Impact of processing on polyphenols content in food: A nutritional and statistical analysis of Brazilian menus.

Valéria Silva de Lana, Thais Barcelos de Castro, Livya Alves Oliveira, Stephanie Michelin Santana Pereira, Kelly Aparecida Dias, Rafaela Neto Dos Santos Rodrigues, Ceres Mattos Della Lucia, Fernando Frei, Izabela Maria Montezano de Carvalho
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Abstract

Fresh and minimally processed foods are recognized as important natural sources of phenolic compounds, while industrial processing tends to reduce their concentrations. This in silico study investigated the effect of food processing on the presence of phenolic compounds in Brazilian menus, using linear regression models. The research examined menus from 319 schools in 75 counties in the state of Sergipe, Brazil, analyzing the caloric content, nutrients and polyphenols. These variables were grouped based on similarity and subjected to cluster analysis using Euclidean distance and Ward's method. The foods were classified by the degree of processing, based on NOVA classification, with modifications. The polyphenol content in menus was estimated using the Phenol Explorer database. Cluster analysis revealed three distinct groupings and the results indicated that cluster 2 offered the highest macro and micronutrient values. Linear regression highlighted that the presence of regional foods and culinary ingredients significantly influenced the concentration of flavonoids and phenolic acid in the school menus analyzed. Fresh and minimally processed foods were positively associated with flavonoids without hydrolysis and phenolic acid with hydrolysis. Ultra-processed foods, on the other hand, showed negative associations with flavonoids with hydrolysis. These results provide important insights into the formulation of school menus, with implications for nutrition and public health.

加工对食品中多酚含量的影响:巴西菜单的营养和统计分析。
新鲜和最低限度加工的食品被认为是酚类化合物的重要天然来源,而工业加工往往会降低其浓度。这项计算机研究调查了食品加工对巴西菜单中酚类化合物存在的影响,使用线性回归模型。这项研究检查了巴西塞尔吉佩州75个县的319所学校的菜单,分析了卡路里含量、营养成分和多酚类物质。根据相似性对这些变量进行分组,并使用欧几里得距离和沃德方法进行聚类分析。在NOVA分类的基础上,根据加工程度对食品进行了分类,并进行了修改。菜单中的多酚含量是用苯酚探索者数据库估计的。聚类分析结果显示,聚类2提供的宏量和微量营养素值最高。线性回归显示,区域食物和烹饪成分的存在对所分析的学校菜单中类黄酮和酚酸的浓度有显著影响。新鲜和最低限度加工的食品与未水解的类黄酮和水解的酚酸呈正相关。另一方面,超加工食品与类黄酮水解呈负相关。这些结果为学校菜单的制定提供了重要的见解,对营养和公共卫生有影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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