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Introdução: A ingestão de aditivos por meio dos alimentos industrializados pode impactar a saúde humana. Diante disso, surge à tendência clean label visando produtos mais saudáveis e naturais. Objetivo: Analisar a proporção de produtos clean label e dos principais aditivos presentes em alimentos industrializados, comparando-os aos análogos clean label. Métodos: Estudo transversal, descritivo, onde compilou-se aditivos presentes nas listas de ingredientes de três categorias de alimentos (hambúrgueres de carne, iogurtes e pós para o preparo de gelatina). As informações foram extraídas de um banco de dados de 2021, por meio de coleta em supermercados de Belo Horizonte-Minas Gerais (MG). Resultados e Discussão: Atingiu-se um número final de 157 produtos: hambúrgueres de carne (n=14), pós para o preparo de gelatina (n=51) e iogurtes (n=92). Apenas 16 produtos (10,2%) foram considerados clean label ou similares. A categoria de pós para o preparo de gelatina apresentou maior média de aditivos (7,3). Os principais aditivos encontrados foram: Tripolifosfato de Sódio (100%; n=12) nos hambúrgueres de carne, Sorbato de Potássio (92%; n=77) nos iogurtes e Acessulfame de Potássio (89%; n=40) nos pós para o preparo de gelatina. Após levantamento dos aditivos mais frequentes, uma discussão sobre o impacto na saúde foi realizada. Conclusão: Os resultados indicaram que a maioria dos produtos avaliados possui 5 ou mais aditivos em sua composição e que os aditivos mais frequentes podem ter efeito negativo à saúde, logo a alternativa de alimentos clean label pode oferecer um mesmo aporte nutricional sem os riscos inerentes à ingestão de aditivos químicos. (AU)
Introduction: The ingestion of food additives in processed foods can impact human health. Considering this, the clean label trend arises with healthier and more natural ingredients. Objective: To analyze the proportion of clean label products and the main additives present in industrialized foods, comparing them to their clean label analogues. Methods: A cross-sectional, descriptive study, in which the additives present in the ingredients lists of three categories of industrialized foods (meat-based hamburgers, yogurts and powders for gelatin) were compiled. The information was extracted from a database built in 2021, through collection in supermarkets in Belo Horizonte-MG. Results and Discussion: A final number of 157 products was reached: meat-based hamburgers (n=14), powders for gelatin (n=51) and yogurts (n=92). Only 16 products (10.2%) were considered clean label or similar. The category of powders for gelatin had the highest average of additives per product (7.3). The main additives found were: Sodium Tripolyphosphate (100%; n=12) in meat-based hamburgers, Potassium Sorbate (92%; n=77) in yogurts and Acesulfame Potassium (89%; n=40) in powders for gelatin. After surveying the most frequent additives, a discussion about their impact on health was held. Conclusion: The results indicated that most of the evaluated products have 5 or more additives in their composition and that the most frequent additives can have a negative effect on health, so the clean label food alternative can offer the same nutritional contribution without the risks inherent to the ingestion of chemical additives. (AU)
ABSTRACT
ABSTRACT Objective: This study aimed to evaluate food labels targeted at children and identify the concomitant presence of claims and high levels of critical nutrients and/or the presence of sweeteners. As a secondary objective, it aimed to list different types of claims and check which marketing strategies are most used. Methods: We collected 409 products, from 8 popular food groups targeted at children, in Brazilian market (i.e., fruit drinks, dairy drinks, sandwich cookies, cakes, breakfast cereals, jellies, corn snacks, and yogurts). The contents of critical nutrients (e.g., sugar, total fat, saturated fat, and trans-fat, and sodium) and presence/absence of sweetener were calculated, considering Pan American Health Organization (PAHO) parameters. Then, we verified the presence and types of claims in these products. Results: Overall, 265 (64.7%) labels presented claims. In three of the eight categories (i.e., breakfast cereals, dairy drinks, and yogurt), all products with claims (50, 34, and 34 products, respectively) had one or more nutrients in harmful concentrations (critical nutrients above PAHO's nutritional profile and/or presence of sweeteners). In the other categories, only one product (of 63 sandwich cookies and 26 breakfast cereals with claims) and three products (of 22 cakes and 28 jellies with claims) had no nutrient in critical concentration. The presence of claims, like "rich/source" of micronutrient, was predominant in seven of the eight food groups. Conclusion: In the present study, there was a high presence of claims, of different types, in foods targeted at children, which, for the most part, also have excess of at least one critical nutrient, according to PAHO.
RESUMO Objetivo: Avaliar rótulos de alimentos direcionados ao público infantil e identificar a presença concomitante de alegações e de altos teores de nutrientes críticos e/ou presença de adoçantes. Como objetivo secundário, listar os diferentes tipos de alegações e verificar quais estratégias de marketing são mais utilizadas. Métodos: Foram coletados 409 produtos provenientes das oito categorias de alimentos mais populares entre crianças brasileiras (bebidas à base de frutas, bebidas lácteas, biscoitos recheados, bolos, cereais matinais, gelatinas, salgadinhos de milho e iogurtes). Foram calculados os teores de nutrientes críticos (açúcares, gorduras totais, saturadas e trans e sódio) e presença/ausência de adoçante, considerando-se os parâmetros da Organização Pan-Americana de Saúde (OPAS). Em seguida, verificamos a presença e os tipos de alegações nesses produtos. Resultados: No total, 265 (64,7%) rótulos apresentaram alegações. Em três das oito categorias (cereais matinais, bebidas lácteas e iogurtes), todos os produtos com alegações (50, 34 e 34 produtos, respectivamente) continham um ou mais nutrientes em concentrações prejudiciais (nutrientes críticos acima do preconizado pela OPAS e/ou presença de edulcorantes). Nas demais categorias, apenas um produto (de 63 biscoitos recheados e 26 cereais matinais com alegação) e três (de 22 bolos e 28 gelatinas com alegação) não apresentavam nutrientes em concentração crítica. A presença de alegações, como "rico" ou "fonte" de micronutriente, foi predominante em sete dos oito grupos de alimentos. Conclusões: Observou-se alta presença de alegações, de diferentes tipos, em alimentos destinados a crianças, que, em sua maioria, também possuem excesso de pelo menos um nutriente crítico, de acordo com a OPAS.
ABSTRACT
OBJECTIVE: This study aimed to evaluate food labels targeted at children and identify the concomitant presence of claims and high levels of critical nutrients and/or the presence of sweeteners. As a secondary objective, it aimed to list different types of claims and check which marketing strategies are most used. METHODS: We collected 409 products, from 8 popular food groups targeted at children, in Brazilian market (i.e., fruit drinks, dairy drinks, sandwich cookies, cakes, breakfast cereals, jellies, corn snacks, and yogurts). The contents of critical nutrients (e.g., sugar, total fat, saturated fat, and trans-fat, and sodium) and presence/absence of sweetener were calculated, considering Pan American Health Organization (PAHO) parameters. Then, we verified the presence and types of claims in these products. RESULTS: Overall, 265 (64.7%) labels presented claims. In three of the eight categories (i.e., breakfast cereals, dairy drinks, and yogurt), all products with claims (50, 34, and 34 products, respectively) had one or more nutrients in harmful concentrations (critical nutrients above PAHO's nutritional profile and/or presence of sweeteners). In the other categories, only one product (of 63 sandwich cookies and 26 breakfast cereals with claims) and three products (of 22 cakes and 28 jellies with claims) had no nutrient in critical concentration. The presence of claims, like "rich/source" of micronutrient, was predominant in seven of the eight food groups. CONCLUSION: In the present study, there was a high presence of claims, of different types, in foods targeted at children, which, for the most part, also have excess of at least one critical nutrient, according to PAHO.
Subject(s)
Food Labeling , Nutrients , Child , Humans , Nutritive Value , Brazil , Sweetening AgentsABSTRACT
Nutrient profiling is the science of classifying or ranking foods according to their nutritional composition, for reasons related to disease prevention and health promotion. To be effective, policies such as front-of-pack nutrition labeling (FoPNL) must have an adequate nutritional profile model, since it will determine which products will be eligible to receive a FoPNL. This study aimed to determine the percentage of packaged food and drink products available in Brazil that would be subject to FoPNL under two different legislations: Brazilian and Mexican. This is a cross-sectional study in which we collected information on food products (photos of the ingredients list, the front label, the barcode, and the nutrition facts table) from one of the largest stores of a supermarket chain in the city of Belo Horizonte-MG, Brazil, from March to May 2021 (~6 months after the publication of the Brazilian legislation about FoPNL and a year and a half before the legislation came into force). The products were classified in relation to the BNPM (added sugars, saturated fats, and sodium) and the MNPM (energy, free sugars, saturated fats, trans fats, sodium, non-sugar sweeteners, and caffeine). A total of 3384 products were collected and, after applying the exclusion criteria, 3,335 products were evaluated. Of these, 2,901 would be eligible to receive FoPNL in Brazil and 2,914 would be eligible to receive FoPNL in Mexico. According to the BNPM, 56.7% (95% CI 54.9; 58.5%) of the products were "high in" critical nutrients, 27.1% (95% CI 25.5; 28.7%) of the products in added sugars, 26.7% (95% CI 25.2; 28.4%) of the products in saturated fats, and 21.4% (95% CI 19.9; 22.9%) of the products in sodium. As for the MNPM, 96.8% (95% CI 96.1; 97.4%) of them were "high in" up to five critical nutrients and up to two warning rectangles (caffeine and non-sugar sweeteners), 45.8% (95% CI 44.0; 47.6%) of them in free sugars, 43.7% (95% CI 41.9; 45.5%) of them in saturated fats, and 47.9% (95% CI 46.1; 49.7%) of them in sodium. We concluded that the eligibility to receive FoPNL by BNPM and MNPM was relatively similar between products; however, almost all products would have at least one FoPNL and/or warning rectangles according to Mexican legislation, and nearly half of them would have at least one FoPNL, considering BNPM. The MNPM is much more restrictive than the BNPM. The Nutrient Profile Model (NPM) that regulates FoPNL, and other health policies, must be carefully defined to ensure that foods are properly classified according to their healthiness.
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[This corrects the article DOI: 10.3389/fnut.2022.898021.].
ABSTRACT
One of the suggestions for improving the understanding of food labels is implementing front-of-pack nutrition labeling (FoPNL), where nutritional information is objectively made available to consumers. Scientific data on the best FoPNL model to be adopted for the Brazilian population is still emerging, especially in real-world purchase situations. This study aims to evaluate/compare the proposed Brazilian and Mexican FoPNL systems, on different outcome measures, using an application, in dairy foods available in a supermarket aisle. This pilot randomized controlled trial in a real-world purchase situation was conducted in June/July 2021. A total of 230 participants were randomly allocated to one of the three study arms (Mexican and Brazilian FoPNL systems or control-nutritional information table and ingredients list). Using a smartphone, the participants scanned a product barcode and received the allocated FoPNL (with information about excessive added sugars, sodium, and/or saturated fat content) or the control. After, they answered questions related to our primary outcome (decision to buy or not to buy a product) and secondary outcomes (perceived healthiness, facilitation of a quick purchase decision, and identification of excess nutrients). The Mexican FoPNL system performed better in the primary outcome (3.74 ± 1.34) and "facilitation of a quick purchase decision" (3.59 ± 1.31), compared to the control (3.28 ± 1.45;p = 0.043 and 3.11 ± 1.42; p = 0.029). The Mexican FoPNL system performed better in supporting consumers to identify dairy foods, among the selected sample in this study, high in added sugars than the control (82.2% and 63.5% of correct answers, respectively; p = 0.009). For saturated fats, the Brazilian FoPNL resulted in 93.1% of correct answers against 48.2% for the control and 58.9% for the Mexican system (p ≤ 0.001). The Mexican FoPNL system facilitated consumer decision-making on when to buy or not to buy a selected dairy product and in helping to quickly decide which dairy products to buy, among the selected sample in this study, compared to the control. Considering the right answers of critical nutrients in excess or not, both models of FoPNL, delivered by a smartphone app, performed well.
ABSTRACT
Grape, orange, peach and passion fruit nectars were formulated and adulterated by dilution with syrup, apple and cashew juices at 10 levels for each adulterant. Attenuated total reflectance Fourier transform mid infrared (ATR-FTIR) spectra were obtained. Partial least squares (PLS) multivariate calibration models allied to different variable selection methods, such as interval partial least squares (iPLS), ordered predictors selection (OPS) and genetic algorithm (GA), were used to quantify the main fruits. PLS improved by iPLS-OPS variable selection showed the highest predictive capacity to quantify the main fruit contents. The selected variables in the final models varied from 72 to 100; the root mean square errors of prediction were estimated from 0.5 to 2.6%; the correlation coefficients of prediction ranged from 0.948 to 0.990; and, the mean relative errors of prediction varied from 3.0 to 6.7%. All of the developed models were validated.
