helpful to understand the main doubts of the Brazilian population about types of food, nutritional composition, and healthiness, as well as to support health professionals in developing food and nutrition education actions. In this context, the purpose of this study was to describe the support application for Brazilian consumers called Desrotulando, focusing on the motivation for users to join the application and the profile of the most researched foods.

METHODS
Study design
This is a descriptive study, carried out with secondary data from the food scoring application called “Desrotulando”.
Desrotulando application
Desrotulando is an application that aims to support consumers in identifying the healthiness of foods, considering a lower degree of industrial processing and nutritional balance, contributing to greater autonomy in adopting an adequate and healthy diet. It was the first food scoring application developed in Brazil, in 2016, and currently has more than 3 million users27,28.
The application evaluates all packaged foods that have labels, except those intended for baby food (baby food and infant formula); some culinary ingredients (salt, sugar, oil, olive oil, lard, yeast, essences, and honey); and foods, such as eggs, water, alcoholic beverages, bulk products, and dietary supplements27. It is updated daily by users when they enter information about the list of ingredients, nutritional table, and photos of the food, which are validated by the application's technical team. Between 2016 and 2023, more than 55 thousand foods were registered, which can be consulted by scanning the barcode, searching by name, or browsing the food category27.
The food score in the application is a score that helps the user identify the best alternatives between products in the same category or between similar categories, enabling more conscious choices27. The analysis of the food score by the application is based on the evaluation of the product quality based on the list of ingredients and healthiness through the presence of critical nutrients and additives, according to the NOVA food classification proposed by the Food Guide for the Brazilian Population2; and guidelines from the Ministry of Health, the National Health Surveillance Agency (ANVISA) and the World Health Organization (WHO). This evaluation is based on the clean label concept, or in other words, it considers healthier foods to be those with a smaller list of ingredients or ingredients that are easily recognized by the consumer27. Additionally, products with the "Orgânico Brasil" seal or source foods or with a protein-high content or dietary fiber, according to the criteria of Normative Instruction No. 75 of 202018, are considered to be more healthful. On the other hand, those products that have cosmetic food additives (change in color, flavor, and texture), non-cosmetic (product conservation), and with precautions (change in toxicity) are less healthy; food substances (ingredients for industrial use); processed and ultra-processed ingredients; trans fat; and excess sodium, added sugar and saturated fat, according to the ranges established in IN nº75 of 202018 and RDC nº429 of 202017,27.
From all this information, an algorithm generates a score from 1 to 100 for each food product analyzed, the higher the score, the better the composition of the food and the better its nutritional composition. This note is categorized according to the traffic light colors, aiming to facilitate the use of the application by the consumer, in 1 to 29 points, red color; 30 to 49 points, orange; 50 to 69 points, yellow color; 70 to 89 points, light green color; and 90 to 100 points, dark green27.
Data collect
The data collected came from user registration and product scans carried out by the application from September 2022 to January 2023. This time interval was chosen due to the large volume of observations in the application and the need to standardize the data collection. The relevant variables for the study were determined based on the modifications made to the application, considering the information collected in a standardized manner over all the evaluated months.
The data were organized into monthly spreadsheets corresponding to the evaluated period. The registrations of new users, identified by random unique ID codes, were analyzed separately, along with the motivation indicated by each user upon registering in the application. For the analysis of the most searched products, each scan performed in the application was recorded in spreadsheets with corresponding information about the product's food category, its degree of processing, and its score in the application.
Thus, the information analyzed regarding food products was: a) Food category (drinks; cookies and snacks; meat; frozen; preserved and canned goods; sweets and desserts; sausages; flours and farofas; grains and cereals; dairy products; butter and margarine; pasta; sauces and condiments; pastes and pates; bread and cakes; or cheeses); b) Degree of food processing according to the NOVA classification (minimally processed foods; culinary ingredients; processed; and ultra-processed); c) Food score defined by the application, that is, the quality and healthiness score, which varies from 1 to 100, with color gradation according to the traffic light (green, yellow, orange, and red). For analysis purposes, the light green and dark green colors were grouped into the same category: green, with scores ranging from 70 to 100 points.
Regarding the user profile, the motivations for using the application were investigated, and categorized into: General Health; Weight control; Infant Food; Disease Control; Avoid Foods of Animal Origin; Allergies/Restrictions; or Sports Use.
Data analysis
As this is an exploratory study, the analysis was descriptive in nature. To examine the data from the scans conducted in the application, the absolute and relative frequencies of the variables associated with the product profiles were calculated, such as food category, degree of processing, and score in the application, categorized by color blocks (green, yellow, orange, and red). Subsequently, the food categories were analyzed separately between ultra-processed and minimally processed products scanned. The relative frequencies of the score color ranges in the application were also calculated among the degrees of processing of the scanned foods. In addition, the absolute and relative frequencies of the motivations of registered users during the analysis period were calculated. All analyses were conducted using the statistical software Stata, version 14.2.
Regarding ethical issues, Desrotulando acts as controller of the personal data provided by users within the legal limits and the Privacy Policy made available for access on the application and on the company website. The data are anonymized for use in academic studies27. Therefore, the study does not require evaluation by the Research Ethics Committee (CEP)29.

RESULTS
Between September 2022 and January 2023, 116,594 new users were registered on the Desrotulando application. The motivations mentioned by most users for joining the application were: General Health (42.4%) and Weight Control (37.2%) (Table 1).
During the period analyzed, 1,286,114 food products were scanned, the majority of which were classified as ultra-processed foods (52.4%), followed by minimally processed foods (21.9%) (Table 2).
Among ultra-processed foods, the most scanned were: sweet biscuits (9.9%), chocolate (8.6%), yogurt (8.0%), soft drinks (6.3%), dairy drinks (4.7% ) and fruit, cereal and protein bars (4.5%); and among the minimally processed: milk (23.1%), fruit drinks (15.2%), yogurt (9.6%) and oats (6.1%) (Table 3).
Regarding the score that refers to the healthiness of the product, the most prevalent was the score of 70 to 100 points - green range (36.5%), followed by scores of 50 to 69 points - yellow range (24.7%), with similar prevalences for the other ranges (Table 4).
When analyzing the distribution of color ranges for food scores scanned according to the NOVA classification, ultra-processed foods have more significant variations in color ranges, with a higher prevalence of the color red (44.2%), while the other categories had higher prevalences in bands of green or yellow colors (Graph 1).

DISCUSSION
During the period analyzed, the number of new users and foods scanned in the Desrotulando application was high, with the majority of users who accessed the application having health and weight control as their motivations. Among the foods scanned, ultra-processed and minimally processed foods were the most researched, with ultra-processed foods, sweet biscuits, chocolates, yogurts, soft drinks, dairy drinks, and bars predominated, while, among minimally processed foods, the consultation of kinds of milk, fruit drinks, yogurts, and oats. Regarding healthiness, most of the foods scanned were more healthful, represented by the colors green and yellow; however, ultra-processed foods presented a score distribution with greater variability, with a predominance of the color red.
There are several applications in the world to promote adequate and healthy eating, such as FoodSwitch, proposed in Australia, which has the same food scanning methodology as Desrotulando21. However, most applications focus mainly on providing quantitative nutritional information regarding energy and macronutrients, with a focus on weight reduction and caloric monitoring, without taking into account the quality of the food30. In this sense, Desrotulando stands out for evaluating, in addition to the nutritional table, the quality of food by comparing the nutritional composition and the presence of additives with the NOVA classification of foods, proposed by the Food Guide for the Brazilian Population2, and also differentiating organic products27. Furthermore, in Brazil, Desrotulando is considered a successful project due to the high number of registered users (3,000,000)28, the size of the food database, and the volume of scans carried out daily.
It is important to highlight that Brazil has about 212.6 million inhabitants31, and in 2023, it was estimated that 163.8 million Brazilians aged 10 years or older owned a cell phone, a number that has been increasing in recent years32. Thus, the 3 million users of the Desrotulando application28 represent 1.4% of the total population of the country. And in relation to the number of mobile phones in use in Brazil, the percentage of application users rises to 1.8%. Furthermore, the impact and high number of downloads in application stores resulted in Desrotulando being awarded as the best application for personal growth in the Google Play Store in 202333. In this context, mobile applications like Desrotulando, which aim to support consumers in choosing healthier foods, can be important tools, as they provide individuals with greater autonomy in selecting nutritionally recommended foods25. Thus, they contribute to health promotion and the prevention and control of NCDs, potentially reducing healthcare costs34.
In this regard, various applications have been developed and tested. For example, in New Zealand, the SaltSwitch application was used to investigate its effectiveness in helping people with cardiovascular diseases make food choices with lower salt content. During the 4-week intervention phase, a significant reduction in average salt purchases per household was observed23. In the United States, the LowSalt4Life application was evaluated to investigate sodium intake reduction in adults with hypertension, resulting in a greater decrease in sodium intake in the intervention group compared to the control group over an 8-week period35. Additionally, the MyNutriCart application was tested to assist Hispanic adults with overweight and obesity in making food choices while shopping, leading to significant improvements in food-related behaviors compared to baseline, including an increase in the purchase of vegetables and whole grains by users36.
These results corroborate the foremost use of Desrotulando in Brazil, which is to improve health, followed by weight control. Concerns about nutrition to promote health and healthy body weight are in line with the increased prevalence of NCDs in Brazil, such as obesity, high blood pressure, and diabetes mellitus37. NCDs are responsible for a significant proportion of deaths worldwide1. Obesity, in particular, is a severe problem in Brazil, with a 72.0% increase in prevalence in recent years, reaching 20.3% of the population in 201938 and 24.3% of adults in all 26 Brazilian capitals and Federal District in 202339.
It is significant to consider that the increase in consumption of ultra-processed foods in Brazil is growing and the frequency of high consumption of these foods was 18.2% in 20194,40. Systematic reviews and meta-analyses show that the consumption of ultra-processed foods is related to a 20% to 81% increase in the risk of various NCDs, especially obesity6,7,41-46.
The foods most scanned by users were ultra-processed, followed by minimally processed foods. The ultra-processed foods most scanned in the Desrotulando application are among the most consumed ultra-processed foods in Brazil4, except for bars (which include fruit, cereal, and protein bars). The same occurs about the most scanned minimally processed foods, which fall into the 20 most consumed food categories in the country47, except for oats. The search to identify information about the healthiness of bars and oats can be justified by the growing trend of consumption of practical snacks48 and by consumers' uncertainty regarding foods with functional and health properties which are increasingly present in contemporary diets, influenced by fitness culture49. It is worth noting that the application does not evaluate the acquisition and consumption of food, but only the consumer interest and curiosity about the food, which may or may not be purchased and consumed.
There is a growing trend towards an increase in the consumption of ultra-processed foods in Brazil, even though Brazilians' diet still consists mainly of fresh, minimally processed foods and culinary ingredients50. The Food Guide for the Brazilian Population reinforces the importance of consuming fresh and minimally processed foods to the detriment of ultra-processed foods2. However, the distinction between these food groups may not be easy generating doubts between the consumers. In this sense, applications such as Desrotulando are significant support tools for consumers to understand better the healthiness of foods and, as a result, better food choices.
Additionally, practical methods, such as applications, in identifying foods according to the NOVA classification are meaningful and should be encouraged as they make the process of differentiating the degree of food processing more efficient51,52. Specifically, for ultra-processed foods, this becomes even more relevant considering that they can range from fresh and minimally processed foods with food additives used to modify color, odor, flavor, or texture; to industrial formulations with various substances and additives, and high levels of sugar, fat and sodium53. In the Desrotulando application, this variation in the composition of ultra-processed foods is captured by the differences in the notes and color bands of green, yellow, orange, and red. However, the predominant color given by the application to ultra-processed foods is red, highlighting the atherogenicity of these foods, in contrast to other foods where green and yellow colors predominate.
In this sense, clearer information about food composition, combined with visual cues such as color differentiation - a resource used by the Desrotulando application - facilitates the comparison of the positive and negative aspects of products at a nutritional level, providing consumers with greater autonomy to make healthier choices in the supermarket13,14. Furthermore, the possibility for food manufacturers and industries to submit their products for evaluation on the application and analyze the ratings and classification criteria fosters ideas for healthier reformulations, especially when combined with the implementation of mandatory front labeling measures15,27. Thus, manufacturers can use the application as a means of validating the nutritional characteristics of their healthier formulations, adding credibility for greater promotion of their brands and recommended foods.
Despite the relevance of its results, this study has limitations. The absence of more detailed information about the user's profiles (gender, age, and education) in the Desrotulando database prevented the identification of sociodemographic differences in the use of the application. Furthermore, as it is based on product scans, the study does not reflect food consumption but only indicates users' access to and curiosity about these foods. The study also does not cover foods not evaluated in the application, such as fresh vegetables and other fresh foods, as well as some culinary ingredients. However, the database allowed the analysis of more than 37,000 types of foods distributed across more than 260 food categories.
It should be noted that, as far as we know, this study provided the first analysis of the profile of foods and users of a support application for adequate and healthy eating in Brazil, including the most scanned types of food and the user's motivations when accessing the application. Furthermore, it demonstrated how the application can be a crucial tool to help Brazilians identify the healthiest foods and make better choices while shopping, with a probable positive impact on their health. In this sense, it is believed that the application constitutes a powerful tool to support food and nutritional education actions conducted by health professionals within the scope of the Unified Health System (SUS as in Portuguese) due to its ease of use and understanding, as well as the wide availability of cell phones in Brazil.

CONCLUSION
The number of new users and foods scanned on the Brazilian application Desrotulando was high, with most users accessing the application looking for health and weight control. The most researched foods were ultra-processed and minimally processed foods, and the majority were healthier (green color and higher scores). However, ultra-processed foods showed a significant variation in healthiness, highlighting the importance of using the application to distinguish them. These results emphasize the relevance of using applications such as Desrotulando to support consumers in food choices to promote health and prevent and control NCDs.

REFERENCES

1. Noncommunicable diseases progress monitor 2020 [Internet]. World Health Organization; 2020 [cited 2024 Oct 26]. Available from: https://www.who.int/publications/i/item/ncd-progress-monitor-2020.
2. Ministério da Saúde (MS). Guia Alimentar para a População Brasileira. 2ª ed. Brasília, DF: MS; 2014.
3. Monteiro CA, Cannon G, Moubarac JC, Martins APB, Martins CA, Garzillo J, Canella DS, Baraldi LG, Barciotte M, Louzada MLC, Levy RB, Claro RM, Jaime PC. Dietary guidelines to nourish humanity and the planet in the twenty-first century. A blueprint from Brazil. Public Health Nutr 2015; v. 18, n. 13, p. 2311-2322.
4. Costa CS, Sattamini IF, Steele EM, Louzada MLC, Claro RM, Monteiro CA. Consumo de alimentos ultraprocessados e associação com fatores sociodemográficos na população adulta das 27 capitais brasileiras (2019). Rev Saude Publica 2021; v. 55.
5. Soares MM, Rocha KSC, Castro KCE, Amâncio NFG. A importância de hábitos saudáveis e adequados na prevenção de doenças crônicas não transmissíveis. Res Soc Dev 2023; v. 12, n. 1, p. e18012139295-e18012139295.
6. Dai S, Wellens J, Yang N, Li D, Wang J, Wang L, Yuan S, He Y, Song P, Munger R, Kent MP, MacFarlane AJ, Mullie P, Duthie S, Little J, Theodoratou E, Li X. Ultra-processed foods and human health: An umbrella review and updated meta-analyses of observational evidence. Clin Nutr 2024; v. 43, n. 6, p. 1386-1394.
7. Lane MM, Gamage E, Du S, Ashtree DN, McGuinness AJ, Gauci S, Baker P, Lawrence M, Rebholz CM, Srour B, Touvier M, Jacka FN, O'Neil A, Segasby T, Marx W. Ultra-processed food exposure and adverse health outcomes: umbrella review of epidemiological meta-analyses. BMJ 2024; v. 384, e077310.
8. Isaksen IM, Dankel SN. Ultra-processed food consumption and cancer risk: A systematic review and meta-analysis. Clin Nutr 2023; v. 42, n. 6, p. 919-928.
9. Cordova R, Viallon V, Fontvieille E, Peruchet-Noray L, Jansana A, Wagner KH, Kyrø C, Tjønneland A, Katzke V, Bajracharya R, Schulze MB, Masala G, Sieri S, Panico S, Ricceri F, Tumino R, Boer JMA, Verschuren WMM, van der Schouw YT, Jakszyn P, Redondo-Sánchez D, Amiano P, Huerta JM, Guevara M, Borné Y, Sonestedt E, Tsilidis KK, Millett C, Heath AK, Aglago EK, Aune D, Gunter MJ, Ferrari P, Huybrechts I, Freisling H. Consumption of ultra-processed foods and risk of multimorbidity of cancer and cardiometabolic diseases: a multinational cohort study. Lancet Reg Health Eur 2023; v. 35, 100771.
10. Pereira MCS, Jesus MCP, Vassimon HS, Nascimento LCG, Tavares MFL. Direito do consumidor às informações nos rótulos dos alimentos: perspectiva de profissionais envolvidos em políticas públicas. Aletheia 2019; v. 52, n. 1.
11. Andrade AAS, Vieira SM, Rosa R. Hábito de leitura e compreensão dos rótulos dos alimentos por consumidores [Internet]. Ciência e tecnologia de alimentos: o avanço da ciência no Brasil - volume 3. Guarujá - SP: Editora Científica Digital; 2023 [cited 2024 Oct 26]. Available from: https://www.editoracientifica.com.br/books/chapter/habito-de-leitura-e-compreensao-dos-rotulos-dos-alimentos-por-consumidores.
12. Silva CK dos S, da Silva FAR, Santos NE da S. Rotulagem nutricional e o consumidor: uma ferramenta promotora da segurança alimentar e nutricional. CLCS 2024; v. 17: e5364.
13. Zhang X, Liu Y, Gu Y, Wang S, Chen H. Red for "stop": "Traffic-light" nutrition labels decrease unhealthy food choices by increasing activity and connectivity in the frontal lobe. Nutrients 2020; v. 12, n. 1, p. 128.
14. Song J, Brown MK, Tan M, MacGregor GA, Webster J, Campbell NRC, Trieu K, Ni Mhurchu C, Cobb LK, He FJ. Impact of color-coded and warning nutrition labelling schemes: a systematic review and network meta-analysis. PLoS Med 2021; v. 18, n. 10, p. e1003765.
15. Kelly B, Ng SH, Carrad A, Pettigrew S. The potential effectiveness of front-of-pack nutrition labeling for improving population diets. Annu Rev Nutr 2024; v. 44, n. 1, p. 405-440.
16. Pettigrew S, Jongenelis M, Maganja D, Hercberg S, Julia C. The ability of nutrition warning labels to improve understanding and choice outcomes among consumers demonstrating preferences for unhealthy foods. J Acad Nutr Diet 2024; v. 124, n. 1, p. 58-64.e1.
17. Brasil. Resolução de Diretoria Colegiada - RDC nº 429, de 8 de outubro de 2020. Dispõe sobre a rotulagem nutricional dos alimentos embalados. Diário Oficial da União, Brasília, DF, 9 out. 2020. Seção 1, p. 106.
18. Brasil. Instrução Normativa - IN nº 75, de 8 de outubro de 2020. Estabelece os requisitos técnicos para declaração da rotulagem nutricional nos alimentos embalados. Diário Oficial da União, Brasília, DF, 9 out. 2020. Seção 1, p. 113.
19. Coughlin SS, Whitehead M, Sheats JQ, Mastromonico J, Hardy D, Smith SA. Smartphone applications for promoting healthy diet and nutrition: a literature review. Jacobs J Food Nutr 2015; v. 2, n. 3, p. 021.
20. Silva ARCS, Ni Mhurchu C, Anastácio LR. Comparison of two front-of-pack nutrition labels for Brazilian consumers using a smartphone APP in a real-world grocery store: a pilot randomized controlled study. Front Nutr 2022; v. 9, p. 898021.
21. Dunford E, Trevena H, Goodsell C, Ng KH, Webster J, Millis A, Goldstein S, Hugueniot O, Neal B. FoodSwitch: a mobile phone app to enable consumers to make healthier food choices and crowdsourcing of national food composition data. JMIR Mhealth Uhealth 2014; v. 2, n. 3, p. e3230.
22. López D, Torres M, Vélez J, Grullon J, Negrón E, Pérez CM, Palacios C. Development and evaluation of a nutritional smartphone application for making smart and healthy choices in grocery shopping. Healthc Inform Res 2017; v. 23, n. 1, p. 16-24.
23. Eyles H, McLean R, Neal B, Jiang Y, Doughty RN, McLean R, Ni Mhurchu C. A salt-reduction smartphone app supports lower-salt food purchases for people with cardiovascular disease: Findings from the SaltSwitch randomised controlled trial. Eur J Prev Cardiol 2017; v. 24, n. 13, p. 1435-1444.
24. Davidou S, Christodoulou A, Fardet A, Frank K. The holistico-reductionist Siga classification according to the degree of food processing: an evaluation of ultra-processed foods in French supermarkets. Food Funct 2020; v. 11, n. 3, p. 2026-2039.
25. Samoggia A, Riedel B. Assessment of nutrition-focused mobile apps' influence on consumers' healthy food behaviour and nutrition knowledge. Food Res Int 2020; v. 128, p. 108766.
26. Geraldo ML, Carvalho NB, Elias LAS, Campos JM, Sousa KROV, Silva VM. Avaliação do impacto da nova rotulagem na indústria de alimentos. Braz J Dev 2023; v. 9, n. 6, p. 19012-19031.
27. ajuda.desrotulando.com [Internet]. Orientações e respostas da equipe de Desrotulando. [cited 2024 Oct 26]. Available from: https://ajuda.desrotulando.com/pt-BR/.
28. Apple Inc. [Internet]. Desrotulando. [cited 2024 Oct 26]. Available from: https://apps.apple.com/br/app/desrotulando/id1071285904.
29. Ministério da Saúde. Resolução nº 510, de 7 de abril de 2016. Dispõe sobre normas aplicáveis a projetos de pesquisa em seres humanos. Conselho Nacional de Saúde 2016, 24 mai.
30. Franco RZ, Fallaize R, Lovegrove JA, Hwang F. Popular nutrition-related mobile apps: a feature assessment. JMIR Mhealth Uhealth 2016; v. 4, n. 3, p. e5846.
31. Instituto Brasileiro de Geografia e Estatística (IBGE) [Internet]. Estimativas da População: 2024. [cited 2024 Oct 26]. Available from: https://www.ibge.gov.br/estatisticas/sociais/populacao/9103-estimativas-de-populacao.html.
32. Instituto Brasileiro de Geografia e Estatística (IBGE) [Internet]. Acesso à internet e à televisão e posse de telefone móvel celular para uso pessoal: 2023. [cited 2024 Oct 26]. Available from: https://biblioteca.ibge.gov.br/index.php/biblioteca-catalogo?view=detalhes&id=2102107.
33. Google Play [Internet]. Best of 2023 Apps. [cited 2024 Oct 26]. Available from: https://play.google.com/store/apps/editorial?id=mc_bestof2023_apps_fcp.
34. Slazus C, Ebrahim Z, Koen N. Mobile health apps: An assessment of needs, perceptions, usability, and efficacy in changing dietary choices. Nutrition 2022; v. 101, p. 111690.
35. Dorsch MP, Cornellier M, Poggi AD, Bilgen F, Chen P, Wu C, An LC, Hummel SL. Effects of a novel contextual just-in-time mobile app intervention (LowSalt4Life) on sodium intake in adults with hypertension: pilot randomized controlled trial. JMIR Mhealth Uhealth 2020; v. 8, n. 8, p. e16696.
36. Palacios C, Torres M, López D, Trak-Fellermeier MA, Coccia C, Pérez CM. Effectiveness of the nutritional app “mynutricart” on food choices related to purchase and dietary behavior: A pilot randomized controlled trial. Nutrients 2018; v. 10, n. 12, p. 1967.
37. Malta DC, Silva AG, Gomes CS, Stopa SR, Oliveira MM, Sardinha LMV, Caixeta RB, Pereira CA, Rios-Neto ELG. Monitoramento das metas dos planos de enfrentamento das Doenças Crônicas Não Transmissíveis: resultados da Pesquisa Nacional de Saúde, 2013 e 2019. Epidemiol Serv Saude 2022; v. 31.
38. abeso.org [Internet]. Mapa da Obedidade. [cited 2024 Oct 26]. Available from: https://abeso.org.br/obesidade-e-sindrome-metabolica/mapa-da-obesidade/.
39. Ministério da Saúde (MS). Vigilância de Fatores de Risco e Proteção para Doenças Crônicas por Inquérito Telefônico (Vigitel Brasil 2023). Brasília: MS; 2023.
40. Louzada MLC, Cruz GL, Silva KAAN, Grassi AGF, Andrade GC, Rauber F, Levy RB, Monteiro CA. Consumo de alimentos ultraprocessados no Brasil: distribuição e evolução temporal 2008–2018. Rev Saude Publica 2023; v. 57, p. 12.
41. Jardim MZ, Costa BVL, Pessoa MC, Duarte CK. Ultra-processed foods increase noncommunicable chronic disease risk. Nutrition Research 2021; v. 95, p. 19-34.
42. Lane MM, Davis JA, Beattie S, Gómez?Donoso C, Loughman A, O'Neil A, Jacka F, Berk M, Page R, Marx W, Rocks T. Ultraprocessed food and chronic noncommunicable diseases: a systematic review and meta?analysis of 43 observational studies. Obes Rev 2021; v. 22, n. 3, p. e13146.
43. Silva JL, Milhomens LM, Luquine Júnior CD, Domene FM, Araújo BC, Silva LALB, Melo RC, Bortoli MC, Toma TS, Barreto JOM. Consumo de alimentos ultraprocessados e risco de sobrepeso e obesidade. Brasília: Fiocruz, 2021.
44. Louzada MLC, Costa CS, Souza TN, Cruz GL, Levy RB, Monteiro CA. Impacto do consumo de alimentos ultraprocessados na saúde de crianças, adolescentes e adultos: revisão de escopo. Cad Saude Publica 2022; v. 37, p. e00323020.
45. Delpino FM, Figueiredo LM, Bielemann RM, Silva BGC, Santos FS, Mintem GC, Flores TR, Arcêncio SA, Nunes BP. Ultra-processed food and risk of type 2 diabetes: a systematic review and meta-analysis of longitudinal studies. Int J Epidemiol 2022; v. 51, n. 4, p. 1120-1141.
46. Wang M, Du X, Huang W, Xu Y. Ultra-processed foods consumption increases the risk of hypertension in adults: a systematic review and meta-analysis. Am J Hypertens 2022; v. 35, n. 10, p. 892-901.
47. Rodrigues RM, Souza AM, Bezerra IN, Pereira RA, Yokoo EM, Sichieri R. Evolução dos alimentos mais consumidos no Brasil entre 2008-2009 e 2017-2018. Rev Saude Publica 2021; v. 55.
48. Mores L, Santos TR, Malinverno E. Tendências alimentares: uma análise da história da alimentação. Braz J Dev 2023; v. 9, n. 8, p. 23724-23730.
49. Costa NCG, Abonizio J. A alimentação fitness: corpo e comida na contemporaneidade. Revista Antropolítica 2023.
50. Levy RB, Andrade GC, Cruz GL, Rauber F, Louzada MLC, Claro RM, Monteiro CA. Três décadas da disponibilidade domiciliar de alimentos segundo a NOVA–Brasil, 1987–2018. Rev Saude Publica 2022; v. 56.
51. Monteiro CA, Cannon G, Levy RB, Moubarac JC, Louzada MLC, Rauber F, Khandpur N, Cediel G, Neri D, Martinez-Steele E, Baraldi LG, Jaime PC. Ultra-processed foods: what they are and how to identify them. Public Health Nutr 2019; v. 22, n. 5, p. 936-941.
52. Martinez-Steele E, Khandpur N, Batis C, Bes-Rastrollo M, Bonaccio M, Cediel G, Huybrechts I, Juul L, Levy RB, Louzada MLC, Machado PP, Moubarac JC, Nansel T, Rauber F, Srour B, Touvier M, Monteiro CA. Best practices for applying the Nova food classification system. Nat Food 2023; p. 1-4.
53. Monteiro CA, Cannon G, Levy R, Moubarac JC, Jaime P, Martins AP, Canella D, Louzada MLC, Parra D, Ricardo C, Calixto G, Machado P, Martins C, Martinez E, Baraldi L, Garzillo J, Sattamini I. Classificação dos alimentos. Saúde Pública. NOVA. A estrela brilha. Word Nutrition 2016; v. 7, n. 1-3, p. 28-40.