The Impact of Ultra-Processed Foods on Dietary Patterns in Patients with Metabolic Dysfunction–Associated Steatotic Liver Disease

The Impact of Ultra-Processed Foods on Dietary Patterns in Patients with Metabolic Dysfunction–Associated Steatotic Liver Disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Impact of Ultra-Processed Foods on Dietary Patterns in Patients with Metabolic Dysfunction–Associated Steatotic Liver Disease Claudineia Almeida de Souza, Raquel Rocha, Luiza Valois Vieira, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8894319/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : Ultra-processed foods (UPFs) are industrial formulations characterized by a high processing with the addition of food additives. Consumption of UPFs has been associated with adverse metabolic outcomes, including metabolic dysfunction-associated steatotic liver disease (MASLD). Lifestyle changes, including weight loss combined with caloric restrictions are central therapeutic strategies for metabolic control, qualitative dietary modifications may be crucial for the management of MASLD. Objectives : to determine the prevalence of UPFs consumption among patients with MASLD in outpatient follow-up and to assess its contribution to energy intake. Patients and Methods : This cross-sectional study included patients diagnosed with MASLD, who were followed at a hepatology outpatient clinic. Sociodemographic, clinical, and anthropometric data were collected. Dietary intake was assessed using three 24-hour dietary recalls and classified according to NOVA system to quantify the contribution of UPFs to total caloric and nutrient intake. Results : Ninety-seven patients with MASLD were evaluated, women (78.4%), with a high frequency of obesity (60.8%), type 2 diabetes (52.6%), and systemic arterial hypertension (SAH) (56.7%). UPFs consumption ranged from 0.0% to 41.0% of total caloric intake. Higher UPF consumption was associated with lack of paid employment, whereas lower UPFs consumption was associated with the presence of type 2 diabetes (p < 0.05). Carbohydrates, total fats, and proteins derived from UPFs showed a strong positive correlation with caloric intake, with carbohydrates representing the main energy source. Conclusions : Consumption of UPFs was relevant in this sample of patients with MASLD, with energy intake derived from carbohydrates and total fats. Gastroenterology & Hepatology steatotic liver disease MASLD food consumption ultra-processed foods Figures Figure 1 INTRODUCTION Ultra-processed foods (UPFs) are industrial formulations produced from substances derived from whole foods that cannot be replicated in home kitchens. Their production process involves the fractionation of foods into components such as sugars, oils and fats, proteins, starch, and dietary fiber, which may undergo chemical modifications. These components are recombined using advanced industrial techniques and food additives such as colorings, flavorings, and emulsifiers, aiming to confer specific sensory characteristics and promote greater palatability, often resulting in hyperpalatable products. Final processing involves packaging in sophisticated containers, usually made of synthetic materials. These characteristics distinguish UPFs from other processed foods. [1]. Driven by convenience, long shelf life, affordability, and high palatability, UPFs consumption has increased worldwide. In high-income countries such as the United States, Canada, and the United Kingdom, UPFs account for more than half of total daily energy intake [2–4]. Similar trends have been observed in middle-income countries, including Brazil, Mexico, and Chile, where UPFs increasingly contribute to dietary patterns [5–7]. The consumption of UPFs has been associated with adverse health outcomes and, more recently, implicated in the pathogenesis of metabolic dysfunction-associated steatotic liver disease (MASLD) [8]. MASLD is a condition characterized by the presence of hepatic steatosis associated with at least one cardiometabolic risk factor, in the absence of secondary causes of hepatic lipid accumulation [9]. MASLD represents a growing public health challenge, being the leading cause of chronic liver disease worldwide [10]. Caloric deficit-induced weight loss is the main therapeutic intervention recommended for patients with MASLD [11]. The aim of this study was to evaluate the prevalence of UPFs consumption among patients with MASLD in outpatient follow-up and its contribution to energy intake. PATIENTS AND METHODS STUDY DESIGN AND POPULATION This cross-sectional study was conducted at a specialized outpatient clinic for MASLD between July 2021 and April 2025. Participation was voluntary, and all patients provided informed consent. The protocol was reviewed and approved by the Ethics Committee. Patients of both sexes, aged ≥ 18 years, with a diagnosis of MASLD were eligible. MASLD was defined by the presence of hepatic steatosis identified by imaging or histology methods, absence of other risk factors for steatosis and at least one cardiometabolic risk criterion [9]. Exclusion criteria included a diagnosis of autoimmune diseases, other chronic liver diseases (including viral hepatitis, hemochromatosis, or Wilson’s disease), hypothyroidism, pregnancy or lactation, a history of cancer with completion of chemotherapy less than five years prior to enrollment, or any physical condition that could compromise anthropometric measurements. CLINICAL EVALUATION A semi-structured questionnaire was used to collect demographic, clinical, and nutritional data. All patients underwent upper abdominal ultrasound to assess hepatic steatosis. The exams were performed at a specialized diagnostic imaging clinic by a single experienced radiologist using a Xario 100 system (Canon Medical Systems®; Canon Medical Systems do Brasil Ltda., Barueri, Brazil). Hepatic steatosis was classified into mild (grade I), moderate (grade II), and severe (grade III) degrees [12]. ASSESSMENT OF FIBROSIS The Fibrosis Index-4 (FIB-4) was used to assess the presence or absence of advanced fibrosis. The absence of advanced fibrosis was considered when FIB-4 < 1.45; indeterminate fibrosis as FIB-4 between 1.45 and 3.24; and advanced fibrosis as FIB-4 ≥ 3.25 [13,14]. DIETARY ASSESSMENT Dietary intake was assessed using three 24-hour dietary recalls (24hR) per patient: two conducted on weekdays, with a 15-day interval between them, and a third recall conducted a weekend day after a three-month interval. The five steps recommended by the multiple weighing method [15] were adopted to reduce recall bias associated with the 24hR, and a photo album was used to facilitate the determination of portion sizes. Household measures of each food or preparation were converted into grams (g) or milliliters (mL). All culinary preparations were standardized, and the ingredients were quantified in g or mL [16,17]. Nutritional composition was calculated using the DietBox software (online version) with the Brazilian Food Composition Table (TACO) [18]. When food items were not available in TACO, additional food composition databases [19,20] and food labels were consulted. This procedure estimated of a total energy intake as well as macronutrient and micronutrient contents for reported foods, enabling both overall and individual dietary intake analyses. A qualitative assessment of the consumption of each ingested food was conducted, classifying them according to their degree of processing. Four food groups were created, according to the NOVA classification [1]. The contribution of the UPFs group to the daily consumption of calories, carbohydrates, fats, dietary fiber, sugars, sodium, calcium and iron of each patient was evaluated. Based on the 24-hour recall, habitual consumption was estimated using the Multiple Source Method (version 1.0.1, 2011), a free online software that estimates habitual consumption from at least two dietary surveys. Subsequently, nutrient consumption was adjusted for energy using the residual adjustment method [21], in which the final value obtained corresponds to nutrient consumption independent of energy, and this value was used for statistical analysis. From these data, the contribution of each nutrient to the consumption of ultra-processed foods was quantified, both in grams and as a percentage. ANTHROPOMETRIC ASSESSMENT Weight and height were measured using a digital platform scale with an attached stadiometer [22]. For the elderly, height was estimated by measuring knee height and calculating it [23]. Weight and height data were used to determine body mass index (BMI) according to reference values for adults [24] and the elderly [25]. Waist circumference (WC) was measured at the midpoint between the iliac crest and the edge of the last rib and classified according to the World Health Organization (WHO) cut-off points [26]. STATISTICAL ANALYSIS The data were tabulated and analyzed using the Statistical Package for the Social Sciences (SPSS) software, version 20.0. The distribution of continuous variables was assessed using the Kolmogorov–Smirnov test. As the variables did not follow a normal distribution, they were described using the median and interquartile range (IQR). Categorical variables were presented in absolute and relative frequencies. Comparisons between groups were conducted according to the nature of the variables. To assess the association between categories of UPFs consumption and clinical or sociodemographic characteristics, Pearson's chi-square test was used. Given the study's sample size, the magnitude of the associations was assessed using Cramér's V as an effect size measure. When significance was identified, the adjusted standardized residuals, with Bonferroni correction, were examined to identify which cells contributed to the overall result. The contribution of energy-adjusted nutrients to caloric intake from UPFs was assessed using Spearman's correlation, considering the residual caloric value of UPFs as the dependent variable. To identify the nutrients with the greatest influence on the energy consumption of UPFs, multiple linear regression was performed using the logarithmic transformation of the dependent variable (calories from UPFs). The significance level adopted was p < 0.05. RESULTS PATIENTS AND UPFs-TO-TOTAL ENERGY INTAKE The study population consisted of 97 patients with MASLD, with a mean age of 54.3 years (± 11.7), the majority being adults (60.8%), female (78.4%), without professional occupation outside the home (52.1%), with income up to two minimum wages (80.9%) and residing in the capital city (74.0%). They presented a clinical diagnosis of type 2 diabetes mellitus (T2DM) (52.6%), systemic arterial hypertension (SAH) (56.7%) and obesity (60.8%). The UPF-to-to-total energy intake (TEI) ranged from 0.0% to 41.0%, with 25.0% of patients consuming up to 12.6% of TEI from UPFs (P25), while 75.0% consumed up to 25.0% of TEI from UPFs (P75). A significant association was observed between occupational status and the percentiles of caloric intake obtained from UPFs (p = 0.003; Cramer's V = 0.35; moderate effect). Post-hoc analyses with Bonferroni correction (α’ = 0.0167) revealed a significant difference between the extreme percentiles (P25 vs P75: p = 0.001) and between the low and middle percentiles (P25 vs P25 - P75: p = 0.015), showing that women who work outside the home tend to consume fewer UPFs, while those who do not work outside the home have the highest consumption. Patients with DM2 showed a significantly different distribution of UPFs consumption percentiles (p = 0.008; Cramer's V = 0.32; moderate effect). In post-hoc analyses with Bonferroni correction (α' = 0.0167), patients with DM2 showed a lower prevalence in the highest percentile of UPFs consumption when compared to non- T2DM patients (P25-P75 vs P75: p = 0.004; P25 vs P75: p = 0.009), indicating lower consumption of UPFs by patients with T2DM. The remaining sociodemographic and clinical characteristics did not show significant associations with UPFs consumption percentiles, with consistently low effect sizes (Cramér's V between 0.05 and 0.19), indicating that, if there were real differences between the groups, they would be of small clinical magnitude (TABLE 1) NUTRIENTS FROM UPFs Added sugar, macronutrients, dietary fiber, sodium, calcium, and iron showed positive and statistically significant correlations with the caloric value of UPFs. Carbohydrates (r = 0.720; p < 0.001), proteins (r = 0.677; p < 0.001), total fats (r = 0.654; p < 0.001), and sodium (r = 0.613; p < 0.001) showed strong correlations. (TABLE 2) In the multiple regression analysis, among the nutrients that showed a strong correlation, carbohydrates had the greatest influence on caloric value (β = 0.416; p < 0.001), followed by total fats (β = 0.307; p < 0.001) and proteins (β = 0.223; p = 0.023). Residual sodium did not show a significant association (p = 0.558). (TABLE 3) UPFs FOODS Of the 103 UPFs recorded in the diet of patients with MASLD, 13 were consumed most frequently, including whole wheat bread, tomato sauce, margarine, Calabrian sausage, and cream cracker-type savory biscuits; consumption exceeded 30.0%. (FIGURE 1 ) Among these five UPFs with intake above 30.0%, caloric intake from whole wheat bread was higher among those with elevated WC (p = 0.045), and caloric intake from margarine was higher among those with elevated neck circumference (p = 0.041). No significant differences were observed in caloric intake of these foods according to skeletal muscle mass or body fat percentage. DISCUSSION The sample of patients with MASLD was composed of adult women, without professional occupation outside the home, residing in the capital city, with a clinical diagnosis of T2DM and SAH, and those with T2DM presented lower consumption of UPFs. It was observed that the consumption of UPFs represented up to 41.0% of the total energy intake and that carbohydrates, total fats, and proteins were strongly correlated with the energy intake of foods that are sources of these nutrients, highlighting the energy-dense nature of ultra-processed formulations. Of patients with MASLD, 75.0% consumed up to 25.0% of their total energy intake in the form of UPFs, a value higher than the national average described by the Family Budget Survey (POF 2017–2018), which indicates an average participation of 20% of UPFs in the total energy of the Brazilian population [27]. However, this consumption remains within the expected range for the regional context, since estimates from the same survey indicate that the state of Bahia has an average of 19.4%, while the capital city reaches approximately 25.7% of total energy intake from UPFs [28]. These results are consistent with studies conducted with the adult population residing in Brazilian capitals, showing a high participation of UPFs in the diet, associated with the greater availability and accessibility of these products, as well as characteristics of the urban food environment [29, 30]. Patients diagnosed with T2DM who consume less UPFs reflect dietary changes resulting from prior nutritional guidance, such as adopting foods without added sugar. These findings are similar to the results observed by Mahajan et al. (2025), in which patients with T2DM adopted dietary behaviors considered more appropriate, such as regularly eating breakfast, preferring meals prepared and consumed at home, and less frequently eating out [31]. It is observed that sociodemographic characteristics and occupational status also influence the consumption of UPFs. Although women without professional occupations outside the home may have more time to prepare meals, this condition may not be decisive for dietary patterns [32]. National evidence shows that factors such as education, income, and food insecurity have a more consistent association with diet quality and UPFs consumption, often overriding the effect of extra-domestic occupation [29, 30]. The analysis of UPFs consumption should not be limited to the percentage of total energy intake; it is essential to consider the nutritional quality of these foods. In general, UPFs have high energy density, high levels of simple carbohydrates, saturated and/or trans fats, and food additives, with low fiber, vitamin, and mineral content [1]. These findings add to a growing body of evidence associating greater exposure to UPFs with an increased risk of metabolic disorders, including obesity, insulin resistance, and greater severity of MASLD [33–34]. This relationship has been demonstrated due to the influence of food additives widely used in UPFs, such as emulsifiers and artificial sweeteners, on the gut microbiota, reducing bacterial diversity and causing functional alterations in microbial metabolism [35]. These food additives can compromise the integrity of the intestinal barrier, increase permeability and favoring the translocation of lipopolysaccharides (LPS), with consequent activation of a low-grade inflammatory process [36]. This inflammatory environment has been associated with activation of the gut-liver axis, contributing to insulin resistance, hepatic lipid accumulation, and progression of MASLD [37]. Thus, chronic exposure to food additives, regardless of total energy intake, may be a plausible mechanism linking UPFs consumption and adverse hepatic outcomes. Another factor to consider regarding the consumption of UPFs is the classification of certain foods as ultra-processed, which can vary according to regulatory criteria and national contexts. Whole wheat bread, a food frequently consumed as a healthier alternative, presents, in Brazil, degrees of processing and presence of food additives that characterize it as a UPFs [1,38]. The definition of the term "whole grain" is regulated in Brazil by Collegiate Board Resolution (RDC) No. 712/2022 of the National Health Surveillance Agency (ANVISA), which establishes minimum composition criteria, requiring that at least 30% of the ingredients be whole grain, with a quantity greater than that of refined ingredients [39]. However, this regulation does not explicitly consider the degree of food processing or the use of food additives as classification criteria, which allows products labeled as whole grain to present formulations typical of UPFs. Studies analyzing the composition of UPFs in different countries demonstrate that the use of food additives is a central characteristic of these products, regardless of their nutritional profile or the "healthy" claims on their labels. Data from the United States population indicate that most UPFs contain multiple additives, such as emulsifiers, stabilizers, and preservatives, frequently used to improve texture, palatability, and shelf life [40]. The way UPFs are presented in dietary guidelines varies between countries, reflecting different regulatory and conceptual approaches to the role of industrial processing in food. While some guidelines predominantly emphasize the nutritional profile of foods, others, such as the Brazilian Dietary Guidelines, incorporate the degree of processing as a central criterion for dietary recommendations, which contributes to discrepancies in the classification and encouragement of consumption of products such as whole-wheat bread across different national contexts [41]. Margarine is frequently consumed as a “healthy” substitute for butter because it contains vegetable oils and has historically been promoted as a cardioprotective alternative, reinforced by marketing strategies [42,43]. However, margarines are classified as UPFs, regardless of the fatty acid profile declared on the labels, due to the presence of fats that undergo hydrogenation or interesterification processes, as well as the addition of emulsifiers, flavorings, and colorings [1]. Furthermore, the lower cost makes margarine more accessible than butter, especially in contexts of socioeconomic vulnerability, favoring habitual consumption and contributing to greater exposure to UPFs. Thus, although the population studied is predominantly lower middle class and the habit of preparing meals at home is encouraged, continuous exposure to UPFs reflects structural determinants that transcend the sphere of individual behavior. In contexts of socioeconomic constraints or food deserts, the convenience and low cost of UPFs often outweigh individuals' motivation to maintain a healthy diet. The global expansion of UPFs has promoted the replacement of dietary patterns based on whole or minimally processed foods, compromising diet quality and increasing the risk of multiple adverse clinical outcomes, including cardiometabolic and liver diseases [44]. This scenario illustrates that, even with nutritional counseling, social vulnerability, the availability of fresh foods, and market pressure can hinder the adoption of ideal food choices. Given the insufficiency of public policies to address the systemic factors that shape the availability, convenience, and aggressive promotion of these products, this challenge becomes even more evident, especially among vulnerable populations, where healthy alternatives tend to be less accessible and more expensive [45]. In this context, isolated clinical interventions are insufficient, underscoring the need to integrate care strategies with robust public policies that expand access to and acceptance of fresh and minimally processed foods, and to directly address commercial and structural determinants that sustain dependence on low-cost, industrialized products [46]. Therefore, encouraging the traditional Brazilian dietary pattern, combined with maintaining domestic culinary practices, should continue, as the presence of UPFs in this context can mitigate some of the adverse metabolic effects associated with high UPFs intake, reinforcing the importance of preserving and promoting regional culinary practices as a central nutritional strategy for addressing MASLD [47]. Despite the relevance of this study, the first to specifically evaluate UPFs consumption in patients with MASLD in the state of Bahia, some limitations should be considered. The cross-sectional design prevents establishing causal relationships between UPFs intake and clinical outcomes; the sample size, although adequate for exploring dietary patterns in a specialized service, may have reduced the statistical power to detect more subtle associations, especially after covariate adjustment. Furthermore, dietary assessment is subject to biases inherent in recall and underreporting, particularly relevant when analyzing UPFs, whose classification depends on the accuracy of reporting and the rigorous application of the NOVA system. These limitations reinforce the importance of prospective studies with larger sample sizes to deepen the understanding of the effects of UPFs on MASLD progression. CONCLUSION The consumption of ultra-processed foods was high among patients with MASLD in this simple. Caloric intake is strongly driven by carbohydrates and total fat. Moreover, the lower consumption observed among individuals T2DM along with distinct consumption patterns of whole-wheat bread and margarine according to anthropometric measurements, reinforce the complexity of dietary behavior in this population. These findings underscore the clinical relevance of implementing nutritional care strategies to reduce UPFs consumption, such as home-cooking practices, as well as the importance of public policies combined with nutritional interventions. Despite the limitations inherent to its cross-sectional design, this pioneering study conducted in Brazil expands current knowledge on the role of UPFs in MASLD and provides a robust foundation for future longitudinal studies and targeted nutritional interventions. Declarations ETHICAL APPROVAL The protocol for this study was submitted to and approved by the Ethics Committee of the School of Nutrition at the Federal University of Bahia, Salvador, Brazil, under opinion number 7.598.703. COMPETING INTERESTS The authors have no competing interests FUNDING Open access funding provided by Federal University of Bahia AUTHOR CONTRIBUTIONS CAS and RR planned the research and wrote the first draft; CAS, LVV, and NSA collected the data; MS performed the ultrasound examinations; CD guided the statistical analyses; HPC provided technical review and final correction. ACKNOWLEDGEMENTS The authors gratefully acknowledge the commitment and dedication of all the students who contributed to this work. References Monteiro CA, Cannon G, Levy RB, Moubarac JC, Louzada ML, Rauber F, et al. Ultra-processed foods: what they are and how to identify them. Public Health Nutr. 2019; https://doi.org/10.1017/S1368980018003762 . Moubarac JC, Batal M, Louzada ML, Martinez Steele E, Monteiro CA. Consumption of ultra-processed foods predicts diet quality in Canada. Appetite. 2017; https://doi.org/10.1016/j.appet.2016.11.006 . Baraldi LG, Martinez Steele E, Canella DS, Monteiro CA. 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Int J Health Policy Manag. 2022; https://doi.org/10.34172/ijhpm.2021.164 . de Souza RJ, Mente A, Maroleanu A, Cozma AI, Ha V, Kishibe T, et al. Intake of saturated and trans unsaturated fatty acids and risk of all-cause mortality, cardiovascular disease, and type 2 diabetes: systematic review and meta-analysis of observational studies. BMJ. 2015;351:h3978. https://doi.org/10.1136/bmj.h3978 . Weber C, Harnack L, Johnson A, Jasthi B, Pettit J, Stevenson J. Nutrient comparisons of margarine/margarine-like products and butter blend products and butter in the US marketplace in 2020, post FDA ban on partially hydrogenated oils. Public Health Nutr. 2021; https://doi.org/10.1017/S1368980021004511 . Monteiro CA, Louzada MLC, Martinez Steele E, Cannon G, Moubarac JC, Levy RB, et al. Ultra-processed foods and human health: the main thesis and the evidence. Lancet. 2025; Published online Nov 18. https://doi.org/10.1016/S0140-6736(25)01565-X . Scrinis G, Popkin BM, Corvalan C, et al. Policies to halt and reverse the rise in ultra-processed food production, marketing, and consumption. Lancet. 2025; doi: 10.1016/S0140-6736(25)01566-1 . Baker P, Slater S, White M, Machado P, Lacy-Nichols J, Raubenheimer D, et al. Towards unified global action on ultra-processed foods: understanding commercial determinants, countering corporate power, and mobilising a public health response. Lancet. 2025; https://doi.org/10.1016/S0140-6736(25)01567-3 . Salarini JS, Barroso LN, Freitas JV, Leite NC, de Paula TP, Padilha PC, et al. The Brazilian traditional dietary pattern was associated with a lower risk of advanced steatosis in patients with metabolic dysfunction-associated steatotic liver disease. Nutr Res. 2025; https://doi.org/10.1016/j.nutres.2025.04.012 . Tables TABLE 1: Sociodemographic and clinical characteristics of patients with metabolic dysfunction-associated steatotic liver disease, assessed according to the percentage of total energy value derived from ultra-processed foods. Variables Total 97 N (%) % VET derived from AUPs p-value Cramer's V 25,0% 24 N (%) Adults 59 (60.8) 14 (23.7) 31 (52.5) 14 (23.7) 0.884 0.051 Female 76 (78.4) 17 (22.4) 39 (51.3) 20 (26.3) 0.550 0.111 No occupation 50 (52.1) 6 (12.0) 27 (54.0) 17 (34.0) 0.003* 0.348 Resides in the capital 71 (74.0) 18 (25.4) 35 (49.3) 18 (25.4) 0.820 0.064 T2DM 51 (52.6) 15 (29.4) 30 (58.8) 6 (11.8) 0.008* 0.317 SAH 55 (56.7) 12 (21.8) 31 (56.4) 12 (21.8) 0.419 0.134 Dyslipidemia 36 (37.1) 10 (27.8) 17 (47.2) 9 (25.0) 0.845 0.059 Absence of fibrosis - FIB4 78 (96.3) 20 (25.6) 39 (50.0) 19 (24.4) NA 0.068 normal AST 73 (85.8) 18 (24.7) 36 (49.3) 19 (26.0) NA 0.167 normal ALT 66 (78,6) 20 (30,3) 31 (47,0) 15 (22,7) NA 0,104 Steatosis Mild 38 (41.7) 10 (26.3) 18 (47.4) 10 (26.3) NA 0.186 Moderate 44 (48.3) 10 (22.7) 23 (52.3) 11 (25.0) Severe 9 (9.9) 3 (33.3) 5 (55.6) 1 (11.1) BMI Eutrophic 16 (16.5) 1 (6.3) 10 (62.5) 5 (31.3) NA 0.177 Overweight 22 (22.7) 9 (40.9) 9 (40.9) 4 (18.2) Obesy 59 (60.8) 14 (23.7) 30 (50.8) 15 (25.4) DM2: Type 2 diabetes mellitus; HAS: Systemic arterial hypertension; FIB4: Fibrosis-4 score; AST: Aspartate aminotransferase; ALT: Alanine aminotransferase; BMI: Body mass index; TEV: Total energy value; AUPs: Ultra-processed foods; NA: Not applicable *Pearson's chi-square test. Cramér's V presented as a measure of effect size (interpretation: 0.50 strong) TABLE 2: Correlation between residual added sugar, residual nutrients, and caloric intake from ultra-processed foods in patients with metabolic dysfunction-associated steatotic liver disease. Residual nutrient (UPF) r-Spearman p-value Carbohydrates (g) Proteins (g) Total fats (g) Saturated fat (g) Monounsaturated fat (g) Polyunsaturated fat (g) Added sugar (g) Dietary fiber (g) Sodium (mg) Calcium (mg) Iron (mg) 0.720 0.677 0.654 0.566 0.433 0.429 0.500 0.430 0.613 0.447 0.549 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 a. Spearman's correlation coefficient TABLE 3: Influence of residual nutrients on the caloric value of ultra-processed foods among patients with metabolic dysfunction-associated steatotic liver disease. Residual nutrient (UPF) β (standardized) B (CI95%) p-value Carbohydrates (g) Protein (g) Total fat (g) Sodium (mg) 0.416 0.223 0.307 0.053 0.004 (0.002 – 0.006) 0.015 (0.003 – 0.027) 0.012 (0.006 – 0.018) - <0.001 0.023 <0.001 0.558 Adjusted R² = 0.686; p<0.001 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8894319","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":592274341,"identity":"6f4d4006-6a65-4f05-8d69-425d20c8bca7","order_by":0,"name":"Claudineia Almeida de Souza","email":"","orcid":"https://orcid.org/0000-0002-1172-2944","institution":"Federal University of Bahia","correspondingAuthor":false,"prefix":"","firstName":"Claudineia","middleName":"Almeida","lastName":"de Souza","suffix":""},{"id":592274342,"identity":"587bbc16-b3c7-4b9e-8f33-e74c75c7e3f1","order_by":1,"name":"Raquel Rocha","email":"","orcid":"https://orcid.org/0000-0002-2687-2080","institution":"Federal University of Bahia","correspondingAuthor":false,"prefix":"","firstName":"Raquel","middleName":"","lastName":"Rocha","suffix":""},{"id":592274343,"identity":"5c43acbe-105b-43e6-ac7a-ba47ec40de9f","order_by":2,"name":"Luiza Valois Vieira","email":"","orcid":"https://orcid.org/0000-0003-3757-2881","institution":"Federal University of Bahia","correspondingAuthor":false,"prefix":"","firstName":"Luiza","middleName":"Valois","lastName":"Vieira","suffix":""},{"id":592274344,"identity":"7052d9d7-c137-45f5-89da-ed3a8a4de065","order_by":3,"name":"Naiade Silveira Almeida","email":"","orcid":"https://orcid.org/0000-0001-7193-3666","institution":"Federal University of Bahia","correspondingAuthor":false,"prefix":"","firstName":"Naiade","middleName":"Silveira","lastName":"Almeida","suffix":""},{"id":592274345,"identity":"87f38052-2452-4a42-a1f6-2411085efbad","order_by":4,"name":"Carla Daltro","email":"","orcid":"https://orcid.org/0000-0003-1115-688X","institution":"Federal University of Bahia","correspondingAuthor":false,"prefix":"","firstName":"Carla","middleName":"","lastName":"Daltro","suffix":""},{"id":592274346,"identity":"3c0c6520-3189-4ce3-9c6b-7b28e262d801","order_by":5,"name":"Manoel Sarno","email":"","orcid":"https://orcid.org/0000-0002-2312-0932","institution":"Caliper Clinic and School of Imaging","correspondingAuthor":false,"prefix":"","firstName":"Manoel","middleName":"","lastName":"Sarno","suffix":""},{"id":592274347,"identity":"3267fd83-b95a-4997-9aca-122464b9347d","order_by":6,"name":"Helma Pinchemel Cotrim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYBACAwbmBgiLmYHxAZDi4SOshRGsRQKohdkApIWNeC0MDGwggoGgFnP2xtYNP2ps6szbudMqv+bYybAxMD98dAOPFsueg203e46lScgc5t12W3ZbMtBhbMbGOfgcdiOx7QZvw2EJCWagFsltzEAtPGzSeLXcf9h28y9US7HktnoitNxgbLsNs4Xx47bDRGg5k9h2W+ZYmuQMZt7N0ozbjvOwMRPyy/HDx26+qbHhl+A/u/Hjz23V9vzszQ8f49OCAph5wCSxykGA8QcpqkfBKBgFo2DEAAChB0UmoJNdGQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-7698-6919","institution":"Federal University of Bahia","correspondingAuthor":true,"prefix":"","firstName":"Helma","middleName":"Pinchemel","lastName":"Cotrim","suffix":""}],"badges":[],"createdAt":"2026-02-16 15:21:44","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8894319/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8894319/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102909926,"identity":"21c51ff0-8365-4706-b812-e56c3170a239","added_by":"auto","created_at":"2026-02-18 09:57:20","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":59483,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency of consumption of ultra-processed foods among patients with metabolic dysfunction-associated steatotic liver disease\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8894319/v1/4b25ef5522e95c9d496e96ee.jpg"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eThe Impact of Ultra-Processed Foods on Dietary Patterns in Patients with Metabolic Dysfunction–Associated Steatotic Liver Disease\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eUltra-processed foods (UPFs) are industrial formulations produced from substances derived from whole foods that cannot be replicated in home kitchens. Their production process involves the fractionation of foods into components such as sugars, oils and fats, proteins, starch, and dietary fiber, which may undergo chemical modifications. These components are recombined using advanced industrial techniques and food additives such as colorings, flavorings, and emulsifiers, aiming to confer specific sensory characteristics and promote greater palatability, often resulting in hyperpalatable products. Final processing involves packaging in sophisticated containers, usually made of synthetic materials. These characteristics distinguish UPFs from other processed foods. [1].\u003c/p\u003e \u003cp\u003eDriven by convenience, long shelf life, affordability, and high palatability, UPFs consumption has increased worldwide. In high-income countries such as the United States, Canada, and the United Kingdom, UPFs account for more than half of total daily energy intake [2\u0026ndash;4]. Similar trends have been observed in middle-income countries, including Brazil, Mexico, and Chile, where UPFs increasingly contribute to dietary patterns [5\u0026ndash;7].\u003c/p\u003e \u003cp\u003eThe consumption of UPFs has been associated with adverse health outcomes and, more recently, implicated in the pathogenesis of metabolic dysfunction-associated steatotic liver disease (MASLD) [8]. MASLD is a condition characterized by the presence of hepatic steatosis associated with at least one cardiometabolic risk factor, in the absence of secondary causes of hepatic lipid accumulation [9]. MASLD represents a growing public health challenge, being the leading cause of chronic liver disease worldwide [10]. Caloric deficit-induced weight loss is the main therapeutic intervention recommended for patients with MASLD [11]. The aim of this study was to evaluate the prevalence of UPFs consumption among patients with MASLD in outpatient follow-up and its contribution to energy intake.\u003c/p\u003e"},{"header":"PATIENTS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSTUDY DESIGN AND POPULATION\u003c/h2\u003e \u003cp\u003eThis cross-sectional study was conducted at a specialized outpatient clinic for MASLD between July 2021 and April 2025. Participation was voluntary, and all patients provided informed consent. The protocol was reviewed and approved by the Ethics Committee. Patients of both sexes, aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years, with a diagnosis of MASLD were eligible. MASLD was defined by the presence of hepatic steatosis identified by imaging or histology methods, absence of other risk factors for steatosis and at least one cardiometabolic risk criterion [9].\u003c/p\u003e \u003cp\u003eExclusion criteria included a diagnosis of autoimmune diseases, other chronic liver diseases (including viral hepatitis, hemochromatosis, or Wilson\u0026rsquo;s disease), hypothyroidism, pregnancy or lactation, a history of cancer with completion of chemotherapy less than five years prior to enrollment, or any physical condition that could compromise anthropometric measurements.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCLINICAL EVALUATION\u003c/h3\u003e\n\u003cp\u003eA semi-structured questionnaire was used to collect demographic, clinical, and nutritional data. All patients underwent upper abdominal ultrasound to assess hepatic steatosis. The exams were performed at a specialized diagnostic imaging clinic by a single experienced radiologist using a Xario 100 system (Canon Medical Systems\u0026reg;; Canon Medical Systems do Brasil Ltda., Barueri, Brazil). Hepatic steatosis was classified into mild (grade I), moderate (grade II), and severe (grade III) degrees [12].\u003c/p\u003e\n\u003ch3\u003eASSESSMENT OF FIBROSIS\u003c/h3\u003e\n\u003cp\u003eThe Fibrosis Index-4 (FIB-4) was used to assess the presence or absence of advanced fibrosis. The absence of advanced fibrosis was considered when FIB-4\u0026thinsp;\u0026lt;\u0026thinsp;1.45; indeterminate fibrosis as FIB-4 between 1.45 and 3.24; and advanced fibrosis as FIB-4\u0026thinsp;\u0026ge;\u0026thinsp;3.25 [13,14].\u003c/p\u003e\n\u003ch3\u003eDIETARY ASSESSMENT\u003c/h3\u003e\n\u003cp\u003eDietary intake was assessed using three 24-hour dietary recalls (24hR) per patient: two conducted on weekdays, with a 15-day interval between them, and a third recall conducted a weekend day after a three-month interval. The five steps recommended by the multiple weighing method [15] were adopted to reduce recall bias associated with the 24hR, and a photo album was used to facilitate the determination of portion sizes. Household measures of each food or preparation were converted into grams (g) or milliliters (mL). All culinary preparations were standardized, and the ingredients were quantified in g or mL [16,17]. Nutritional composition was calculated using the DietBox software (online version) with the Brazilian Food Composition Table (TACO) [18]. When food items were not available in TACO, additional food composition databases [19,20] and food labels were consulted. This procedure estimated of a total energy intake as well as macronutrient and micronutrient contents for reported foods, enabling both overall and individual dietary intake analyses.\u003c/p\u003e \u003cp\u003e A qualitative assessment of the consumption of each ingested food was conducted, classifying them according to their degree of processing. Four food groups were created, according to the NOVA classification [1]. The contribution of the UPFs group to the daily consumption of calories, carbohydrates, fats, dietary fiber, sugars, sodium, calcium and iron of each patient was evaluated.\u003c/p\u003e \u003cp\u003eBased on the 24-hour recall, habitual consumption was estimated using the Multiple Source Method (version 1.0.1, 2011), a free online software that estimates habitual consumption from at least two dietary surveys. Subsequently, nutrient consumption was adjusted for energy using the residual adjustment method [21], in which the final value obtained corresponds to nutrient consumption independent of energy, and this value was used for statistical analysis. From these data, the contribution of each nutrient to the consumption of ultra-processed foods was quantified, both in grams and as a percentage.\u003c/p\u003e\n\u003ch3\u003eANTHROPOMETRIC ASSESSMENT\u003c/h3\u003e\n\u003cp\u003eWeight and height were measured using a digital platform scale with an attached stadiometer [22]. For the elderly, height was estimated by measuring knee height and calculating it [23]. Weight and height data were used to determine body mass index (BMI) according to reference values for adults [24] and the elderly [25]. Waist circumference (WC) was measured at the midpoint between the iliac crest and the edge of the last rib and classified according to the World Health Organization (WHO) cut-off points [26].\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSTATISTICAL ANALYSIS\u003c/h2\u003e \u003cp\u003eThe data were tabulated and analyzed using the Statistical Package for the Social Sciences (SPSS) software, version 20.0. The distribution of continuous variables was assessed using the Kolmogorov\u0026ndash;Smirnov test. As the variables did not follow a normal distribution, they were described using the median and interquartile range (IQR). Categorical variables were presented in absolute and relative frequencies. Comparisons between groups were conducted according to the nature of the variables. To assess the association between categories of UPFs consumption and clinical or sociodemographic characteristics, Pearson's chi-square test was used. Given the study's sample size, the magnitude of the associations was assessed using Cram\u0026eacute;r's V as an effect size measure. When significance was identified, the adjusted standardized residuals, with Bonferroni correction, were examined to identify which cells contributed to the overall result. The contribution of energy-adjusted nutrients to caloric intake from UPFs was assessed using Spearman's correlation, considering the residual caloric value of UPFs as the dependent variable. To identify the nutrients with the greatest influence on the energy consumption of UPFs, multiple linear regression was performed using the logarithmic transformation of the dependent variable (calories from UPFs). The significance level adopted was p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003ePATIENTS AND UPFs-TO-TOTAL ENERGY INTAKE\u003c/p\u003e \u003cp\u003eThe study population consisted of 97 patients with MASLD, with a mean age of 54.3 years (\u0026plusmn;\u0026thinsp;11.7), the majority being adults (60.8%), female (78.4%), without professional occupation outside the home (52.1%), with income up to two minimum wages (80.9%) and residing in the capital city (74.0%). They presented a clinical diagnosis of type 2 diabetes mellitus (T2DM) (52.6%), systemic arterial hypertension (SAH) (56.7%) and obesity (60.8%).\u003c/p\u003e \u003cp\u003eThe UPF-to-to-total energy intake (TEI) ranged from 0.0% to 41.0%, with 25.0% of patients consuming up to 12.6% of TEI from UPFs (P25), while 75.0% consumed up to 25.0% of TEI from UPFs (P75). A significant association was observed between occupational status and the percentiles of caloric intake obtained from UPFs (p\u0026thinsp;=\u0026thinsp;0.003; Cramer's V\u0026thinsp;=\u0026thinsp;0.35; moderate effect). Post-hoc analyses with Bonferroni correction (α\u0026rsquo; = 0.0167) revealed a significant difference between the extreme percentiles (P25 vs P75: p\u0026thinsp;=\u0026thinsp;0.001) and between the low and middle percentiles (P25 vs P25 - P75: p\u0026thinsp;=\u0026thinsp;0.015), showing that women who work outside the home tend to consume fewer UPFs, while those who do not work outside the home have the highest consumption.\u003c/p\u003e \u003cp\u003ePatients with DM2 showed a significantly different distribution of UPFs consumption percentiles (p\u0026thinsp;=\u0026thinsp;0.008; Cramer's V\u0026thinsp;=\u0026thinsp;0.32; moderate effect). In post-hoc analyses with Bonferroni correction (α' = 0.0167), patients with DM2 showed a lower prevalence in the highest percentile of UPFs consumption when compared to non- T2DM patients (P25-P75 vs P75: p\u0026thinsp;=\u0026thinsp;0.004; P25 vs P75: p\u0026thinsp;=\u0026thinsp;0.009), indicating lower consumption of UPFs by patients with T2DM.\u003c/p\u003e \u003cp\u003eThe remaining sociodemographic and clinical characteristics did not show significant associations with UPFs consumption percentiles, with consistently low effect sizes (Cram\u0026eacute;r's V between 0.05 and 0.19), indicating that, if there were real differences between the groups, they would be of small clinical magnitude (TABLE 1)\u003c/p\u003e \u003cp\u003eNUTRIENTS FROM UPFs\u003c/p\u003e \u003cp\u003eAdded sugar, macronutrients, dietary fiber, sodium, calcium, and iron showed positive and statistically significant correlations with the caloric value of UPFs. Carbohydrates (r\u0026thinsp;=\u0026thinsp;0.720; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), proteins (r\u0026thinsp;=\u0026thinsp;0.677; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), total fats (r\u0026thinsp;=\u0026thinsp;0.654; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and sodium (r\u0026thinsp;=\u0026thinsp;0.613; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) showed strong correlations. (TABLE 2)\u003c/p\u003e \u003cp\u003eIn the multiple regression analysis, among the nutrients that showed a strong correlation, carbohydrates had the greatest influence on caloric value (β\u0026thinsp;=\u0026thinsp;0.416; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), followed by total fats (β\u0026thinsp;=\u0026thinsp;0.307; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and proteins (β\u0026thinsp;=\u0026thinsp;0.223; p\u0026thinsp;=\u0026thinsp;0.023). Residual sodium did not show a significant association (p\u0026thinsp;=\u0026thinsp;0.558). (TABLE 3)\u003c/p\u003e \u003cp\u003eUPFs FOODS\u003c/p\u003e \u003cp\u003eOf the 103 UPFs recorded in the diet of patients with MASLD, 13 were consumed most frequently, including whole wheat bread, tomato sauce, margarine, Calabrian sausage, and cream cracker-type savory biscuits; consumption exceeded 30.0%. (FIGURE \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAmong these five UPFs with intake above 30.0%, caloric intake from whole wheat bread was higher among those with elevated WC (p\u0026thinsp;=\u0026thinsp;0.045), and caloric intake from margarine was higher among those with elevated neck circumference (p\u0026thinsp;=\u0026thinsp;0.041). No significant differences were observed in caloric intake of these foods according to skeletal muscle mass or body fat percentage.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe sample of patients with MASLD was composed of adult women, without professional occupation outside the home, residing in the capital city, with a clinical diagnosis of T2DM and SAH, and those with T2DM presented lower consumption of UPFs. It was observed that the consumption of UPFs represented up to 41.0% of the total energy intake and that carbohydrates, total fats, and proteins were strongly correlated with the energy intake of foods that are sources of these nutrients, highlighting the energy-dense nature of ultra-processed formulations.\u003c/p\u003e \u003cp\u003eOf patients with MASLD, 75.0% consumed up to 25.0% of their total energy intake in the form of UPFs, a value higher than the national average described by the Family Budget Survey (POF 2017\u0026ndash;2018), which indicates an average participation of 20% of UPFs in the total energy of the Brazilian population [27]. However, this consumption remains within the expected range for the regional context, since estimates from the same survey indicate that the state of Bahia has an average of 19.4%, while the capital city reaches approximately 25.7% of total energy intake from UPFs [28]. These results are consistent with studies conducted with the adult population residing in Brazilian capitals, showing a high participation of UPFs in the diet, associated with the greater availability and accessibility of these products, as well as characteristics of the urban food environment [29, 30].\u003c/p\u003e \u003cp\u003ePatients diagnosed with T2DM who consume less UPFs reflect dietary changes resulting from prior nutritional guidance, such as adopting foods without added sugar. These findings are similar to the results observed by Mahajan et al. (2025), in which patients with T2DM adopted dietary behaviors considered more appropriate, such as regularly eating breakfast, preferring meals prepared and consumed at home, and less frequently eating out [31].\u003c/p\u003e \u003cp\u003eIt is observed that sociodemographic characteristics and occupational status also influence the consumption of UPFs. Although women without professional occupations outside the home may have more time to prepare meals, this condition may not be decisive for dietary patterns [32]. National evidence shows that factors such as education, income, and food insecurity have a more consistent association with diet quality and UPFs consumption, often overriding the effect of extra-domestic occupation [29, 30].\u003c/p\u003e \u003cp\u003eThe analysis of UPFs consumption should not be limited to the percentage of total energy intake; it is essential to consider the nutritional quality of these foods. In general, UPFs have high energy density, high levels of simple carbohydrates, saturated and/or trans fats, and food additives, with low fiber, vitamin, and mineral content [1]. These findings add to a growing body of evidence associating greater exposure to UPFs with an increased risk of metabolic disorders, including obesity, insulin resistance, and greater severity of MASLD [33\u0026ndash;34].\u003c/p\u003e \u003cp\u003eThis relationship has been demonstrated due to the influence of food additives widely used in UPFs, such as emulsifiers and artificial sweeteners, on the gut microbiota, reducing bacterial diversity and causing functional alterations in microbial metabolism [35]. These food additives can compromise the integrity of the intestinal barrier, increase permeability and favoring the translocation of lipopolysaccharides (LPS), with consequent activation of a low-grade inflammatory process [36]. This inflammatory environment has been associated with activation of the gut-liver axis, contributing to insulin resistance, hepatic lipid accumulation, and progression of MASLD [37]. Thus, chronic exposure to food additives, regardless of total energy intake, may be a plausible mechanism linking UPFs consumption and adverse hepatic outcomes.\u003c/p\u003e \u003cp\u003e Another factor to consider regarding the consumption of UPFs is the classification of certain foods as ultra-processed, which can vary according to regulatory criteria and national contexts. Whole wheat bread, a food frequently consumed as a healthier alternative, presents, in Brazil, degrees of processing and presence of food additives that characterize it as a UPFs [1,38]. The definition of the term \"whole grain\" is regulated in Brazil by Collegiate Board Resolution (RDC) No. 712/2022 of the National Health Surveillance Agency (ANVISA), which establishes minimum composition criteria, requiring that at least 30% of the ingredients be whole grain, with a quantity greater than that of refined ingredients [39]. However, this regulation does not explicitly consider the degree of food processing or the use of food additives as classification criteria, which allows products labeled as whole grain to present formulations typical of UPFs.\u003c/p\u003e \u003cp\u003eStudies analyzing the composition of UPFs in different countries demonstrate that the use of food additives is a central characteristic of these products, regardless of their nutritional profile or the \"healthy\" claims on their labels. Data from the United States population indicate that most UPFs contain multiple additives, such as emulsifiers, stabilizers, and preservatives, frequently used to improve texture, palatability, and shelf life [40]. The way UPFs are presented in dietary guidelines varies between countries, reflecting different regulatory and conceptual approaches to the role of industrial processing in food. While some guidelines predominantly emphasize the nutritional profile of foods, others, such as the Brazilian Dietary Guidelines, incorporate the degree of processing as a central criterion for dietary recommendations, which contributes to discrepancies in the classification and encouragement of consumption of products such as whole-wheat bread across different national contexts [41].\u003c/p\u003e \u003cp\u003eMargarine is frequently consumed as a \u0026ldquo;healthy\u0026rdquo; substitute for butter because it contains vegetable oils and has historically been promoted as a cardioprotective alternative, reinforced by marketing strategies [42,43]. However, margarines are classified as UPFs, regardless of the fatty acid profile declared on the labels, due to the presence of fats that undergo hydrogenation or interesterification processes, as well as the addition of emulsifiers, flavorings, and colorings [1]. Furthermore, the lower cost makes margarine more accessible than butter, especially in contexts of socioeconomic vulnerability, favoring habitual consumption and contributing to greater exposure to UPFs.\u003c/p\u003e \u003cp\u003eThus, although the population studied is predominantly lower middle class and the habit of preparing meals at home is encouraged, continuous exposure to UPFs reflects structural determinants that transcend the sphere of individual behavior. In contexts of socioeconomic constraints or food deserts, the convenience and low cost of UPFs often outweigh individuals' motivation to maintain a healthy diet. The global expansion of UPFs has promoted the replacement of dietary patterns based on whole or minimally processed foods, compromising diet quality and increasing the risk of multiple adverse clinical outcomes, including cardiometabolic and liver diseases [44].\u003c/p\u003e \u003cp\u003eThis scenario illustrates that, even with nutritional counseling, social vulnerability, the availability of fresh foods, and market pressure can hinder the adoption of ideal food choices. Given the insufficiency of public policies to address the systemic factors that shape the availability, convenience, and aggressive promotion of these products, this challenge becomes even more evident, especially among vulnerable populations, where healthy alternatives tend to be less accessible and more expensive [45]. In this context, isolated clinical interventions are insufficient, underscoring the need to integrate care strategies with robust public policies that expand access to and acceptance of fresh and minimally processed foods, and to directly address commercial and structural determinants that sustain dependence on low-cost, industrialized products [46].\u003c/p\u003e \u003cp\u003eTherefore, encouraging the traditional Brazilian dietary pattern, combined with maintaining domestic culinary practices, should continue, as the presence of UPFs in this context can mitigate some of the adverse metabolic effects associated with high UPFs intake, reinforcing the importance of preserving and promoting regional culinary practices as a central nutritional strategy for addressing MASLD [47].\u003c/p\u003e \u003cp\u003eDespite the relevance of this study, the first to specifically evaluate UPFs consumption in patients with MASLD in the state of Bahia, some limitations should be considered. The cross-sectional design prevents establishing causal relationships between UPFs intake and clinical outcomes; the sample size, although adequate for exploring dietary patterns in a specialized service, may have reduced the statistical power to detect more subtle associations, especially after covariate adjustment. Furthermore, dietary assessment is subject to biases inherent in recall and underreporting, particularly relevant when analyzing UPFs, whose classification depends on the accuracy of reporting and the rigorous application of the NOVA system. These limitations reinforce the importance of prospective studies with larger sample sizes to deepen the understanding of the effects of UPFs on MASLD progression.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThe consumption of ultra-processed foods was high among patients with MASLD in this simple. Caloric intake is strongly driven by carbohydrates and total fat. Moreover, the lower consumption observed among individuals T2DM along with distinct consumption patterns of whole-wheat bread and margarine according to anthropometric measurements, reinforce the complexity of dietary behavior in this population. These findings underscore the clinical relevance of implementing nutritional care strategies to reduce UPFs consumption, such as home-cooking practices, as well as the importance of public policies combined with nutritional interventions. Despite the limitations inherent to its cross-sectional design, this pioneering study conducted in Brazil expands current knowledge on the role of UPFs in MASLD and provides a robust foundation for future longitudinal studies and targeted nutritional interventions.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eETHICAL APPROVAL\u003c/h2\u003e \u003cp\u003e The protocol for this study was submitted to and approved by the Ethics Committee of the School of Nutrition at the Federal University of Bahia, Salvador, Brazil, under opinion number 7.598.703.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCOMPETING INTERESTS\u003c/strong\u003e \u003cp\u003eThe authors have no competing interests\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFUNDING\u003c/h2\u003e \u003cp\u003e Open access funding provided by Federal University of Bahia\u003c/p\u003e\u003ch2\u003eAUTHOR CONTRIBUTIONS\u003c/h2\u003e \u003cp\u003eCAS and RR planned the research and wrote the first draft; CAS, LVV, and NSA collected the data; MS performed the ultrasound examinations; CD guided the statistical analyses; HPC provided technical review and final correction.\u003c/p\u003e\u003ch2\u003eACKNOWLEDGEMENTS\u003c/h2\u003e \u003cp\u003eThe authors gratefully acknowledge the commitment and dedication of all the students who contributed to this work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eMonteiro CA, Cannon G, Levy RB, Moubarac JC, Louzada ML, Rauber F, et al. 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Towards unified global action on ultra-processed foods: understanding commercial determinants, countering corporate power, and mobilising a public health response. Lancet. 2025; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0140-6736(25)01567-3\u003c/span\u003e\u003cspan class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eSalarini JS, Barroso LN, Freitas JV, Leite NC, de Paula TP, Padilha PC, et al. The Brazilian traditional dietary pattern was associated with a lower risk of advanced steatosis in patients with metabolic dysfunction-associated steatotic liver disease. Nutr Res. 2025; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.nutres.2025.04.012\u003c/span\u003e\u003cspan class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTABLE 1:\u0026nbsp;\u003c/strong\u003eSociodemographic and clinical characteristics of patients with metabolic dysfunction-associated steatotic liver disease, assessed according to the percentage of total energy value derived from ultra-processed foods.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"931\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;97\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 462px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% VET derived from AUPs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;p-value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCramer\u0026apos;s V\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 12.6%\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e24\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12.6% \u0026ndash; 25.0%\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e49\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;25,0%\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e24\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdults\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e59 (60.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e14 (23.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e31 (52.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e14 (23.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.884\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e76 (78.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e17 (22.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e39 (51.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e20 (26.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.550\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.111\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo occupation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e50 (52.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e6 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e27 (54.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e17 (34.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.348\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResides in the capital\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e71 (74.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e18 (25.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e35 (49.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e18 (25.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT2DM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e51 (52.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e15 (29.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e30 (58.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e6 (11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.008*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.317\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSAH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e55 (56.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e12 (21.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e31 (56.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e12 (21.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.419\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDyslipidemia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e36 (37.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e10 (27.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e17 (47.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e9 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAbsence of fibrosis - FIB4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e78 (96.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e20 (25.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e39 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e19 (24.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003enormal AST\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e73 (85.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e18 (24.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e36 (49.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e19 (26.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003enormal ALT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e66 (78,6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e20 (30,3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e31 (47,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e15 (22,7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0,104\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSteatosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003eMild\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e38 (41.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e10 (26.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e18 (47.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e10 (26.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.186\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e44 (48.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e10 (22.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e23 (52.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e11 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003eSevere\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e9 (9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e3 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e5 (55.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e1 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003eEutrophic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e16 (16.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e1 (6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e10 (62.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e5 (31.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e22 (22.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e9 (40.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e9 (40.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e4 (18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003eObesy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e59 (60.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e14 (23.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e30 (50.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e15 (25.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eDM2: Type 2 diabetes mellitus; HAS: Systemic arterial hypertension; FIB4: Fibrosis-4 score; AST: Aspartate aminotransferase; ALT: Alanine aminotransferase; BMI: Body mass index; TEV: Total energy value; AUPs: Ultra-processed foods; NA: Not applicable\u003c/p\u003e\n\u003cp\u003e*Pearson\u0026apos;s chi-square test.\u003c/p\u003e\n\u003cp\u003eCram\u0026eacute;r\u0026apos;s V presented as a measure of effect size (interpretation: \u0026lt;0.10 trivial; 0.10-0.30 weak; 0.30-0.50 moderate; \u0026gt;0.50 strong)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTABLE 2:\u0026nbsp;\u003c/strong\u003eCorrelation between residual added sugar, residual nutrients, and caloric intake from ultra-processed foods in patients with metabolic dysfunction-associated steatotic liver disease.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"593\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidual nutrient (UPF)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003e\u003cstrong\u003er-Spearman\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003eCarbohydrates (g)\u003c/p\u003e\n \u003cp\u003eProteins (g)\u003c/p\u003e\n \u003cp\u003eTotal fats (g)\u003c/p\u003e\n \u003cp\u003eSaturated fat (g)\u003c/p\u003e\n \u003cp\u003eMonounsaturated fat (g)\u003c/p\u003e\n \u003cp\u003ePolyunsaturated fat (g)\u003c/p\u003e\n \u003cp\u003eAdded sugar (g)\u003c/p\u003e\n \u003cp\u003eDietary fiber (g)\u003c/p\u003e\n \u003cp\u003eSodium (mg)\u003c/p\u003e\n \u003cp\u003eCalcium (mg)\u003c/p\u003e\n \u003cp\u003eIron (mg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.720\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.677\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.654\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.566\u003c/p\u003e\n \u003cp\u003e0.433\u003c/p\u003e\n \u003cp\u003e0.429\u003c/p\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003cp\u003e0.430\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.613\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.447\u003c/p\u003e\n \u003cp\u003e0.549\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ea. Spearman\u0026apos;s correlation coefficient\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTABLE 3:\u0026nbsp;\u003c/strong\u003eInfluence of residual nutrients on the caloric value of ultra-processed foods among patients with metabolic dysfunction-associated steatotic liver disease.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"594\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 193px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidual nutrient (UPF)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta; (standardized)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB (CI95%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 193px;\"\u003e\n \u003cp\u003eCarbohydrates (g)\u003c/p\u003e\n \u003cp\u003eProtein (g)\u003c/p\u003e\n \u003cp\u003eTotal fat (g)\u003c/p\u003e\n \u003cp\u003eSodium (mg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e0.416\u003c/p\u003e\n \u003cp\u003e0.223\u003c/p\u003e\n \u003cp\u003e0.307\u003c/p\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e0.004 (0.002 \u0026ndash; 0.006)\u003c/p\u003e\n \u003cp\u003e0.015 (0.003 \u0026ndash; 0.027)\u003c/p\u003e\n \u003cp\u003e0.012 (0.006 \u0026ndash; 0.018)\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e0.558\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAdjusted R\u0026sup2; = 0.686; p\u0026lt;0.001\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Federal University of Bahia","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"steatotic liver disease, MASLD, food consumption, ultra-processed foods","lastPublishedDoi":"10.21203/rs.3.rs-8894319/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8894319/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Ultra-processed foods (UPFs) are industrial formulations characterized by a high processing with the addition of food additives. Consumption of UPFs has been associated with adverse metabolic outcomes, including metabolic dysfunction-associated steatotic liver disease (MASLD). Lifestyle changes, including weight loss combined with caloric restrictions are central therapeutic strategies for metabolic control, qualitative dietary modifications may be crucial for the management of MASLD.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e: to determine the prevalence of UPFs consumption among patients with MASLD in outpatient follow-up and to assess its contribution to energy intake.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatients and Methods\u003c/strong\u003e: This cross-sectional study included patients diagnosed with MASLD, who were followed at a hepatology outpatient clinic. Sociodemographic, clinical, and anthropometric data were collected. Dietary intake was assessed using three 24-hour dietary recalls and classified according to NOVA system to quantify the contribution of UPFs to total caloric and nutrient intake.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Ninety-seven patients with MASLD were evaluated, women (78.4%), with a high frequency of obesity (60.8%), type 2 diabetes (52.6%), and systemic arterial hypertension (SAH) (56.7%). UPFs consumption ranged from 0.0% to 41.0% of total caloric intake. Higher UPF consumption was associated with lack of paid employment, whereas lower UPFs consumption was associated with the presence of type 2 diabetes (p \u0026lt; 0.05). Carbohydrates, total fats, and proteins derived from UPFs showed a strong positive correlation with caloric intake, with carbohydrates representing the main energy source.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: Consumption of UPFs was relevant in this sample of patients with MASLD, with energy intake derived from carbohydrates and total fats.\u003c/p\u003e","manuscriptTitle":"The Impact of Ultra-Processed Foods on Dietary Patterns in Patients with Metabolic Dysfunction–Associated Steatotic Liver Disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-18 09:56:15","doi":"10.21203/rs.3.rs-8894319/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"61cc347a-320c-4009-8150-689aa48873da","owner":[],"postedDate":"February 18th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":63018620,"name":"Gastroenterology \u0026 Hepatology"}],"tags":[],"updatedAt":"2026-02-18T09:56:15+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-18 09:56:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8894319","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8894319","identity":"rs-8894319","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}