Objective: To expose the likely impact of genetically modified foods in Collective Feeding. Methods: This was a case study conducted on a steel company (SC) in Rio de Janeiro State. The likely impact recognition began...Objective: To expose the likely impact of genetically modified foods in Collective Feeding. Methods: This was a case study conducted on a steel company (SC) in Rio de Janeiro State. The likely impact recognition began with the preparation of a soy food products’ list. Then, we verified these products’ frequency on the Food and Nutrition Unit (FNU) menu from the SC, outlining the offer profile. We calculated odds ratios and binomial distribution probability for assessing exposure to soy that may be transgenic. Food frequency questionnaire (FFQ) regarding soy products was applied. The convergence of daily products’ relative frequency of this population and the population from a reference study about FFQ validation in Rio de Janeiro was verified. Confrontation took place between the classification of foods by the consumers’ likely exposure to soy and the percentage deviation between observed relative frequency of products’ intake offered on the FNU and on the reference study. Results: A list of 51 products were created and 16 of them integrated the menu, e.g. flour, chicken, sausage, maize, instant pudding, bologna, hot dogs and peanuts. Food usually consumed by FNU users and concomitantly consumed in reference study were cookies, flour, spaghetti, bread, cake, instant pudding, sausage and hot dogs. By the classification and percentage deviations results, cookies, breads and pasta were the “villains” of soy’s susceptibility. Coclusion: It was possible to show the likely impact of genetically modified foods in Collective Feeding, confirming that these consumers were exposed to soybeans that may be transgenic.展开更多
文摘Objective: To expose the likely impact of genetically modified foods in Collective Feeding. Methods: This was a case study conducted on a steel company (SC) in Rio de Janeiro State. The likely impact recognition began with the preparation of a soy food products’ list. Then, we verified these products’ frequency on the Food and Nutrition Unit (FNU) menu from the SC, outlining the offer profile. We calculated odds ratios and binomial distribution probability for assessing exposure to soy that may be transgenic. Food frequency questionnaire (FFQ) regarding soy products was applied. The convergence of daily products’ relative frequency of this population and the population from a reference study about FFQ validation in Rio de Janeiro was verified. Confrontation took place between the classification of foods by the consumers’ likely exposure to soy and the percentage deviation between observed relative frequency of products’ intake offered on the FNU and on the reference study. Results: A list of 51 products were created and 16 of them integrated the menu, e.g. flour, chicken, sausage, maize, instant pudding, bologna, hot dogs and peanuts. Food usually consumed by FNU users and concomitantly consumed in reference study were cookies, flour, spaghetti, bread, cake, instant pudding, sausage and hot dogs. By the classification and percentage deviations results, cookies, breads and pasta were the “villains” of soy’s susceptibility. Coclusion: It was possible to show the likely impact of genetically modified foods in Collective Feeding, confirming that these consumers were exposed to soybeans that may be transgenic.
