Análise exploratória dos padrões alimentares de pacientes com adenocarcinoma gástrico: um estudo de caso-controle na Região Brasil Central

Arq Gastroenterol ag Arquivos de Gastroenterologia Arq. Gastroenterol. 0004-2803 1678-4219 Instituto Brasileiro de Estudos e Pesquisas de Gastroenterologia e Outras Especialidades - IBEPEGE. RESUMO Contexto: A dieta é um dos fatores de risco modificáveis mais importante para a incidência de câncer gástrico. Objetivo: Realizar uma análise exploratória sobre os padrões alimentares de indivíduos com adenocarcinoma gástrico (AdG) na região Brasil central. Métodos: Este é um estudo de caso-controle realizado no período de abril de 2019 a julho de 2022, em três centros de referência para o tratamento para câncer em Goiânia-GO. Os casos foram pacientes diagnosticados com AdG, o controle 1 pacientes dispépticos submetidos a endoscopia digestiva alta e o controle 2 pacientes sem queixas gástricas. Nos três grupos foram recrutados pacientes de 18 a 75 anos e de ambos os sexos. Para avaliar o consumo alimentar foi utilizado um Questionário de Frequência Alimentar validado para a população brasileira. Os padrões alimentares foram identificados por Análise Fatorial Exploratória (AFE), utilizando a análise de componentes principais como método de extração, seguida pela rotação Varimax. Resultados: Os valores de comunalidade na AFE para os alimentos/grupos alimentares consumidos pelos casos e controles ficaram acima de 0,30 para todas as variáveis. A variância explicada pelo modelo foi de 66,7%, para casos, 60,3% para o controle 1 e 59,7% para o controle 2. Foram identificados três padrões alimentares nos casos, controle 1 e controle 2 que explicaram 34,87%, 35,41% e 33,25% respectivamente da variância total. O primeiro padrão (“saudável”) foi caracterizado pelo consumo de vegetais, frutas, carne e queijos; o segundo (“não saudável”) por embutidos, pizzas, snacks, ketchup, bebidas doces e macarrão instantâneo e o terceiro (“prudente”) arroz, feijão, carnes e peixes fritos e massas. Conclusão: Esse estudo identificou três padrões alimentares entre os pacientes com AdG e os controles na região Brasil central. De acordo com os padrões identificados, será possível estabelecer uma relação entre a dieta e outras medidas epidemiológicas destinadas à prevenção do câncer gástrico. INTRODUCTION Gastric adenocarcinoma (AdG) is the fifth most common malignant neoplasm and the third leading cause of cancer mortality. AdG incidence rates vary according to gender, age, ethnicity, and socioeconomic status1-3. For each year of the 2020-2022 triennium, approximately 21,000 new cases were estimated to occur in Brazil, 1,320 in the Midwest Region. Although mortality from AdG is declining, in 2020, this neoplasm was responsible for almost 1 million deaths worldwide4,5. The AdG accounts for 95% of tumors located in the stomach and is associated with several non-modifiable (genetic) and modifiable risk factors, such as Helicobacter pylori and Epstein-Bar infection, environmental factors, smoking, alcoholism and eating habits2,3. High consumption of salt (>5 g/day), alcohol (45> g/day), refined carbohydrates, saturated and trans fats, consumption of processed and ultra-processed foods, have been positively associated with AdG. On the other hand, the high consumption of fruits and vegetables has a protective effect on the development of AdG1,3,6,7. Although the eating habits of Brazilians are predominantly composed of vegetables, fruits, milk, and meat, in the last two decades, a trend has been observed in the replacement of in natura foods by ultra-processed foods (UPF)6. A worrying scenario, since the increased consumption of these foods is associated with an imbalance in the supply of nutrients, excessive intake of calories and adverse health outcomes, such as a higher risk of developing gastric cancer6,8,9. The complexity of the human diet represents a challenge for those who intend to study the relationship between diet and disease, since individuals, when eating, ingest a variety of foods and not isolated nutrients. It is likely that the complexity of the diet and the interactive and synergistic effects of food may interfere more with the risk of some diseases than individual food components10. Understanding the dietary patterns of a segment of the population through factor analysis can be an complementary approach to elucidate the relationships between diet and health11. Since diet can play a key role in gastric carcinogenesis, understanding the dietary patterns of patients with AdG is of particular interest in the field of nutritional epidemiology. It is noteworthy that in Goiás the AdG is the fifth cause of death by neoplasms12. Since 2017, in the state, there has been an increase in the consumption of red meat, soft drinks, beer and processed foods. In the same period, there was an increase in the incidence of AdG13,14. Given the scarcity of studies on dietary patterns in patients with AdG in Brazil and especially in the Midwest region of Brazil, where there has been a worsening of diet quality, the objective of this case-control study was to carry out an exploratory analysis of the dietary patterns of patients with AdG in this region of the country. METHODS Design, study population and data collection This is a hospital-based case-control study of AdG that is part of a multicenter study called “Epidemiology and Genomics of Gastric Adenocarcinoma in Brazil” (FAPESP grant no. 2014/26897-0) conducted by the A.C.Camargo Cancer Center, São Paulo. This project is being carried out in five Brazilian capitals, Belém (North Region), Salvador and Fortaleza (Northeast), São Paulo (Southeast) and Goiania (Midwest Region). In this study, patients were recruited in Goiania from April 2019 to July 2022, in public institutions (Clinical Hospital of the Federal University ofGoiás HC/UFG), philanthropic institutions (Association to Combat Cancer in Goiás - Hospital Araújo Jorge - ACCG/HAJ) and private (Brazilian Center for Radiotherapy, Oncology and Mastology - CEBROM and Institute of the Digestive Apparatus - IAD). The sample size calculation was performed using the study power (1-β) of 80%, with α error of 5% and odds ratio (OR) of 2 for the two-tailed hypothesis. Individuals of both sexes, aged between 18 and 75 years, were included in the study. Because it is an exploratory analysis of the dietary pattern, there was no pairing of cases. The cases were patients with AdG, diagnosed in the last two years, through clinical signs, upper digestive endoscopy with biopsy, confirmed by histology and classified by ICD-O3 C.1615. Patients with advanced neoplasms in the terminal state without therapeutic proposal were excluded from the study. The controls consisted of two groups, endoscopic control (control 1) and hospital control (control 2). Control 1 was dyspeptic patients submitted to upper digestive endoscopy, without diagnosis of gastric neoplastic lesions. Control 2 was composed of patients without gastric complaints and without diagnosis or suspicion of gastric cancer, treated in the gynecology, traumatology, and ophthalmology sectors of the HC/UFG. Patients unable to answer the questionnaire due to physical or psychological reasons, those with a previous diagnosis of cancer, except for non-melanoma skin cancer, were excluded from the study. Data were collected through a questionnaire containing sociodemographic information, lifestyle and eating habits. The questionnaires were completed using laptops and tablets by previously trained professionals. Then the information was stored in the RedCap database. With the COVID-19 pandemic, restrictive measures emerged to ensure the health of the population, making it impossible to conduct face-to-face interviews in hospitals16. In this sense, they were adapted to be carried out remotely, by phone call and video call. Study variables The study variables sociodemographic characteristics, lifestyle, and food consumption. Sociodemographic characteristics and lifestyle The sociodemographic variables collected were categorized into gender (male, female), age (≤45, 46-55, 56-65, 66-75 years), level of education (up to 5 years, 6 years and high school, higher education), marital status (married, unmarried) and self-declared ethnicity (white, no white). Anthropometric indices, weight, and height were self-reported by the patient and the Body Mass Index (BMI) was automatically calculated on the RedCap platform. Participants were categorized according to BMI into underweight (<18.5 kg), eutrophic (18.5 to 24.9 kg), overweight (25.0 to 29.9 kg) and obese (30.0 to >60 kg). This categorization was made for the adult and elderly population, according to the World Health Organization (WHO) and Pan American Health Organization (PAHO), respectively17,18. In the lifestyle, the consumption of tobacco and alcoholic beverages was evaluated qualitatively (consumes/does not consume) and for this reason they were included only in the descriptive analyses. Assessment of food consumption Data on food consumption were obtained through the Food Frequency Questionnaire (FFQ) validated for the Brazilian population in patients treated for colorectal cancer19. The FFQ was adapted for the present study, with the inclusion of regional foods. At the time of the interviews, the patients were instructed to answer about their habitual food intake with reference to one year prior to the diagnosis of AdG. The FFQ is composed of 120 food items and categorized into qualitative and quantitative components. In the quantitative component, the pre-defined portions were determined by household measurements or by food unit. The frequency of food consumption was evaluated by the number of times consumed (0-10) per day, week, month, or year, never or rarely, sometimes, always and don’t know. The portion sizes of each food item were classified as small (P50), medium (P75) and large (P150) with percentile distribution of weights for each food consumed in the last 24 months. Consumption was calculated in grams/day: ((amount*portion)/unit days)) x grams. Then the foods/food groups were stratified into tertiles of consumption and regrouped by similarity of nutritional composition into 25 food groups, as shown in Table 1. TABLE 1 Description of the food groups used in the EFA consumed by cases and controls in the period 2019-2022 in Goiania- Goiás. Food groups Description of food grouping (variables - g/day) Tuber and Vegetables Carrot, beet, tomato, onion, chayote, pumpkin, cucumber, zucchini and eggplant. Fruits in general Orange, pineapple, grape, red fruits, banana, apple, papaya, melon, mango, avocado, guava, persimmon, cupuaçu, bacuri, pupunha and soursop. Coffee and tea Coffee and tea Sweets in general Plain cake, stuffed cake, whipped cream, icing, biscuit with and without filling, cereal, chocolate, gelatin, ice cream, candy, and candies. Vegetables and cruciferous Kale, cauliflower, cabbage, and salad. Dark green vegetables Peppers, parsley, lettuce, spinach, watercress, caruru and green smell. Meat and fish (fried and baked) Pork, red meat, chicken, beef grilled, roasted chicken, fried chicken, giblets, barbecue, fried and roasted fish, shrimp and pirarucu. Oil and butter Mayonnaise, butter with or without salt, margarine with or without salt, light margarine, and butter with or without light salt. Pizza, snacks (baked and fried), french fries, popcorn and snacks; Pizza, snacks (baked and fried), french fries, popcorn, and snacks; Ketchup, industrialized pepper sauce, ramen noodles and cream soup Ketchup, industrialized pepper sauce, ramen noodles and cream soup Sweet drinks Soda, industrialized juice, and chocolate milk. Beans and lentils Beans and lentils Pasta Pasta (with and without meat) and lasagna. Sausages in general Sausage, bacon, dried meat, sausage, fried meat, feijoada, sausages, processed meat, canned meat, nuggets, and hot dogs. Rice and brown rice Rice and brown rice French bread and whole meal bread French bread and whole meal bread Cheese Cheese Milk Milk Fried egg Fried egg Fruit smoothies, yogurt, natural fruit juices, Minas cheese, cupuaçu juice, bacuri juice, soursop juice and açaí Fruit smoothies, yogurt, natural fruit juices, Minas cheese, cupuaçu juice, bacuri juice, soursop juice and açaí Egg and potato (boiled) Egg and potato (boiled) Farofa, tapioca, oats and peanuts Farofa, tapioca, oats and peanuts Soup with vegetables and meat Soup with vegetables and meat Spices Salt, vinaigrette, soy drink, mayonnaise, and soy sauce. Pequi Pequi EFA: Exploratory Factor Analysis. Food supplements were excluded because they were not considered food or drink. Regional foods such as jambu and maniçoba were disregarded due to the absence of consumption. Dietary patterns were defined by factor analysis of the 25 food groups. The naming of patterns was based on terminologies recognized in studies of dietary patterns in Brazil and in other countries20. The standards were named as “healthy”, “unhealthy” and “prudent”. Data analysis The chi-square test was applied to verify differences between the independent variables of the cases and controls. The Kruskal-Wallis’s test was used to compare the mean ages for case, control 1 and control 2. Both tests considered a significance level of 5%. Dietary patterns were defined by Exploratory Factor Analysis (EFA) of the 25 food groups, with extraction by principal component analysis, using Varimax orthogonal rotation to simplify the structure. The applicability of the factor analysis of the data was verified using the Kaiser-Meyer-Olklin (KMO) test and Bartllet’s sphericity test. To determine the number of factors to be preserved as main standards, we considered the eigenvalues >1, correlation coefficient (r) >0.30, screen plot and factor interpretability. The commonality index was evaluated to indicate the percentage of variation present in each food group. Some groups had commonality values below 0.30, however, they remained in the analyzes as an adjustment. The factor loadings of the foods/food groups with the highest loads characterized each pattern. Statistical analyzes were performed using Stata 15 (College Station, Texas, 2017) and Statistical Package for Social Science (SPSS) version 23.0 for Windows. Ethical aspects The research was approved by the Research Ethics Committee of the Antônio Prudente Foundation, under the consubstantiated opinion number 3,174,666 (CAAE: 53166915.9.1001.5432). All individuals who agreed to participate in the study previously signed the Free and Informed Consent Form (ICF). RESULTS This multicenter case-control study in Goiania - Goiás was composed of 444 individuals. A total of 49 controls were excluded from the study for not meeting the eligibility criteria. For this study, 100 cases, 158 endoscopic controls and 137 hospital controls were selected, as shown in Figure 1. FIGURE 1 Flowchart of the patients interviewed and selection for a case-control study, in the period 2019-2022 in Goiânia, Goiás. In the case group, 56% were male, 59% over 56 years old, 58% with 6 to 12 years of study and high school education, 73% married, 67% non-white and 43% eutrophic. Controls 1 and 2 were female (62.7% and 70.8%), aged less than or equal to 45 years (43.6% and 57.7%), 6-12 years of education and education medium (77.8% and 74.5%). Most were married (53.2% and 59.8%), non-white (76.6%, 64.2%) and eutrophic (41.1% and 43%). In cases and controls, statistical differences were observed in gender, age, and level of education (P≤0.001) according to Table 2. TABLE 2 Distribution of cases, endoscopic control, hospital control, according to sociodemographic, smoking and alcoholics, in the period 2019-2022 in Goiânia-Goiás. Cases n=100 % Endoscopic control n=158 % Hospitalar Control n=137 % P Sex Male 56 56.0 59 37.3 40 29.2 ≤0.001a Female 44 44.0 99 62.7 97 70.8 Age Age (min-max) 28-73 18-75 19-75 ≤0.001b Mean age (years) ±SD 56±10.0 47.3±15.5 43.9±14.2 Age range ≤45 16 16.0 69 43.6 79 57.7 ≤0.001a 46-55 25 25.0 36 22.8 26 19 56-65 43 43.0 30 19 21 15.3 66-75 16 16.0 23 14.6 11 8 Level of education Up to 5 years 23 23.0 24 15.2 7 5.1 ≤0.001a 6 years of high school 58 58.0 123 77.8 102 74.5 Higher education 19 19.0 11 7.0 28 20.4 Marital status Married 73 73.0 84 53.2 82 59.8 0.006 a Not married c 27 27.0 74 46.8 55 40.2 Ethnicity Withe 33 33.0 37 23.4 49 35.8 0.015 a Not white 67 67.0 121 76.6 88 64.2 BMI (kg/m2) d Low weight (<18,5) 24 24.0 9 5,7 9 6.6 0.084 a Eutrophic (18.5 a 24.9) 43 43.0 67 42.4 56 40.9 Overweight (25.0 a 29.9) 18 18.0 43 27.2 42 30.6 Obesity (30.0 a >60.0) 15 15.0 39 24.7 30 21.9 Tobacco consumption Smoked regularly 50 50 59 37.3 44 32.1 0.018 Alcohol consumption Consumed alcohol regularly 59 59 82 52 67 49 0.3 a Pearson’s X2 test; bKruskal-Wallis’s test; csingle, divorced, separated, widowed or cohabiting; dBMI ≤60 years WHO, >60 years PAHO. The mean consumption (g/day) of food ingested by patients in the case and control groups were calculated. The results showed that some marker foods of unhealthy eating such as sweets in general, sausages and sweet drinks were two to three times more consumed by patients with AdG (Table 3). TABLE 3 Mean daily intake (g/day) of foods or food groups consumed by the cases, endoscopic control, hospitalar control, in the period 2019-2022 in Goiânia-Goiás. Food groups Case n=100 Endoscopic control n=158 Hospitalar control n=137 Tuber and legum 91.56 77.75 96.35 Fruit 296.93 207.86 248.12 Coffee and tea 275.70 247.73 171.94 Sweets in general 119.73 104.08 58.82 Vegetables and crucifers 29.34 23.33 29.67 Dark green vegetables 35.14 33.97 36.37 Meat and fish (fried and baked) 148.54 142.18 120.68 Oil and butter 14.89 12.76 10.68 Pizza, French fries, Popcorn and snacks 60.63 64.61 40.78 Catchup, industrialized pepper sauce, noodles and cream soup 19.05 24.48 10.95 Sweet drinks 350.80 207.37 112.41 Beans and lentils 151.87 140.93 102.86 Pasta 58.53 67.35 50.55 Sausage 101.54 90.28 70.21 Rice and brown rice 260.19 237.71 177.31 French bread and whole grain bread 49.14 42.27 39.40 Cheese 7.85 6.57 8.43 Milk 155.17 8.22 67.97 Fried egg 11.66 14.65 11.97 Vitamin, juices, yogurt and Mina’s cheese 161.57 155.72 148.59 Egg and potato (boiled) 42.70 44.14 37.89 Farofa, Tapioca, Oats and Peanuts 46.83 32.41 28.90 Soup with vegetables and meat 47.76 43.48 37.89 Seasonings 4.72 6.03 2.64 Pequi 21.31 9.96 7.87 In the Exploratory Factor Analysis, commonality values above 0.30 were included. All groups were factorable with KMO >0.50 and the sphericity guess test <0.001. The variance explained by the model for cases was 66.7%, endoscopic controls 60.3% and hospital controls 59.7% (Table 4) distributed into 9, 8 and 8 factors, respectively. In this study, it was decided to maintain only the three factors that most explained the total variance in food intake. The screen plot of eigenvalues retained the three main dietary patterns, separately for the cases, control 1 and control 2. The matrices of these factors are listed in TABLE 5. Three dietary patterns were identified in the study population. TABLE 4 Commonality for the foods/food groups consumed by the cases, endoscopic controls and hospital control in the period 2019-2022 in Goiânia-Goiás. Food Groups Commonality Case Endoscopic Control Hospital Control Tubers and vegetable 0.669 0.674 0.647 Fruit 0.630 0.557 0.658 Coffee and tea 0.742 0.629 0.585 Sweets in general 0.562 0.527 0.658 Vegetables and cruciferous 0.607 0.599 0.688 Dark green vegetables 0.690 0.595 0.632 Meat and fish (fried and baked) 0.497 0.546 0.547 Oil and butter 0.664 0.657 0.659 Pizza. snacks (fried and baked). french fries. popcorn and snacks 0.661 0.657 0.541 Ketchup. industrialized pepper sauce. ramen noodles and cream soup 0.668 0.586 0.639 Sweet drinks 0.681 0.593 0.581 Beans and lentils 0.787 0.752 0.727 Pasta 0.639 0.467 0.498 Sausages in general 0.680 0.640 0.597 Rice and brown rice 0.785 0.686 0.727 French bread and whole meal bread 0.674 0.653 0.749 Cheese 0.675 0.571 0.515 Milk 0.685 0.586 0.677 Fried egg 0.677 0.737 0.439 Fruit smoothies. yogurt. natural fruit juices. Mina’s cheese 0.569 0.575 0.618 Egg and potato (boiled) 0.737 0.636 0.465 Farofa. tapioca. oats and peanuts 0.792 0.598 0.521 Soup with vegetables and meat 0.668 0.514 0.399 Spices 0.582 0.474 0.407 Pequi 0.653 0.566 0.748 KMO 0.648 0.728 0.661 Sphericity <0.001 <0.001 <0.001 Explained Variance (%) 66.699 60.303 59.685 KMO: Kaiser-Meyer-Olklin. For the cases, the main pattern was “healthy”, with a predominance of tubers and vegetables, crucifers and fruits. The other variables that constituted this pattern were vitamins, juice, yogurt and minas cheese; soup with vegetables and meat; dark green vegetables and cheese. The second “unhealthy” category was characterized by sweet drinks; sausages; pizzas, snacks and popcorn. The third “prudent” pattern consisted of oil and butter; french and wholemeal bread, and sweets in general. These three patterns explained 34.9% of the total variance (Table 5). TABLE 5 Factor loadings of food groups for the three dietary patterns identified in the cases, endoscopic control and hospitalar control in the period 2019-2022 in Goiânia-Goiás. Case Pattern Endoscopic Control Pattern Hospitalar Control Pattern S NS P NS S P S NS P Tubers and vegetables 0.788 Tubers and vegetables 0.752 Tubers and vegetables 0.764 Vegetables and cruciferous 0.755 Vegetables and cruciferous 0.722 Vegetables and cruciferous 0.759 Fruits 0.675 Fruits 0.694 Dark green vegetables 0.699 Vitamin, juice, yogurt and Minas cheese 0.646 Vitamin, juice, yogurt and Minas cheese 0.694 Fried egg 0.439 Soup with vegetables and meat 0.627 Soup with vegetables and meat 0.527 Soup with vegetables and meat 0.374 Dark green vegetables 0.568 Dark green vegetables 0.516 Ketchup, industrialized chili sauce, instant noodles, soup 0.714 Cheese 0.372 Cheese 0.775 Pasta 0.654 Sweet drinks 0.794 Sweet drinks 0.735 Pizza, snacks, french fries and popcorn 0.541 Sausages 0.754 Sausages 0.625 Sausages 0.46 Pizza, snacks, french fries and popcorn 0.529 Pizza, snacks, french fries and popcorn 0.567 Spices 0.333 Oil and butter 0.777 Oil and butter 0.849 Fried and roasted meat, fish, shrimp and pirarucu 0.355 French and wholemeal bread 0.762 French and wholemeal bread 0.808 Vitamin, juice, yogurt and Minas cheese 0.755 Sweets in general 0.428 Sweets in general 0.455 Fruits 0.728 Tubers and vegetables 0.361 Boiled egg and potato 0.429 Farofa, tapioca, oats, and peanuts 0.379 KMO 0.648 0.728 0.661 Accumulated variance 34.87% 35.41% 33.25% Bartllet’s sphericity test P<0.001 S: healthy; NS: not healthy; P: prudent; KMO: Kaiser-Meyer-Olklin. In endoscopic control, the accumulated variance was 35.4%. The first pattern called “unhealthy” showed a predominance of industrialized foods such as pizzas, snacks, french fries and popcorn; ketchup, industrial pepper sauce, instant noodles, soup; sweet drinks; sausages; spices and sweets in general. In second pattern (“healthy”), consumption of tubers and vegetables; crucifers and dark green vegetables was observed. In third pattern (prudent) the foods consumed were beans and lentils; rice and brown rice; meat, fried and roasted fish, shrimp and arapaima and pastes (Table 5). In hospital control, the first pattern (healthy) consisted of tubers and vegetables; vegetables and crucifers; dark green vegetables; fried egg and soup with vegetables and meat. The second pattern (unhealthy) was categorized by consumption; ketchup, industrial hot sauce, instant noodles, soup; pasta; pizzas, snacks, french fries and popcorn; sausages; spices; meat, fried and roasted fish, shrimp and pirarucu. In the third pattern (prudent) it was composed of vitamin, juice, yogurt and Mina’s cheese; fruits; egg and boiled potato; farofa, tapioca, oats and peanuts (Table 5). DISCUSSION In developing countries, studies that identify dietary patterns are scarce. Food consumption patterns of population groups may vary according to sex, socioeconomic status, ethnicity, and geographic region21. In this study, it was possible to identify three dietary patterns, “healthy”, “unhealthy” and “prudent”. Interestingly, the main pattern identified in the case group was “healthy”, with a predominance of vegetables and fruits. A similar pattern has been observed in other case-control studies of esophageal, gastric, and colorectal cancer adenocarcinoma22-24. The “healthy” pattern may be related to the recommendations of a healthier diet at the time of diagnosis, or by the spontaneous change in the onset of symptoms of this neoplasm in order to relieve gastrointestinal discomfort25. Another hypothesis for this finding may be due to the memory bias characteristic of case-control studies, however, it is unlikely that distorted reports have occurred since cancer patients tend to remember more easily their lifestyle habits in the past, due to the feeling of guilt of developing the disease26. The second pattern of cases (“unhealthy”) and the third pattern (“prudent”) were composed of processed foods and oil and butter, respectively. These foods are rich in fats and sugars with high energy value. A previous study carried out in São Paulo also observed a pattern characterized by the predominance of sweets11. A diet high in sugars, can increase down-regulate glucose, and insulin levels, and lead to obesity. These clinical conditions induce the production of inflammatory mediators associated with carcinogenesis, as well as the production of endogenous sex steroid hormones, which contribute to tumor growth27. In addition, the intake of these industrialized foods with unfavorable nutritional composition can increase the risk of gastric cancer by up to 50% and the risk of cancers in general by 10%28,29. The “unhealthy” and “prudent” patterns may be more associated with AdG than the healthy factor considered alone. It is noteworthy that a diet is composed of several food groups and there is a synergism between nutrients and their composition30. Most individuals in the case group consumed alcohol regularly, in this exploratory descriptive analysis, the association among alcohol consumption and AdG was not calculated. However, individuals who consume alcohol regularly prefer for salty foods, high intake of fast food and low intake of fruit. This unhealthy eating pattern represents a risk factor for AdG31. In the endoscopic control, the predominant pattern was “unhealthy”, characterized by industrialized or ready-to-eat foods. In this group, most individuals were under 45 years old. The age of the endoscopic controls may have influenced the observed dietary pattern. As this is an economically active population, meals are possibly eaten quickly and are often limited to fast foods. Similar results were observed in young adults in the Southeast region of Brazil, where consumption of processed foods was high in this age group32. In the Midwest Region, the Family Budget Survey (FBS-2018) showed that in the purchase of basic foods reduces spending on beverages, processed foods and ready-to-eat meals increased14. The high caloric value and the unfavorable nutritional composition of this pattern may explain the gastric complaints presented by the endoscopic control and the high proportion of overweight individuals. As these are young adults, maintaining this pattern may affect gastric health and increase the risk of AdG33. The second factor (healthy) of the endoscopic control was composed of healthy eating markers, and the third factor (prudent) presented foods such as rice and beans, pasta, meat, fried fish, and shrimp. Fried foods and the high starch content present in this pattern are related to damage to the gastric mucosa28. In hospital control, the main dietary pattern was “healthy”, composed mainly of tubers, vegetables; vegetables dark green and cruciferous. These foods provide a series of antioxidants, phenolic compounds, phytoestrogens, and fibers that have a protective role against gastric diseases34. Among the limitations of the study, we highlight the memory bias inherent to case-control studies and the application of the FFQ. To minimize these limitations, the FFQ was applied by previously trained interviewers. It is recognized that it is quite difficult to accurately remember the diet consumed in the past, however during the interview the portions were referred to in household measures that are well known and used daily. The inclusion criteria of the cases and controls were used to avoid selection bias. The strong points of this study were the factorial analysis that allowed the identification of eating patterns in the population of the center-west of Brazil. This identification is unprecedented in patients with AdG in this region. In addition, another strong point was the remote adaptation and standardization of interviews, which characterizes a novelty in the scientific environment. This adaptation was necessary because of the limitations imposed by the pandemic caused by the Sars-CoV-2 virus16. CONCLUSION In the case and hospital control groups, the predominant dietary pattern was “healthy”, while in the endoscopic control it was “unhealthy”. 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