Full dataset with the participation of respondents from São Paulo and Salvador, from September 5th to 23rd, 2019.

A consumer survey start-up (Opinion Box®) was hired to apply the questionnaire to individuals over 18 years-old, from September 5th to 23rd, 2019. The survey was elaborated based on a previous study of consumers in Southern Brazil, and composed of 15 multiple-choice and two open-ended questions. Questions 1 to 7 were related to sociodemographic data (gender, income, age, region, city, education, frequency of meat consumption). The questions from 12 to 17 presented the following response categories: very negative, negative, neutral, positive, and very positive. Questions 8 and 10 featured an image depicting conventional and cultivated meat chains.The answers to open-ended questions were analyzed by two researchers, who individually synthesized the phrases into preliminary central ideas, using the Collective Subject Discourse (CSD) method. Then, the results of the individual analyses by the two researchers were considered to define the final central ideas used, which were translated into visual representations in word clouds, where words that come up most frequently are displayed in proportionally larger sizes. The justification for answers to question 11 were also analyzed by the two different researchers, grouping them by similarity, using the CSD method.The following factors were considered as explanatory variables: city (São Paulo, Salvador), gender (male, female), age (18 to 29, 30 to 49, 50 or older), income (up to R$1996.00, R$1997.00 to R$4990.00, more than R$4990.00), education (elementary/high school, higher education, postgraduate degree), and frequency of meat consumption (does not eat, 1 to 3 days a week, 4 to 7 days a week). Knowledge about cultivated meat, consumption intention, and the relationships between cultivated and conventional meat with the environment, human health and animal welfare were the subjects addressed in the questions. For the binary responses (yes or no) we fitted binary logistic regression models, and the results are presented through the odds ratios of a positive response and corresponding confidence intervals (95%), whereas the ordinal response variables (very negative, negative, neutral, positive, very positive) were analyzed by fitting proportional odds regression models, and the results are presented by means of the odds ratios for a more favorable (positive) response. The ordinal scale variables were grouped before fitting the regression models, by combining the two less favorable options as a negative response, and the two more favorable as a positive response. In this case, each ordinal variable presents three categories: negative, neutral, and positive. All questions contained the "I do not know" answer option. Thus, an examination was also carried out on how demographic factors influenced knowledge, or lack thereof, in relation to each of the questions. We present the non-adjusted results, based on univariate regression models, as well as the adjusted results, provided by multiple regression models. All conclusions are based on a 5% significance level. All analyses were carried out using the R software for statistical computation, version 4.3.1. The R library ordinal was used to fit the ordinal regression models.