---
title: "Applying Brazil’s FoPNL (RDC 429) and PAHO Nutrient Profile Models to Social Media Food Advertisin"
id: "plos-one-6-applying-brazilian-front-of-pack-nutrition-labeling-and-paho-nutritional"
canonical_url: "https://medichelpline.com/clinical-feed/plos-one-6-applying-brazilian-front-of-pack-nutrition-labeling-and-paho-nutritional"
content_type: "clinical_feed_article"
specialty: "General"
source_name: "PLOS ONE (Medicine)"
source_url: "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0354180"
published_at: "2026-07-17T14:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Applying Brazil’s FoPNL (RDC 429) and PAHO Nutrient Profile Models to Social Media Food Advertisin
## Provenance & Clinical Metadata
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- **Specialty:** [General](https://medichelpline.com/clinical-feed/general.md)
- **Primary Source:** PLOS ONE (Medicine)
- **Source URL:** [Original Journal Publication](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0354180)
- **Published At:** 2026-07-17T14:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- This study applied two **Nutrient Profile Models (NPM)**—Brazil’s FoPNL framework (RDC No. 429/2020 together with IN No. 75/2020, hereafter **RDC 429**) and the Pan American Health Organization model (**PAHO**)—to ultra-processed food advertising content on Brazilian social media directed at children and adolescents. - The sample comprised 994 social media posts from 33 brand pages collected in 2023: **623 Instagram**, **257 TikTok**, and **114 YouTube** posts. A total of 1,498 food items (after excluding items without nutrition data) were analyzed. - At the food-item level, **61.28%** of products exceeded at least one criterion under **RDC 429**, with platform-specific non-compliance of **72.63%** on TikTok, **59.88%** on Instagram, and **49.06%** on YouTube. - Under **PAHO**, **93.86%** of food items exceeded at least one critical nutrient threshold, reaching **100%** on TikTok and **98.5%** on YouTube. - **Added sugars** were the most frequent nutrient driving non-compliance across both models (RDC 429: **45.99%** of foods; PAHO: **62.62%** of foods), with higher prevalence on TikTok. - By food category, many ultra-processed categories showed high non-compliance: e.g., under RDC 429 breakfast cereals and ultra-processed cheeses reached up to **90–100%** non-compliance in some platforms; under PAHO most categories exceeded **85%** non-compliance, with several categories at or near **100%** on TikTok and YouTube. - At the advertisement level (classifying a post as non-compliant if it contained at least one violating food), **49.53%** of posts would be restricted under **RDC 429**, while **74.13%** would be restricted under **PAHO**. YouTube showed the highest potential restriction rates under both models. - The authors conclude both NPM are operationally feasible for regulating digital food advertising: **PAHO** provides a stricter, more comprehensive framework, whereas **RDC 429** represents a practical starting point within Brazil due to its current legal status. - The study does not evaluate effectiveness of labeling or restrictions; it provides descriptive analysis and highlights the fragmented regulatory landscape in Brazil and the intensified exposure and persuasive power of digital advertising platforms among youth.
## Clinical Analysis & Structured Key Points
SKIP TO MAIN CONTENT Advertisement plos.org Create account Sign in About Browse Publish advanced search 0 Save 0 Citation 22 View 0 Share OPEN ACCESS PEER-REVIEWED RESEARCH ARTICLE Applying Brazilian front-of-pack nutrition labeling and PAHO nutritional criteria to digital food advertising: regulatory implications for protecting children and adolescents Juliana de Paula Matos , Breenda Lorranny Santos Gonçalves Araújo, Mariana Ribeiro, Laís Amaral Mais, Paula Martins Horta Published: July 17, 2026 https://doi.org/10.1371/journal.pone.0354180 Article Authors Metrics Comments Media Coverage Abstract Introduction Methods Results Discussion References Reader Comments Figures Abstract Front-of-pack nutrition labeling (FoPNL) and restrictions on food advertising are regulatory strategies to support informed dietary choices and reduce exposure to unhealthy food. These measures are often integrated through a policy package, that employs a Nutrient Profile Model (NPM) for the classification of food. In Brazil, however, these policies remain fragmented, and current food advertising regulations do not fully cover all channels, particularly digital media. This study applied the NPM adopted in Brazil’s FoPNL (RDC No. 429/2020 in conjunction with IN No. 75/2020, hereafter RDC 429) and those proposed by the Pan American Health Organization (PAHO) for identifying foods subject to advertising restrictions on social media posts directed at children and adolescents. The sample included posts from ultra-processed food brands/products on Instagram (n = 623), TikTok (n = 257), and YouTube (n = 114). Both NPM were applied to assess non-compliance at the food-item level and at the advertisement level (considering posts containing at least one non-compliant food). At the food-item level, 61.28% of products exceeded at least one item of RDC 429, with the highest prevalence on TikTok (72.63%), while 93.86% were non-compliant according to PAHO, reaching 100% on TikTok and 98.5% on YouTube. At the advertisement level, 49.53% of posts contained at least one non-compliant food under RDC 429, and 74.13% under PAHO, with YouTube showing the greatest potential for restriction (62.16% RDC; 99.10% PAHO). Both models are feasible for regulating digital food advertising: the PAHO provides a robust framework, while RDC 429 offers a strategic starting point given its current implementation in Brazil. Figures Citation: Matos JdP, Araújo BLSG, Ribeiro M, Mais LA, Horta PM (2026) Applying Brazilian front-of-pack nutrition labeling and PAHO nutritional criteria to digital food advertising: regulatory implications for protecting children and adolescents. PLoS One 21(7): e0354180. https://doi.org/10.1371/journal.pone.0354180 Editor: Charles Odilichukwu R. Okpala, University of Georgia, UNITED STATES OF AMERICA Received: December 1, 2025; Accepted: July 3, 2026; Published: July 17, 2026 Copyright: © 2026 Matos et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: All relevant data are within the paper. Funding: This work was supported by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), the Pró-Reitoria de Pesquisa of the Federal University of Minas Gerais (UFMG), and the Brazilian Institute for Consumer Defense (IDEC). Competing interests: The authors have declared that no competing interests exist. Introduction Regulatory measures designed to limit the commercial practices of ultra-processed food corporations are widely recommended to mitigate the health impacts of excessive consumption of these products, particularly the development of noncommunicable diseases (NCD) such as obesity, hypertension, and type 2 diabetes [1,2]. To achieve this objective, such measures should form part of a comprehensive regulatory framework that includes restrictions on advertising directed at children and adolescents, front-of-pack nutrition labeling (FoPNL), taxation of unhealthy products, and controls on the availability of unhealthy foods in institutional settings. Collectively, these actions reshape the food environment in which people purchase and consume food, simultaneously influencing millions of individuals and contributing to the prevention of NCD [3]. Among these regulatory approaches, restrictions on food advertising and the implementation of a FoPNL stand out due to their potential both to reduce population exposure to the marketing of unhealthy foods and to increase awareness of the risks associated with their excessive consumption. Advertising restrictions have been recommended by the World Health Organization (WHO) since 2010, with updated guidance issued in 2023 urging governments to address both the extent of exposure to such marketing and its persuasive power [4]. With respect to FoPNL, WHO recommends government-led regulation as a means of fostering more informed dietary choices by highlighting excessive levels of critical nutrients through warning systems [5]. Although distinct in their mechanisms, these measures are frequently integrated through the adoption of a common Nutrient Profile Model (NPM), which serves as the criterion to determine which foods should be subject to regulation. By definition, NPM are science-based tools for classifying or ranking foods according to their nutritional composition, grounded in health promotion and disease prevention. Their application enables the standardized identification of foods with excessive levels of nutrients of concern such as sugars, sodium, and fats, thereby ensuring greater coherence and effectiveness across regulatory measures [6]. In the Region of the Americas, the Pan American Health Organization (PAHO) has developed a NPM to guide governments in identifying unhealthy foods products and implementing public policies to discourage their consumption. This model defines foods as unhealthy when they contain excessive amounts of free sugars, total fats, saturated fats, trans fats, and sodium, as determined by its NPM [7]. Latin American countries provide relevant examples of how such regulatory packages can be implemented, particularly regarding the simultaneous and coordinated application of advertising restrictions and FoPNL. In Argentina, for instance, Law No. 27,642 of 2021 prohibits the advertising of foods bearing FoPNL for high contents of sugars, sodium, total fats, and saturated fats across multiple media outlets and in school settings [8]. In Chile, Law No. 20,606 of 2012 imposes restrictions on advertisements for foods high in sugars, sodium, and fats, identified through NPM, during peak child-audience hours, in digital media, and in child-focused spaces such as schools [9]. In contrast, Brazil regulates advertising restrictions and FoPNL separately and independently. With respect to advertising, existing legislation prohibits misleading advertising (capable of deceiving consumers) and abusive advertising (particularly when directed at children), as established in the Consumer Defense Code and reinforced by Resolution No. 163 of the National Council for the Rights of Children and Adolescents (CONANDA) [10,11]. Although applicable to food, these provisions are not specifically designed for food advertising. Monitoring studies in Brazil reveal high levels of non-compliance by the food industry, which continues to promote unhealthy products, particularly through child-targeted marketing in both traditional [12] and digital media [13]. Brazilian FoPNL is regulated by Collegiate Board Resolution (RDC) No. 429/2020 [14] and Normative Instruction (IN) No. 75/2020, both issued by the National Health Surveillance Agency (ANVISA) on October 8, 2020 [15]. These regulations mandate the use of a magnifying-glass symbol to identify high levels of nutrients of concern (added sugars, sodium, and saturated fats) in processed and ultraprocess foods (Brasil, 2020a). However, the NPM adopted are not aligned with internationally recommended NPM, establish thresholds regarded as insufficiently strict, and were not validated prior to implementation, thereby limiting their effectiveness and underscoring the need for refinement [16]. In light of this fragmented regulatory framework and the absence of specific legislation on food advertising, integrating FoPNL, already implemented in Brazil, with restrictions on the marketing of unhealthy foods emerges as a strategic approach to strengthening national efforts to combat NCD and to improve the food environment. In this regard, the nutritional parameters applied in labeling could also serve as a basis for coordinating advertising restrictions across different communication channels and media platforms. Progress in this direction is particularly important given the evolving nature of digital advertising strategies. In digital environments, both exposure to and the persuasive power of advertising are intensified, with direct targeting of specific audiences, including children and adolescents, and increased frequency and intensity of exposure, which render these practices more difficult to detect and regulate compared with traditional media [4]. Social media platforms such as TikTok, Instagram, and YouTube are especially influential, given their broad reach and widespread use among children and adolescents. These platforms employ algorithms that personalize content and extend screen time, thereby increasing the likelihood of frequent exposure to ultra-processed food advertising [17]. The objective of this study is to apply the NPM criteria adopted in Brazilian FoPNL and those proposed by PAHO to identify foods subject to advertising restrictions in Brazil, drawing on content disseminated by the ultra-processed food industry targeting children and adolescents on Brazilian social media. It is important to note that this study does not aim to evaluate the effectiveness of FoPNL or advertising restrictions. Rather, it provides a structured descriptive analysis of how different regulatory nutrient profile models may be operationalized to assess and potentially coordinate restrictions on digital food advertising targeting children and adolescents. Methods Sample selection and characterization The identification of brands/products, social media platforms and advertisements eligible for the study was guided by the WHO/Europe CLICK framework, which provides structured guidance for monitoring food marketing across multiple domains [18]. The process was conducted in two stages: (i) defining the set of products/brands and (ii) selecting social media platforms and the corresponding advertisements. In the first stage, a database compiled from five of the largest retail food chains in São Paulo, covering approximately 70% of branded products available in the city, was consulted [19]. Food labels from this database were systematically screened to identify communication elements targeting children and adolescents, based on the criteria described by Borges et al. (2022) [19]. These elements included promotional characters, mascots, references to health or energy, sports-related themes, prizes, and imagery featuring children or fruits and vegetables. This screening yielded 1,054 products displaying at least one child-directed marketing strategy. From this total, only products classified as ultra-processed according to the NOVA classification system [20] were retained, resulting in a subsample of 724 products/brands. YouTube, Instagram, and TikTok were selected as the social media platforms for this study, based on the 2024 TIC Kids Online Brazil survey, a nationally representative study supported by UNESCO, UNICEF, and the Economic Commission for Latin America and the Caribbean (CEPAL). This survey identified these platforms as the most frequently used among Brazilian children and adolescents aged 9–17 years [21]. Subsequently, the official social media accounts of the 724 products/brands were identified for the three selected platforms. Among these, 604 had active accounts on at least one of the platforms. The content of these pages was analyzed using the same child-targeted criteria applied to food packaging. After excluding supermarket chains, companies with broad product portfolios not specifically aimed at children, and duplicate product lines, 33 unique brand pages remained. From each page, 20 posts published in 2023 were randomly sampled, in accordance with CLICK framework recommendations. The final sample comprised 994 posts: 623 from Instagram, 257 from TikTok, and 114 from YouTube. Food identification and classification All industrialized foods displayed in the selected advertisements were identified, and their nutritional information was collected from food labels, brand websites, or retailer websites between August and October 2024. Foods for which nutritional information was unavailable at the time of data collection were excluded (n = 56). In advertisements featuring multiple foods, only items representative of the advertised brand were considered. For example, in an advertisement for a juice brand that also displayed cakes or fruit bars, the juice was classified as eligible. Conversely, when all foods depicted were representative of the brand, for instance, a chocolate brand advertisement featuring various types of chocolates – all items were included in the analysis. The final analytical sample comprised of 1,498 foods. Subsequently, foods were categorized according to the CLICK framework recommendations: (a) candies and chewing gum (29.64%); (b) breads, cakes, and cookies (23.36%); (c) snacks (15.49%); (d) dairy and chocolate beverages (11.48%); (e) sweets and chocolates (7.34%); (f) juices and soft drinks (6.07%); (g) breakfast cereals (4.14%); (h) ultra-processed cheeses (2.40%); and (i) ready-to-eat meals (0.07%) (Tatlow-Golden et al. 2021). Nutritional criteria applied to promoted foods To determine which foods advertised in the selected posts would be subject to restrictions, two NPM were applied: the ANVISA Resolution RDC No. 429/2020 in conjunction with IN No. 75/2020 (hereafter jointly referred to as RDC 429), and the PAHO NPM (hereafter referred to as PAHO). A comparative table outlining the specific features of each model is presented below (Table 1). It should be emphasized that, in the application of the PAHO, only added sugars were considered, as Brazilian nutrition labeling does not provide information on free sugars, which is required by the model. Download: PNG larger image TIFF original image Table 1. Comparison of RDC 429 and PAHO Nutrient Profile Model criteria for foods. https://doi.org/10.1371/journal.pone.0354180.t001 Data analysis Absolute and relative frequencies were used to describe the adequacy of foods according to the two NPM. Classification was performed for each individual criterion of the models and globally, considering a food item as non-compliant if it exceeded at least one criterion. This analysis was conducted at the food-item level for the entire set of advertised foods and stratified by food categories. To assess adequacy at the advertisement level, advertisements featuring more than one food were classified as non-compliant if at least one of the foods exceeded any of the nutritional criteria defined by the models. Permitted advertisements included both those that did not feature foods violating the NPM criteria and brand-only advertisements, i.e., advertisements without any foods present (n = 216 advertisements). All analyses were conducted using a 95% confidence interval, with differences considered significant when confidence intervals did not overlap. Analyses were performed for the overall sample and stratified by social media platform. Statistical analyses were carried out using Stata version 14.0. The dataset was constructed from content that was publicly available across the selected platforms during the study period. Data were collected through a systematic manual procedure based on predefined inclusion criteria. Only institutional or brand-related content was included, and no personal or private user information was accessed. All data collection and analytical procedures were conducted in accordance with the terms of service and conditions of use of the respective platforms. Results At the food-item level, the application of the RDC 429 indicated that 61.28% of foods advertised in social media posts exceeded at least one of the model’s parameters. Among the platforms analyzed, the highest prevalence of non-compliance was observed on TikTok (72.63%), followed by Instagram (59.88%) and YouTube (49.06%). When applying the PAHO, 93.86% of the foods exceeded at least one critical nutrient threshold, with the highest proportions on TikTok (100%) and YouTube (98.50%) (Table 2). Download: PNG larger image TIFF original image Table 2. Application of the RDC 429/2020 and PAHO NPMs to foods advertised on Brazilian social media. https://doi.org/10.1371/journal.pone.0354180.t002 Added sugars were the nutrient with the highest prevalence of non-compliance across both NPM, regardless of the platform. Using the RDC 429, 45.99% of foods exceeded the cut-off for added sugars, with the highest proportion on TikTok (56.01%) and similar values on Instagram (44.64%) and YouTube (35.58%). According to the PAHO, non-compliance for added sugars was even more pronounced, affecting 62.62% of foods analyzed, with minor differences across platforms (Instagram: 60.0%; TikTok: 71.87%; YouTube: 57.30%) (Table 2). At the food-item level and stratified by food category, RDC 429 indicated that 100% of ultra-processed cheeses promoted on posts exceeded at least one nutrient criterion, followed by breakfast cereals (90.32%), breads, cakes, and cookies (88.29%), sweets and chocolates (77.27%), and candies and chewing gum (67.57%). When stratified by social media, Instagram showed a similar pattern, with the same five categories exceeding approximately 65% non-compliance. On TikTok, 100% of ultra-processed cheeses, breakfast cereals, sweets and chocolates, and snacks exceeded at least one RDC 429, while breads, cakes, cookies, and snacks reached 97.73% non-compliance. On YouTube, the highest non-compliance rates were observed in breakfast cereals (100%), sweets and chocolates (100%), breads, cakes, and cookies (83.67%), and ultra-processed cheeses (100%) (Table 3). Download: PNG larger image TIFF original image Table 3. Food categories advertised on Brazilian social media according to non-compliance with at least one nutrient criterion under the RDC 429/2020 and PAHO NPM. https://doi.org/10.1371/journal.pone.0354180.t003 Under the PAHO, non-compliance rates were higher across categories. Except for juices and soft drinks (62.64%), all food categories exceeded at least one nutrient threshold in over 85% of products: pre-prepared meals (100%), ultra-processed cheeses (100%), dairy and chocolate beverages (100%), candies and chewing gum (99.32%), sweets and chocolates (98.18%), breads, cakes, and cookies (96.29%), snacks (86.64%), and breakfast cereals (85.48%). On Instagram, six of these eight categories had non-compliance ≥95%. On TikTok, all analyzed categories reached 100% non-compliance, while on YouTube, all categories except pre-prepared meals (91.84%) reached 100% non-compliance (Table 3). At the advertisement level, 49.53% of posts promoted at least one food exceeding a critical nutrient threshold and would therefore be eligible for restriction under RDC 429, while 74.13% would be restricted under PAHO. Among social media platforms, applying RDC 429, YouTube showed the highest proportion of restricted advertisements (62.16%), followed by Instagram (45.39%). Under PAHO, nearly all YouTube advertisements were restricted (99.10%), exceeding restriction levels observed on Ti
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