Association between the consumption of ultra-processed foods and generalized anxiety disorder in adults with obesity seeking weight loss

Association between the consumption of ultra-processed foods and generalized anxiety disorder in adults with obesity seeking weight loss | 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 Association between the consumption of ultra-processed foods and generalized anxiety disorder in adults with obesity seeking weight loss João Victor Laurindo dos Santos, Dafiny Rodrigues Silva, Samyra Araujo Monteiro de Carvalho, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6227414/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Purpose The association between symptoms of generalized anxiety disorder (GAD) and the consumption of ultra-processed foods (UPF) needs to be better characterized in obese adults seeking weight loss. This study aimed to evaluate the relationship between GAD symptoms and UPF consumption in this Population. Methods A cross-sectional study was conducted with 148 adults (19–59 years old) with obesity recruited from a Brazilian university. Food consumption was assessed using three 24-hour dietary recalls, which were classified according to the NOVA classification. GAD was measured using the Generalized Anxiety Disorder Scale (GAD-7). Linear regression models adjusted for confounding factors, such as sex, age, economic status, and physical activity, were used to analyze the association between anxiety symptoms and UPF consumption. Results Higher GAD-7 scores were associated with greater UPF consumption (β = 0.445%; 95% CI: 0.042% – 0.849%; p = 0.031). There was no significant association between GAD and the intake of sodium (β = -18.464mg; 95% CI: -55.618mg – 18.689mg; p = 0.328), sugar (β = -0.127g; 95% CI: -0.342g – 0.087g; p = 0.243), or saturated fat (β = 0.290g; 95% CI: -0.024g – 0.604g; p = 0.070). The average UPF consumption was 22.8% of total energy intake. Conclusion Obese adults seeking weight loss who had higher anxiety symptoms consumed more UPF, suggesting a relationship between anxiety and dietary patterns. Longitudinal studies are needed to explore causality and underlying mechanisms. obesity weight loss anxiety diet food intake ultra-processed foods Figures Figure 1 Figure 2 Introduction Obesity is one of the major global public health challenges, with its prevalence among adults more than doubling between 1990 and 2022, affecting approximately 878 million adults worldwide [1]. This condition is associated with various physical comorbidities, especially non-communicable chronic diseases such as diabetes, cardiovascular diseases, and cancer, as well as mental disorders, among which generalized anxiety disorder (GAD) stands out [2-8]. GAD is characterized by excessive and persistent worry, accompanied by symptoms such as irritability, muscle tension, fatigue, and sleep disturbances [9], affecting over 301 million people globally [10]. Individuals with obesity, particularly those seeking to lose weight, are more vulnerable to psychological disorders compared to the general population [11]. This relationship can be explained by the psychological stress associated with the constant effort to change lifestyle habits and manage weight, which often exacerbates anxiety symptoms [12]. Diet has been widely explored as a determining factor in health, influencing both physical and mental aspects. Numerous studies are investigating the nutritional composition of diets, dietary patterns, and the level of food processing as variables of interest in determining physical and mental health outcomes [13-18]. In this context, the NOVA classification has emerged as a method to categorize foods according to the nature, extent, and purpose of industrial processing, dividing them into four groups: unprocessed or minimally processed foods, processed culinary ingredients, processed foods, and ultra-processed foods (UPF) [19]. UPFs are industrial formulations that undergo extensive transformations and contain ingredients rarely used in traditional culinary preparations, such as chemical additives like colorants, preservatives, flavor enhancers, and hydrogenated fats, which enhance the taste, texture, and organoleptic properties of these foods [19]. Additionally, these foods are often energy-dense, high in salt, free sugars, and saturated fats, while potentially low in fiber and, in many cases, vitamins and minerals [19]. The consumption of these foods has increased significantly in recent decades, accounting for more than 50% of the calories consumed in countries such as the United States and the United Kingdom [20,21]. In Brazil, data from the Household Budget Survey (2017-2018) reveal that UPF represents approximately 20% of the daily calories consumed by the Brazilian population [22]. This finding is particularly relevant, as the Dietary Guidelines for the Brazilian Population recommend limiting the consumption of these foods and prioritizing unprocessed or minimally processed foods as the foundation of a healthy diet [23]. The relationship between anxiety and the consumption of UPF appears to be bidirectional. Evidence suggests that individuals with higher levels of anxiety are more likely to consume these foods due to their high content of rewarding nutrients, such as sugar, sodium, and fat, which activate brain reward pathways and provide temporary relief from anxiety symptoms [24-26]. On the other hand, excessive consumption of UPF is associated with metabolic, inflammatory, and behavioral changes that may increase the risk of mental disorders, including anxiety [27-31]. However, this relationship, particularly in individuals with obesity who are interested in losing weight and may present unique metabolic and psychological vulnerabilities, still lacks sufficient clarification in the scientific literature. Therefore, this study aimed to evaluate the association between symptoms of GAD and the consumption of UPF in adults with obesity interested in weight loss. We hypothesize that individuals with higher levels of anxiety will consume more UPF. Methods Study design and ethical aspects This is a cross-sectional study using baseline data from a clinical trial titled: "Effectiveness and Metabolic Impacts of Restricting Ultra-Processed Food Consumption on Metabolic Adaptation and Weight Regain in Overweight Individuals Undergoing Caloric Restriction," registered in the Brazilian Registry of Clinical Trials (ReBEC) under the number RBR-3q9vgk9. The clinical trial was approved by the Research Ethics Committee of the Federal University of Alagoas under the Certificate of Ethical Appreciation Presentation number 56625522.0.0000.5013 and conducted in accordance with the principles of the Declaration of Helsinki. All participants provided written informed consent, indicating their voluntary participation. This article follows the guidelines of the Strengthening the Reporting of Observational Studies in Epidemiology – Nutritional Epidemiology (STROBE-nut) [32]. Location, population and sample The research was conducted at the Nutrition and Metabolism Laboratory of the Federal University of Alagoas (UFAL), located at the AC Simões campus in Maceió, Alagoas, with students, staff, and the surrounding community. The sampling method was non-probabilistic and convenience-based. Participants were recruited through announcements at the AC Simões campus of UFAL and invitations posted on Instagram and the official UFAL website. Adults (19-59 years old) of both sexes with obesity, defined by at least two of the following three criteria, were included: body mass index (BMI) between 25 and 40 kg/m², waist circumference ≥ 88 cm for women and ≥ 102 cm for men, and body fat percentage ≥ 35% for women and ≥ 25% for men, determined by bioelectrical impedance analysis. Participants were required to express a desire to lose weight but had to be weight-stable for at least one month at the time of inclusion in the clinical trial. Individuals using chronic medications such as antidiabetics, antihypertensives, antiretrovirals, immunosuppressants, and antidepressants; those with conditions preventing anthropometric measurements or assessment of energy expenditure components; postmenopausal, pregnant, or lactating women; and those who had undergone any surgical intervention for weight loss were excluded. Variables Exposure Generalized anxiety disorder scale (GAD-7) The GAD-7 is a scale developed by Spitzer et al. [33], designed to provide a quick self-report measure aimed at identifying probable cases of GAD. It was created in the United States with adult patients from 15 primary care clinics, based on the symptom criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), for GAD and other existing anxiety scales. The scale demonstrated high reliability and satisfactory validity in terms of criterion, construct, factorial, and procedural aspects. Additionally, a cutoff point was determined to maximize its diagnostic accuracy, with a sensitivity of 89% and specificity of 82% [33]. The GAD-7 consists of seven items that assess the frequency of signs and symptoms of generalized anxiety over the past two weeks. Its items are scored on a 4-point Likert scale, ranging from 0 (not at all) to 3 (nearly every day). A general suggested cutoff point for identifying GAD is 10 [33]. Outcome Dietary consumption Dietary consumption was assessed using the 24-hour dietary recall method, employing the Multiple Pass Method [34]. Three 24-hour dietary recalls were collected on different days, including two weekdays and one weekend day. During the collection, participants reported all foods and beverages consumed from the moment they woke up until bedtime. To assist in estimating the quantities consumed, a photographic manual of food quantification was used [35]. The collected data were processed using the NutraBem software (Federal University of São Paulo, São Paulo - SP), which converted the foods and beverages consumed into energy (kilocalories), macronutrients (in grams), and micronutrients (in milligrams). Additionally, NutraBem, coordinated by a team of academics who constantly update the software, particularly regarding the NOVA classification of foods, already classifies the consumed foods into unprocessed foods, minimally processed foods, processed culinary ingredients, processed foods, and UPF [19]. Covariates Anthropometric measurements For the anthropometric assessment, data on body weight, height, BMI, waist circumference, and body composition were collected. Body weight was measured using a digital Filizola® scale (São Paulo), with a capacity of 150 kg and an accuracy of 100 g. Participants were weighed, and they were wearing light clothing and without shoes. Height was measured using a wall-mounted stadiometer, with participants barefoot, feet together, back straight, and looking forward, adjusting the stadiometer so that the sliding arm touched the top of the participant's head. BMI was calculated according to World Health Organization criteria, using the formula: BMI = weight (kg) / height² (m). Waist circumference was measured with a flexible and non-elastic tape, positioned at the midpoint between the lower edge of the last rib and the iliac crest. Body composition was assessed using tetrapolar bioelectrical impedance analysis (RJL Quantum IV, RJL Systems Inc., Michigan, USA). The evaluation was performed with participants in a supine position after a 12-hour overnight fast. Instructions were provided to avoid caffeine consumption during the fast, refrain from physical exercise in the 24 hours prior to the assessment, and ensure an empty bladder at the time of measurement. Resistance and reactance data, expressed in ohms (Ω), along with information on age (years), sex, weight (kg), and height (cm), were processed using RJL software. The NHANES III formula was selected within the RJL software to estimate fat mass (kg), fat-free mass (kg), body water (L), and body fat percentage (%), ensuring standardized calculations based on bioelectrical impedance parameters. Physical activity level Physical activity level was estimated using triaxial accelerometers (ActiGraph wGT3X-BT, ActiGraph LLC, Pensacola, Florida, USA), which assess physical behavior by measuring acceleration in the anteroposterior, lateral, and vertical axes. The devices were attached to the participants' waists and worn for five consecutive days, including three weekdays and two weekend days. Participants were instructed not to remove the accelerometers during the wear period, except during water activities and bathing. Data collected by the accelerometers were processed using ActiLife software, version 6.13.3, and expressed in counts per minute (CPM), a quantitative indicator of body movement based on the data recorded by the accelerometers. Economic status Economic status was assessed using the Brazilian Economic Classification Criterion (CCEB) developed by the Brazilian Association of Research Companies. The CCEB classifies the Brazilian Population into different economic strata, considering the ownership of durable goods, education level, and access to services such as piped water and paved streets [36]. Based on the score obtained, individuals are categorized into six economic classes, ranging from class "A" (highest) to classes "D-E" (lowest) [36]. Bias To minimize potential biases, three 24-hour dietary recalls were collected to assess food consumption, and a triaxial accelerometer was used to estimate participants' physical activity levels. These approaches were chosen based on the fact that, regarding food consumption, collecting three 24-hour dietary recalls provides a more accurate estimate of energy and nutrient intake compared to a smaller number of recalls [37,38]. As for physical activity levels, questionnaires are susceptible to memory biases, such as difficulty recalling the intensity and duration of activities [39-41]. In contrast, the use of an accelerometer allows for a more precise assessment of physical activity levels, taking into account intensity, duration, and frequency, making it a more reliable method for this measurement [39-41]. Statistical analyses Continuous variables were described using measures of mean and standard deviation, while categorical variables were presented as absolute and relative frequencies. Multiple linear regression models were used to assess the association between the GAD score, estimated by the consumption of UPF, and nutritional outcomes. The independent variables were adjusted for potential confounding factors, including sex, age, body fat percentage, energy intake, socioeconomic status, and CPM (counts per minute). A directed acyclic graph (DAG) was developed to illustrate the causal pathways between generalized anxiety disorder and UPF consumption, taking into account the confounding variables included in the model (Figure 1). In addition to the variables included in the model, adjustments were also made to the participant's total energy intake [42]. Statistical analyses were performed using the Jamovi software, version 2.5.3, with an alpha value of 5%. Results The selection of participants followed the process described in the flowchart (Figure 2). Initially, 365 patients were assessed for eligibility. Of these, 217 were not included due to various reasons: 180 did not meet the inclusion criteria, 25 refused to participate, and 12 were excluded for other factors. As a result, 148 patients were included in the study. The mean age of the participants was 31.56 ± 8.39 years, with the majority being female (n = 115; 77.7%). Most participants belonged to economic classes B2 (n = 41; 27.7%), C1 (n = 37; 25%), and C2 (n = 42; 28.4%). Detailed characteristics of the sample are described in Table 1. The mean BMI was 31.59 ± 3.50 kg/m², and the mean body fat percentage was 41.89 ± 6.09%. The average counts per minute (CPM) was 505.66 ± 152.44. The mean GAD-7 score was 9.21 ± 5.27 points. The average energy intake, based on three dietary recalls per participant, was 2146.13 ± 651.19 kcal. The average intake of AUP was 503.74 ± 333.24 kcal, representing an average of 22.84 ± 12.73% of the total energy intake. Table 1. Descriptive characteristics and dietary consumption of the sample (n = 148). Variables n % CCEB A 7 4,7 B1 11 7,4 B2 41 27,7 C1 37 25,0 C2 42 28,4 D-E 10 6,8 Sex Female 115 77,7 Male 33 22,3 Mean SD GAD-7 (Score) 9.21 5.27 BMI (kg/m²) 31.59 3.50 Body Fat (%) 41.89 6.09 CPM 505.66 152.44 Age (years) 31.56 8.39 Dietary Consumption Energy (kcal) 2146.13 651.19 UPF (kcal) 503.74 333.24 UPF (%) 22.84 12.73 Carbohydrate (kcal) 1030.42 328.07 Carbohydrate (%) 48.93 7.12 Protein (kcal) 393.09 148.47 Protein (%) 18.63 4.09 Lipid (kcal) 707.24 272.22 Lipid (%) 32.36 5.51 Fiber (g) 18.27 8.03 Sodium (mg) 3478.25 1608.69 Sugar (g) 84.69 46.62 Sugar (%) 15.65 6.74 Saturated Fat (g) 33.32 24.55 Saturated Fat (%) 13.91 9.78 CCEB, Brazilian Economic Classification Criterion; GAD-7, Generalized Anxiety Disorder-7 Scale; BMI, Body Mass Index; CPM, Counts per Minute; UPF, Ultra-Processed Foods. The regression analysis results indicate a significant association between the GAD-7 score and the consumption of UPF (β = 0.445%; 95% CI: 0.042% – 0.849%; p = 0.031), suggesting that higher scores of anxiety symptoms on the GAD-7 are associated with greater consumption of UPF (Table 2). The model for this variable had an adjusted R² of 0.052, indicating that although the explained variability is small, the association is statistically significant. Table 2. Multiple linear regression models for the association between generalized anxiety disorder and the consumption of UPF and their rewarding components. Outcome Adjusted R² p-value 1 β CI 95% p-value 2 UPF (%) 0,052 0,042 0,445 0,042 : 0,849 0,031 Sodium (mg) 0,496 <0,001 -18,464 -55,618 : 18,689 0,328 Sugar (g) 0,044 0,063 -0,127 -0,342 : 0,087 0,243 Saturated Fat (g) 0,027 0,145 0,290 -0,024 : 0,604 0,070 The multiple linear regression models were adjusted for the following covariates: age (years), sex (female and male), body mass index (kg/m²), body fat (%), energy intake (kcal), Brazilian Economic Classification Criterion (A; B1 and B2; C1, C2, D-E), and physical activity level (CPM). 1 p-value of the model; 2 p-value of the Beta coefficient. On the other hand, no significant associations were found between the GAD-7 score and specific nutritional outcomes, such as sodium intake (β = -18.464mg; 95% CI: -55.618mg – 18.689mg; p = 0.328), sugar intake (β = -0.127g; 95% CI: -0.342g – 0.087g; p = 0.243), and saturated fat intake (β = 0.290g; 95% CI: -0.024g – 0.604g; p = 0.070). Additionally, the models for these variables showed low adjusted R² values (0.496 for sodium, 0.044 for sugar, and 0.027 for saturated fat), reinforcing the lack of statistically significant associations. Discussion This study's results revealed that the GAD-7 score was significantly associated with the consumption of UPF, indicating that higher levels of anxiety may be related to greater intake of these foods. On the other hand, no statistically significant associations were observed between the GAD-7 score and the intake of sodium, sugar, and saturated fat. It was found that, on average, 22.84% of the participants' total caloric intake came from UPF. Behavioral and physiological mechanisms can explain the association between GAD symptoms and UPF consumption. In behavioral terms, anxiety is linked to emotional eating, where individuals with high levels of anxiety tend to lose control over their eating, experiencing increased hunger and impulsive food consumption [43-45]. Dakanalis et al. [46], in a review, observed that patients with obesity, like the participants in this study, are more prone to emotional eating. Similarly, Cifuentes et al. [47] found that patients with obesity and anxiety exhibit less confidence in controlling their eating behaviors and a greater tendency toward emotional eating. From a physiological perspective, evidence suggests that ultra-processed foods affect the dopaminergic system, disrupting the brain's reward system. This can increase cravings for foods with rewarding components, such as UPF, creating a cycle that intensifies anxiety symptoms [48-50]. On the other hand, the literature often points to an inverse relationship compared to the findings of this study, where UPF consumption precedes the development of anxiety symptoms [51-54]. Hecht et al. [51], in a cross-sectional study using data from the National Health and Nutrition Examination Survey, observed that adults with higher UPF consumption were more likely to report more anxious days per month (RR: 1.19; 95% CI: 1.16–1.23). Complementarily, Sun et al. [52] demonstrated in a prospective cohort of 183,474 participants that higher UPF consumption was associated with an increased risk of anxiety (RR: 1.13; 95% CI: 1.06–1.21) over a follow-up period of 13.1 years. Although the GAD-7 score is associated with UPF consumption, the statistical analysis did not reveal significant associations between the GAD-7 score and the intake of sodium, sugar, and saturated fat. This suggests that the rewarding components of UPF, such as sodium, sugar, and saturated fats, are not directly related to this effect. The impact must be more associated with the overall food matrix of these products or its energy density. UPF are rich in sodium, saturated fats, and sugars but also contain a wide variety of artificial additives, emulsifiers, and potentially inflammatory compounds, which may influence mood regulation and brain function [55-57]. It is important to highlight that the average consumption of UPF among the study participants was 22.84% of total energy intake, a value close to the 19.7% reported in the 2017-2018 Household Budget Survey: Analysis of Personal Food Consumption in Brazil for the Brazilian Population [22]. Similar values have also been found in other studies conducted in Brazil. Silva et al. [58] reported that UPF intake accounted for 22.7% of total energy intake among 8,977 adult and elderly participants, and Canhada et al. [59] indicated that 24.6% of energy intake among 11,827 adult and elderly participants came from UPF [] . It is relevant to note that the value found is considerably lower compared to studies conducted in developed countries, such as the United States and the United Kingdom, where the average consumption of UPF exceeds 50% of total energy intake [20,21]. The present study has some limitations. Firstly, the cross-sectional design prevents the determination of causal relationships between anxiety and UPF consumption. Another limitation was the sample size was not calculated for the specific objective of this study, as it is a secondary analysis, which may affect the generalizability of the results and compromise the statistical power of the study. On the other hand, the study has strengths, such as the analysis conducted in a specific population, contributing to filling knowledge gaps about this group. Additionally, the use of three 24-hour dietary recalls allowed for a more accurate estimation of participants' food intake. The use of an accelerometer to estimate physical activity levels provided an objective and precise measure, while the use of the GAD-7 as an anxiety assessment tool added validity to the results, given its widespread recognition in the literature. Adjusting for relevant confounding factors also ensured greater robustness in the statistical analysis. Conclusion In conclusion, higher GAD-7 scores were associated with greater consumption of UPF in obese adults who were interested in losing weight. Although our study's cross-sectional design does not allow for causal inferences, our findings suggest that higher levels of anxiety symptoms may be related to increased consumption of these foods. Future studies, particularly longitudinal and interventional ones, are needed to understand the mechanisms underlying this association and to evaluate the impact of modulating anxiety on dietary patterns. Declarations Acknowledgments The authors would like to thank all the participants involved in this study. The contribution of each individual was essential to the completion of this research. Conflict of Interest: The authors have no conflicts of interest to disclose. Ethics approval and consent to participate: This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Research Ethics Committee of the Federal University of Alagoas (Certificate of Ethical Appreciation Presentation number 56625522.0.0000.5013). Informed consent was obtained from all individual participants included in the study. Consent to Publish: Not applicable. Author Contributions: J.V.L.S. contributed to the writing of the original draft and the review and editing of the manuscript. D.R.S. participated in the investigation and the review and editing of the manuscript. S.A.M.C., D.C.F., R.T.L.C., and N.G.S.L. were responsible for data curation, including data tabulation and organization. M.L.M. and A.E.S.J. were involved in the investigation and the review and editing of the manuscript. I.S.V.M. contributed to supervision, validation, and the review and editing of the manuscript. N.B.B. performed the formal analysis of the data, in addition to conceptualization, project administration, and the review and editing of the manuscript. All authors reviewed and approved the final version of the manuscript. Funding This study was fully funded by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) under the call CNPq/MCTI/FNDCT No. 18/2021 - Faixa A - Grupos Emergentes, with the process number 409166/2021-9. Additionally, this work was carried out with the support of the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Financing Code 001. 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Lachat C, Hawwash D, Ocké MC, Berg C, Forsum E, Hörnell A, et al. Strengthening the Reporting of Observational Studies in Epidemiology–nutritional epidemiology (STROBE‐nut): An extension of the STROBE statement. Nutr Bull. 2016;41(3):240-251. https://doi.org/10.1111/nbu.12217. Spitzer RL, Kroenke K, Williams JBW, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006;166(10):1092-1097. https://doi.org/10.1001/archinte.166.10.1092. Moshfegh AJ, Rhodes DG, Baer DJ, Murayi T, Clemens JC, Rumpler WV, et al. The US Department of Agriculture Automated Multiple-Pass Method reduces bias in the collection of energy intakes. Am J Clin Nutr. 2008;88(2):324-332. https://doi.org/10.1093/ajcn/88.2.324. Crispim SP, Fisberg RM, Marchioni DML, Steluti J. Manual fotográfico de quantificação alimentar. Curitiba: Universidade Federal do Paraná; 2017. Brazilian Association of Research Companies. Brazilian Economic Classification Criteria. 2022. Available at: https://abep.org/criterio-brasil/ (accessed 8 February 2025). Ma Y, Olendzki BC, Pagoto SL, Hurley TG, Magner RP, Ockene IS, et al. Number of 24-hour diet recalls needed to estimate energy intake. Ann Epidemiol. 2009;19(8):553-559. https://doi.org/10.1016/j.annepidem.2009.04.010. Shamah-Levy T, Rodríguez-Ramírez S, Gaona-Pineda EB, Cuevas-Nasu L, Carriquiry AL, Rivera JA. Three 24-hour recalls in comparison with one improve the estimates of energy and nutrient intakes in an urban Mexican population. J Nutr. 2016;146(5):1043-1050. https://doi.org/10.3945/jn.115.219683. Hills AP, Mokhtar N, Byrne NM. Assessment of physical activity and energy expenditure: an overview of objective measures. Front Nutr. 2014;1:5. https://doi.org/10.3389/fnut.2014.00005. Aparicio-Ugarriza R, Mielgo-Ayuso J, Benito PJ, Pedrero-Chamizo R, Ara I, González-Gross M, et al. Physical activity assessment in the general population; instrumental methods and new technologies. Nutr Hosp. 2015;31(Suppl 3):219-226. https://doi.org/10.3305/nh.2015.31.sup3.8769. Ndagijimana D, Kim E-K. Measurement methods for physical activity and energy expenditure: a review. Clin Nutr Res. 2017;6(2):68-80. https://doi.org/10.7762/cnr.2017.6.2.68. Willett WC, Howe GR, Kushi LH. Adjustment for total energy intake in epidemiologic studies. Am J Clin Nutr. 1997;65(4 Suppl):1220S-1228S. https://doi.org/10.1093/ajcn/65.4.1220S. Hussenoeder FS, Conrad I, Löbner M, Löffler M, Tönjes A, Sturmvoll M, et al. Understanding eating-related health outcomes: connections between anxiety and eating behavior. Eur J Public Health. 2022;32(Suppl 3):ckac129.698. https://doi.org/10.1093/eurpub/ckac129.698. Kaner G, Yurtdaş-Depboylu G, Çalık G, Yalçın T, Nalçakan T. Evaluation of perceived depression, anxiety, stress levels and emotional eating behaviours and their predictors among adults during the COVID-19 pandemic. Public Health Nutr. 2023;26(3):674-683. https://doi.org/10.1017/S1368980022002579. Fonseca NKO, Costa MA, Gosmann NP, Molle RD, Gonçalves FG, Silva AC, et al. Emotional eating in women with generalized anxiety disorder. Trends Psychiatry Psychother. 2023;45:e20210399. https://doi.org/10.47626/2237-6089-2021-0399. Dakanalis A, Mentzelou M, Papadopoulou SK, Papandreou D, Spanoudaki M, Vasios GK, et al. The association of emotional eating with overweight/obesity, depression, anxiety/stress, and dietary patterns: a review of the current clinical evidence. Nutrients. 2023;15(5):1173. https://doi.org/10.3390/nu15051173. Cifuentes L, Campos A, Silgado MLR, Kelpin S, Stutzman J, Hurtado MD, et al. Association between anxiety and eating behaviors in patients with obesity. Obes Pillars. 2022;3:100021. https://doi.org/10.1016/j.obpill.2022.100021. Wilcox CE, Farrar DC. Highly Palatable Foods Are Addictive. In: Wilcox CE, editor. Food Addiction, Obesity, and Disorders of Overeating. Cham: Springer; 2021. p. 153-163. https://doi.org/10.1007/978-3-030-83078-6_11. Gearhardt AN, Schulte EM. Is food addictive? A review of the science. Annu Rev Nutr. 2021;41:387-410. https://doi.org/10.1146/annurev-nutr-110420-111710. Hanßen R, Schiweck C, Aichholzer M, Reif A, Thanarajah SE. Food reward and its aberrations in obesity. Curr Opin Behav Sci. 2022;48:101224. https://doi.org/10.1016/j.cobeha.2022.101224. Hecht EM, Rabil A, Martinez Steele E, Abrams GA, Ware D, Landy DC, et al. Cross-sectional examination of ultra-processed food consumption and adverse mental health symptoms. Public Health Nutr. 2022;25(12):3225-3234. https://doi.org/10.1017/s1368980022001586. Sun M, He Q, Li G, Zhao H, Wang Y, Ma Z, et al. Association of ultra-processed food consumption with incident depression and anxiety: a population-based cohort study. Food Funct. 2023;14(16):7631-7641. https://doi.org/10.1039/d3fo01120h. Meller FO, Costa CS, Quadra MR, Miranda VIA, Eugênio FD, Silva TJ, et al. Consumption of ultra-processed foods and mental health of pregnant women from the South of Brazil. Br J Nutr. 2024;1-8. https://doi.org/10.1017/S0007114524000783. Lane MM, Gamage E, Travica N, Dissanayaka T, Ashtree DN, Gauci S, et al. Ultra-processed food consumption and mental health: a systematic review and meta-analysis of observational studies. Nutrients. 2022;14(13):2568. https://doi.org/10.3390/nu14132568. Contreras-Rodriguez O, Solanas M, Escorihuela RM. Dissecting ultra-processed foods and drinks: Do they have a potential to impact the brain? Rev Endocr Metab Disord. 2022;23(6):697-717. https://doi.org/10.1007/s11154-022-09711-2. Doney E, Cadoret A, Dion-Albert L, Lebel M, Menard C. Inflammation‐driven brain and gut barrier dysfunction in stress and mood disorders. Eur J Neurosci. 2022;55(9-10):2851-2894. https://doi.org/10.1111/ejn.15239. Petruso F, Giff AE, Milano BA, De Rossi MM, Saccaro LF. Inflammation and emotion regulation: a narrative review of evidence and mechanisms in emotion dysregulation disorders. Neuronal Signal. 2023;7(1):NS20220077. https://doi.org/10.1042/NS20220077. Silva FM, Giatti L, Figueiredo RC, Molina MCB, Cardoso LO, Duncan BB, et al. Consumption of ultra-processed food and obesity: cross sectional results from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) cohort (2008–2010). Public Health Nutr. 2018;21(12):2271-2279. https://doi.org/10.1017/s1368980018000861. Canhada SL, Luft VC, Giatti L, Duncan BB, Chor D, Fonseca MJM, et al. Ultra-processed foods, incident overweight and obesity, and longitudinal changes in weight and waist circumference: the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Public Health Nutr. 2020;23(6):1076 1086. https://doi.org/10.1017/S1368980019002854. Additional Declarations No competing interests reported. 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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-6227414","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":432701244,"identity":"79a0fd28-0cb5-465c-8c94-19e89b9739f0","order_by":0,"name":"João Victor Laurindo dos Santos","email":"","orcid":"","institution":"Federal University of Alagoas","correspondingAuthor":false,"prefix":"","firstName":"João","middleName":"Victor Laurindo dos","lastName":"Santos","suffix":""},{"id":432701245,"identity":"82886517-2138-4e4b-8a47-596ee3ff5cea","order_by":1,"name":"Dafiny Rodrigues Silva","email":"","orcid":"","institution":"Federal University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Dafiny","middleName":"Rodrigues","lastName":"Silva","suffix":""},{"id":432701246,"identity":"0a18bd98-5e9c-4bfd-89bb-982761f59e42","order_by":2,"name":"Samyra Araujo Monteiro de Carvalho","email":"","orcid":"","institution":"Federal University of Alagoas","correspondingAuthor":false,"prefix":"","firstName":"Samyra","middleName":"Araujo Monteiro","lastName":"de Carvalho","suffix":""},{"id":432701247,"identity":"6e139b86-4795-44b7-8213-ce0a631f6b71","order_by":3,"name":"Débora Cavalcante Ferro","email":"","orcid":"","institution":"Federal University of Alagoas","correspondingAuthor":false,"prefix":"","firstName":"Débora","middleName":"Cavalcante","lastName":"Ferro","suffix":""},{"id":432701248,"identity":"82c807c9-17cc-4cc9-89ff-cbced6520db7","order_by":4,"name":"Rodrigo Tenório Lins Carnaúba","email":"","orcid":"","institution":"Federal University of Alagoas","correspondingAuthor":false,"prefix":"","firstName":"Rodrigo","middleName":"Tenório Lins","lastName":"Carnaúba","suffix":""},{"id":432701250,"identity":"4399c05d-515d-4fec-ba63-aaedba3b952a","order_by":5,"name":"Natália Gomes Silva Lopes","email":"","orcid":"","institution":"Federal University of Alagoas","correspondingAuthor":false,"prefix":"","firstName":"Natália","middleName":"Gomes Silva","lastName":"Lopes","suffix":""},{"id":432701251,"identity":"c3773f85-e34c-4289-9dbc-081842d7dad3","order_by":6,"name":"Mateus de Lima Macena","email":"","orcid":"","institution":"Federal University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Mateus","middleName":"de Lima","lastName":"Macena","suffix":""},{"id":432701252,"identity":"24fcb2f0-f1ec-4be6-a1e4-7285a5e30585","order_by":7,"name":"André Eduardo Silva Júnior","email":"","orcid":"","institution":"Federal University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"André","middleName":"Eduardo Silva","lastName":"Júnior","suffix":""},{"id":432701253,"identity":"ecfad9bd-2015-4df2-b7f5-f83686b8201c","order_by":8,"name":"Ingrid Sofia Vieira de Melo","email":"","orcid":"","institution":"Federal Institute of Alagoas","correspondingAuthor":false,"prefix":"","firstName":"Ingrid","middleName":"Sofia Vieira","lastName":"de Melo","suffix":""},{"id":432701255,"identity":"db0aeb5f-d8bc-49dd-9105-cdd606231ade","order_by":9,"name":"Nassib Bezerra Bueno","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDElEQVRIie3RPUvDQBjA8acU4hKcHznwM1wp5AWCn+WOgi5nliyCgoVCp5hZv0XHjhcCyXLomq1KBpcOcZG6iGeawSE9OjrcH3JcAj/uCQdgs/3X+BxYt2mj/ssNBECPIaPHS706+lGAZjLqydg9hvgnVdO+rSGm1UPeROwippu5g/IOwSdykISp8JArSKh6nk0FmyW0BE1KhDBjg4RK4QBfAl/VwiPXuzFfaUJaRw+mhgejL+9N25HN1iMBu+8Iym8DqRnF/SmuR4AVe5IvTWT7+y+YnCkxnaSs4k8lXwR5hm6YHhrsqvn4WkfxaaUmrzt2y7OiyGv5GZ377jDpw78v+pp0ZmCz2Ww2Yz/dHmFebeXC9QAAAABJRU5ErkJggg==","orcid":"","institution":"Federal University of Alagoas","correspondingAuthor":true,"prefix":"","firstName":"Nassib","middleName":"Bezerra","lastName":"Bueno","suffix":""}],"badges":[],"createdAt":"2025-03-14 14:53:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6227414/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6227414/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":79262634,"identity":"e583fba1-0761-4bbd-b84b-77adfddd7696","added_by":"auto","created_at":"2025-03-26 09:46:30","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":125993,"visible":true,"origin":"","legend":"\u003cp\u003eDirected acyclic graph illustrating the relationship between generalized anxiety disorder (exposure variable, yellow circle) and the consumption of ultra-processed foods (outcome variable, blue circle). The variables adjusted in the multivariable model (red ellipses) were considered potential confounding factors, with arrows indicating their relationships with the exposure and outcome.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6227414/v1/364877e2b29d6684c551090c.jpeg"},{"id":79262637,"identity":"7c0b6d7b-3c80-4977-93b7-978f685b0d5b","added_by":"auto","created_at":"2025-03-26 09:46:30","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":50929,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of participant selection.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6227414/v1/533d2ad0d4540478935c941a.jpeg"},{"id":79265528,"identity":"a7c27a57-3741-4c5c-91b0-1bfbeae4998d","added_by":"auto","created_at":"2025-03-26 10:02:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":885762,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6227414/v1/1549d000-883f-4932-940f-e4292e426673.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association between the consumption of ultra-processed foods and generalized anxiety disorder in adults with obesity seeking weight loss","fulltext":[{"header":"Introduction","content":"\u003cp\u003eObesity is one of the major global public health challenges, with its prevalence among adults more than doubling between 1990 and 2022, affecting approximately 878 million adults worldwide [1]. This condition is associated with various physical comorbidities, especially non-communicable chronic diseases such as diabetes, cardiovascular diseases, and cancer, as well as mental disorders, among which generalized anxiety disorder (GAD) stands out [2-8]. GAD is characterized by excessive and persistent worry, accompanied by symptoms such as irritability, muscle tension, fatigue, and sleep disturbances [9], affecting over 301 million people globally [10]. Individuals with obesity, particularly those seeking to lose weight, are more vulnerable to psychological disorders compared to the general population [11]. This relationship can be explained by the psychological stress associated with the constant effort to change lifestyle habits and manage weight, which often exacerbates anxiety symptoms [12].\u003c/p\u003e\n\u003cp\u003eDiet has been widely explored as a determining factor in health, influencing both physical and mental aspects. Numerous studies are investigating the nutritional composition of diets, dietary patterns, and the level of food processing as variables of interest in determining physical and mental health outcomes [13-18]. In this context, the NOVA classification has emerged as a method to categorize foods according to the nature, extent, and purpose of industrial processing, dividing them into four groups: unprocessed or minimally processed foods, processed culinary ingredients, processed foods, and ultra-processed foods (UPF) [19].\u003c/p\u003e\n\u003cp\u003eUPFs are industrial formulations that undergo extensive transformations and contain ingredients rarely used in traditional culinary preparations, such as chemical additives like colorants, preservatives, flavor enhancers, and hydrogenated fats, which enhance the taste, texture, and organoleptic properties of these foods [19]. Additionally, these foods are often energy-dense, high in salt, free sugars, and saturated fats, while potentially low in fiber and, in many cases, vitamins and minerals [19]. The consumption of these foods has increased significantly in recent decades, accounting for more than 50% of the calories consumed in countries such as the United States and the United Kingdom [20,21]. In Brazil, data from the Household Budget Survey (2017-2018) reveal that UPF represents approximately 20% of the daily calories consumed by the Brazilian population [22]. This finding is particularly relevant, as the Dietary Guidelines for the Brazilian Population recommend limiting the consumption of these foods and prioritizing unprocessed or minimally processed foods as the foundation of a healthy diet [23].\u003c/p\u003e\n\u003cp\u003eThe relationship between anxiety and the consumption of UPF appears to be bidirectional. Evidence suggests that individuals with higher levels of anxiety are more likely to consume these foods due to their high content of rewarding nutrients, such as sugar, sodium, and fat, which activate brain reward pathways and provide temporary relief from anxiety symptoms [24-26]. On the other hand, excessive consumption of UPF is associated with metabolic, inflammatory, and behavioral changes that may increase the risk of mental disorders, including anxiety [27-31]. However, this relationship, particularly in individuals with obesity who are interested in losing weight and may present unique metabolic and psychological vulnerabilities, still lacks sufficient clarification in the scientific literature. Therefore, this study aimed to evaluate the association between symptoms of GAD and the consumption of UPF in adults with obesity interested in weight loss. We hypothesize that individuals with higher levels of anxiety will consume more UPF.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy design and ethical aspects \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis is a cross-sectional study using baseline data from a clinical trial titled: \u0026quot;Effectiveness and Metabolic Impacts of Restricting Ultra-Processed Food Consumption on Metabolic Adaptation and Weight Regain in Overweight Individuals Undergoing Caloric Restriction,\u0026quot; registered in the Brazilian Registry of Clinical Trials (ReBEC) under the number RBR-3q9vgk9. The clinical trial was approved by the Research Ethics Committee of the Federal University of Alagoas under the Certificate of Ethical Appreciation Presentation number 56625522.0.0000.5013 and conducted in accordance with the principles of the Declaration of Helsinki. All participants provided written informed consent, indicating their voluntary participation. This article follows the guidelines of the Strengthening the Reporting of Observational Studies in Epidemiology \u0026ndash; Nutritional Epidemiology (STROBE-nut) [32].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLocation, population and sample \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research was conducted at the Nutrition and Metabolism Laboratory of the Federal University of Alagoas (UFAL), located at the AC Sim\u0026otilde;es campus in Macei\u0026oacute;, Alagoas, with students, staff, and the surrounding community.\u003c/p\u003e\n\u003cp\u003eThe sampling method was non-probabilistic and convenience-based. Participants were recruited through announcements at the AC Sim\u0026otilde;es campus of UFAL and invitations posted on Instagram and the official UFAL website.\u003c/p\u003e\n\u003cp\u003e\u003cspan lang=\"EN-US\"\u003eAdults (19-59 years old) of both sexes with obesity, defined by at least two of the following three criteria, were included: body mass index (BMI) between 25 and 40 kg/m\u0026sup2;, waist circumference \u0026ge; 88 cm for women and \u0026ge; 102 cm for men, and body fat percentage \u0026ge; 35% for women and \u0026ge; 25% for men, determined by bioelectrical impedance analysis. Participants were required to express a desire to lose weight but had to be weight-stable for at least one month at the time of inclusion in the clinical trial. Individuals using chronic medications such as antidiabetics, antihypertensives, antiretrovirals, immunosuppressants, and antidepressants; those with conditions preventing anthropometric measurements or assessment of energy expenditure components; postmenopausal, pregnant, or lactating women; and those who had undergone any surgical intervention for weight loss were excluded.\u003c/span\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVariables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExposure\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGeneralized anxiety disorder scale (GAD-7)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe GAD-7 is a scale developed by Spitzer et al. [33], designed to provide a quick self-report measure aimed at identifying probable cases of GAD. It was created in the United States with adult patients from 15 primary care clinics, based on the symptom criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), for GAD and other existing anxiety scales. The scale demonstrated high reliability and satisfactory validity in terms of criterion, construct, factorial, and procedural aspects. Additionally, a cutoff point was determined to maximize its diagnostic accuracy, with a sensitivity of 89% and specificity of 82% [33].\u003c/p\u003e\n\u003cp\u003eThe GAD-7 consists of seven items that assess the frequency of signs and symptoms of generalized anxiety over the past two weeks. Its items are scored on a 4-point Likert scale, ranging from 0 (not at all) to 3 (nearly every day). A general suggested cutoff point for identifying GAD is 10 [33].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOutcome\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDietary consumption\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDietary consumption was assessed using the 24-hour dietary recall method, employing the Multiple Pass Method\u003csup\u003e\u0026nbsp;\u003c/sup\u003e[34]. Three 24-hour dietary recalls were collected on different days, including two weekdays and one weekend day. During the collection, participants reported all foods and beverages consumed from the moment they woke up until bedtime.\u003c/p\u003e\n\u003cp\u003eTo assist in estimating the quantities consumed, a photographic manual of food quantification was used [35]. The collected data were processed using the NutraBem software (Federal University of S\u0026atilde;o Paulo, S\u0026atilde;o Paulo - SP), which converted the foods and beverages consumed into energy (kilocalories), macronutrients (in grams), and micronutrients (in milligrams). Additionally, NutraBem, coordinated by a team of academics who constantly update the software, particularly regarding the NOVA classification of foods, already classifies the consumed foods into unprocessed foods, minimally processed foods, processed culinary ingredients, processed foods, and UPF [19].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCovariates\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnthropometric measurements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor the anthropometric assessment, data on body weight, height, BMI, waist circumference, and body composition were collected. Body weight was measured using a digital Filizola\u0026reg; scale (S\u0026atilde;o Paulo), with a capacity of 150 kg and an accuracy of 100 g. Participants were weighed, and they were wearing light clothing and without shoes. Height was measured using a wall-mounted stadiometer, with participants barefoot, feet together, back straight, and looking forward, adjusting the stadiometer so that the sliding arm touched the top of the participant\u0026apos;s head. BMI was calculated according to World Health Organization criteria, using the formula: BMI = weight (kg) / height\u0026sup2; (m). Waist circumference was measured with a flexible and non-elastic tape, positioned at the midpoint between the lower edge of the last rib and the iliac crest. Body composition was assessed using tetrapolar bioelectrical impedance analysis (RJL Quantum IV, RJL Systems Inc., Michigan, USA). The evaluation was performed with participants in a supine position after a 12-hour overnight fast. Instructions were provided to avoid caffeine consumption during the fast, refrain from physical exercise in the 24 hours prior to the assessment, and ensure an empty bladder at the time of measurement. Resistance and reactance data, expressed in ohms (\u0026Omega;), along with information on age (years), sex, weight (kg), and height (cm), were processed using RJL software. The NHANES III formula was selected within the RJL software to estimate fat mass (kg), fat-free mass (kg), body water (L), and body fat percentage (%), ensuring standardized calculations based on bioelectrical impedance parameters.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhysical activity level\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePhysical activity level was estimated using triaxial accelerometers (ActiGraph wGT3X-BT, ActiGraph LLC, Pensacola, Florida, USA), which assess physical behavior by measuring acceleration in the anteroposterior, lateral, and vertical axes. The devices were attached to the participants\u0026apos; waists and worn for five consecutive days, including three weekdays and two weekend days. Participants were instructed not to remove the accelerometers during the wear period, except during water activities and bathing. Data collected by the accelerometers were processed using ActiLife software, version 6.13.3, and expressed in counts per minute (CPM), a quantitative indicator of body movement based on the data recorded by the accelerometers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEconomic status\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEconomic status was assessed using the Brazilian Economic Classification Criterion (CCEB) developed by the Brazilian Association of Research Companies. The CCEB classifies the Brazilian Population into different economic strata, considering the ownership of durable goods, education level, and access to services such as piped water and paved streets [36]. Based on the score obtained, individuals are categorized into six economic classes, ranging from class \u0026quot;A\u0026quot; (highest) to classes \u0026quot;D-E\u0026quot; (lowest) [36].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBias \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo minimize potential biases, three 24-hour dietary recalls were collected to assess food consumption, and a triaxial accelerometer was used to estimate participants\u0026apos; physical activity levels. These approaches were chosen based on the fact that, regarding food consumption, collecting three 24-hour dietary recalls provides a more accurate estimate of energy and nutrient intake compared to a smaller number of recalls [37,38]. As for physical activity levels, questionnaires are susceptible to memory biases, such as difficulty recalling the intensity and duration of activities [39-41]. In contrast, the use of an accelerometer allows for a more precise assessment of physical activity levels, taking into account intensity, duration, and frequency, making it a more reliable method for this measurement [39-41].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analyses \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eContinuous variables were described using measures of mean and standard deviation, while categorical variables were presented as absolute and relative frequencies. Multiple linear regression models were used to assess the association between the GAD score, estimated by the consumption of UPF, and nutritional outcomes. The independent variables were adjusted for potential confounding factors, including sex, age, body fat percentage, energy intake, socioeconomic status, and CPM (counts per minute). A directed acyclic graph (DAG) was developed to illustrate the causal pathways between generalized anxiety disorder and UPF consumption, taking into account the confounding variables included in the model (Figure 1). In addition to the variables included in the model, adjustments were also made to the participant\u0026apos;s total energy intake [42]. Statistical analyses were performed using the Jamovi software, version 2.5.3, with an alpha value of 5%.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe selection of participants followed the process described in the flowchart (Figure 2). Initially, 365 patients were assessed for eligibility. Of these, 217 were not included due to various reasons: 180 did not meet the inclusion criteria, 25 refused to participate, and 12 were excluded for other factors. As a result, 148 patients were included in the study.\u003c/p\u003e\n\u003cp\u003eThe mean age of the participants was 31.56 \u0026plusmn; 8.39 years, with the majority being female (n = 115; 77.7%). Most participants belonged to economic classes B2 (n = 41; 27.7%), C1 (n = 37; 25%), and C2 (n = 42; 28.4%). Detailed characteristics of the sample are described in Table 1. The mean BMI was 31.59 \u0026plusmn; 3.50 kg/m\u0026sup2;, and the mean body fat percentage was 41.89 \u0026plusmn; 6.09%. The average counts per minute (CPM) was 505.66 \u0026plusmn; 152.44. The mean GAD-7 score was 9.21 \u0026plusmn; 5.27 points. The average energy intake, based on three dietary recalls per participant, was 2146.13 \u0026plusmn; 651.19 kcal. The average intake of AUP was 503.74 \u0026plusmn; 333.24 kcal, representing an average of 22.84 \u0026plusmn; 12.73% of the total energy intake.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1.\u0026nbsp;Descriptive characteristics and dietary consumption of the sample (n = 148).\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"465\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eCCEB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\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: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e4,7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;B1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e7,4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;B2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e27,7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;C1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e25,0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;C2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e28,4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;D-E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e6,8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\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: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e77,7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e22,3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eGAD-7 (Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e9.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e5.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eBMI (kg/m\u0026sup2;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e31.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e3.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eBody Fat (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e41.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e6.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eCPM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e505.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e152.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e31.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e8.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eDietary Consumption\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\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: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Energy (kcal)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e2146.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e651.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; UPF (kcal)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e503.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e333.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; UPF (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e22.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e12.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Carbohydrate (kcal)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1030.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e328.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Carbohydrate (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e48.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e7.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Protein (kcal)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e393.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e148.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Protein (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e18.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e4.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Lipid (kcal)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e707.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e272.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Lipid (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e32.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e5.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Fiber (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e18.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e8.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Sodium (mg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e3478.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e1608.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Sugar (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e84.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e46.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Sugar (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e15.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e6.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Saturated Fat (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e33.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e24.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Saturated Fat (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e13.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e9.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eCCEB, Brazilian Economic Classification Criterion; GAD-7, Generalized Anxiety Disorder-7 Scale; BMI, Body Mass Index; CPM, Counts per Minute; UPF, Ultra-Processed Foods.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe regression analysis results indicate a significant association between the GAD-7 score and the consumption of UPF (\u0026beta; = 0.445%; 95% CI: 0.042% \u0026ndash; 0.849%; p = 0.031), suggesting that higher scores of anxiety symptoms on the GAD-7 are associated with greater consumption of UPF (Table 2). The model for this variable had an adjusted R\u0026sup2; of 0.052, indicating that although the explained variability is small, the association is statistically significant.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2.\u0026nbsp;Multiple linear regression models for the association between generalized anxiety disorder and the consumption of UPF and their rewarding components.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"513\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eOutcome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eAdjusted R\u0026sup2;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003ep-value\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e\u0026beta;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003eCI 95%\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003ep-value\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eUPF (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0,052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0,042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e0,445\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e0,042 : 0,849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0,031\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eSodium (mg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0,496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026lt;0,001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e-18,464\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e-55,618 : 18,689\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0,328\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eSugar (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0,044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0,063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e-0,127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e-0,342 : 0,087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0,243\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eSaturated Fat (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0,027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0,145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e0,290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e-0,024 : 0,604\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0,070\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe multiple linear regression models were adjusted for the following covariates: age (years), sex (female and male), body mass index (kg/m\u0026sup2;), body fat (%), energy intake (kcal), Brazilian Economic Classification Criterion (A; B1 and B2; C1, C2, D-E), and physical activity level (CPM).\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003ep-value of the model; \u003csup\u003e2\u003c/sup\u003ep-value of the Beta coefficient.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOn the other hand, no significant associations were found between the GAD-7 score and specific nutritional outcomes, such as sodium intake (\u0026beta; = -18.464mg; 95% CI: -55.618mg \u0026ndash; 18.689mg; p = 0.328), sugar intake (\u0026beta; = -0.127g; 95% CI: -0.342g \u0026ndash; 0.087g; p = 0.243), and saturated fat intake (\u0026beta; = 0.290g; 95% CI: -0.024g \u0026ndash; 0.604g; p = 0.070). Additionally, the models for these variables showed low adjusted R\u0026sup2; values (0.496 for sodium, 0.044 for sugar, and 0.027 for saturated fat), reinforcing the lack of statistically significant associations.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study\u0026apos;s results revealed that the GAD-7 score was significantly associated with the consumption of UPF, indicating that higher levels of anxiety may be related to greater intake of these foods. On the other hand, no statistically significant associations were observed between the GAD-7 score and the intake of sodium, sugar, and saturated fat. It was found that, on average, 22.84% of the participants\u0026apos; total caloric intake came from UPF.\u003c/p\u003e\n\u003cp\u003eBehavioral and physiological mechanisms can explain the association between GAD symptoms and UPF consumption. In behavioral terms, anxiety is linked to emotional eating, where individuals with high levels of anxiety tend to lose control over their eating, experiencing increased hunger and impulsive food consumption [43-45]. Dakanalis et al. [46], in a review, observed that patients with obesity, like the participants in this study, are more prone to emotional eating. Similarly, Cifuentes et al. [47] found that patients with obesity and anxiety exhibit less confidence in controlling their eating behaviors and a greater tendency toward emotional eating. From a physiological perspective, evidence suggests that ultra-processed foods affect the dopaminergic system, disrupting the brain\u0026apos;s reward system. This can increase cravings for foods with rewarding components, such as UPF, creating a cycle that intensifies anxiety symptoms [48-50]. On the other hand, the literature often points to an inverse relationship compared to the findings of this study, where UPF consumption precedes the development of anxiety symptoms [51-54]. Hecht et al. [51], in a cross-sectional study using data from the National Health and Nutrition Examination Survey, observed that adults with higher UPF consumption were more likely to report more anxious days per month (RR: 1.19; 95% CI: 1.16\u0026ndash;1.23). Complementarily, Sun et al. [52] demonstrated in a prospective cohort of 183,474 participants that higher UPF consumption was associated with an increased risk of anxiety (RR: 1.13; 95% CI: 1.06\u0026ndash;1.21) over a follow-up period of 13.1 years.\u003c/p\u003e\n\u003cp\u003eAlthough the GAD-7 score is associated with UPF consumption, the statistical analysis did not reveal significant associations between the GAD-7 score and the intake of sodium, sugar, and saturated fat. This suggests that the rewarding components of UPF, such as sodium, sugar, and saturated fats, are not directly related to this effect. The impact must be more associated with the overall food matrix of these products or its energy density. UPF are rich in sodium, saturated fats, and sugars but also contain a wide variety of artificial additives, emulsifiers, and potentially inflammatory compounds, which may influence mood regulation and brain function [55-57].\u003c/p\u003e\n\u003cp\u003eIt is important to highlight that the average consumption of UPF among the study participants was 22.84% of total energy intake, a value close to the 19.7% reported in the 2017-2018 Household Budget Survey: Analysis of Personal Food Consumption in Brazil for the Brazilian Population [22]. Similar values have also been found in other studies conducted in Brazil. Silva et al. [58] reported that UPF intake accounted for 22.7% of total energy intake among 8,977 adult and elderly participants, and Canhada et al. [59] indicated that 24.6% of energy intake among 11,827 adult and elderly participants came from UPF\u003csup\u003e[]\u003c/sup\u003e. It is relevant to note that the value found is considerably lower compared to studies conducted in developed countries, such as the United States and the United Kingdom, where the average consumption of UPF exceeds 50% of total energy intake\u003csup\u003e\u0026nbsp;\u003c/sup\u003e[20,21].\u003c/p\u003e\n\u003cp\u003eThe present study has some limitations. Firstly, the cross-sectional design prevents the determination of causal relationships between anxiety and UPF consumption. Another limitation was the sample size was not calculated for the specific objective of this study, as it is a secondary analysis, which may affect the generalizability of the results and compromise the statistical power of the study. On the other hand, the study has strengths, such as the analysis conducted in a specific population, contributing to filling knowledge gaps about this group. Additionally, the use of three 24-hour dietary recalls allowed for a more accurate estimation of participants\u0026apos; food intake. The use of an accelerometer to estimate physical activity levels provided an objective and precise measure, while the use of the GAD-7 as an anxiety assessment tool added validity to the results, given its widespread recognition in the literature. Adjusting for relevant confounding factors also ensured greater robustness in the statistical analysis.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, higher GAD-7 scores were associated with greater consumption of UPF in obese adults who were interested in losing weight. Although our study\u0026apos;s cross-sectional design does not allow for causal inferences, our findings suggest that higher levels of anxiety symptoms may be related to increased consumption of these foods. Future studies, particularly longitudinal and interventional ones, are needed to understand the mechanisms underlying this association and to evaluate the impact of modulating anxiety on dietary patterns.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank all the participants involved in this study. The contribution of each individual was essential to the completion of this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to disclose.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Research Ethics Committee of the Federal University of Alagoas (Certificate of Ethical Appreciation Presentation number 56625522.0.0000.5013). Informed consent was obtained from all individual participants included in the study.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;J.V.L.S. contributed to the writing of the original draft and the review and editing of the manuscript. D.R.S. participated in the investigation and the review and editing of the manuscript. S.A.M.C., D.C.F., R.T.L.C., and N.G.S.L. were responsible for data curation, including data tabulation and organization. M.L.M. and A.E.S.J. were involved in the investigation and the review and editing of the manuscript. I.S.V.M. contributed to supervision, validation, and the review and editing of the manuscript. N.B.B. performed the formal analysis of the data, in addition to conceptualization, project administration, and the review and editing of the manuscript. All authors reviewed and approved the final version of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;This study was fully funded by the Conselho Nacional de Desenvolvimento Cient\u0026iacute;fico e Tecnol\u0026oacute;gico (CNPq) under the call CNPq/MCTI/FNDCT No. 18/2021 - Faixa A - Grupos Emergentes, with the process number 409166/2021-9. Additionally, this work was carried out with the support of the Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de N\u0026iacute;vel Superior \u0026ndash; Brasil (CAPES) \u0026ndash; Financing Code 001. The funding agencies had no role in the design, analysis, or writing of this article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePhelps NH, Singleton RK, Zhou B, Heap RA, Mishra A, Bennett JE, et al. Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults. Lancet. 2024;403(1027-1050). https://doi.org/10.1016/S0140-6736(23)02750-2.\u003c/li\u003e\n\u003cli\u003eAkil L, Ahmad HA. Relationships between obesity and cardiovascular diseases in four southern states and Colorado. J Health Care Poor Underserved. 2011;22(1):61-72. https://doi.org/10.1353/hpu.2011.0166.\u003c/li\u003e\n\u003cli\u003eKearns K, Dee A, Fitzgerald AP, Doherty E, Perry IJ. Chronic disease burden associated with overweight and obesity in Ireland: the effects of a small BMI reduction at population level. 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Public Health Nutr. 2020;23(6):1076 1086. https://doi.org/10.1017/S1368980019002854.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nutrire","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Nutrire](https://www.springer.com/journal/41110)","snPcode":"41110","submissionUrl":"https://submission.nature.com/new-submission/41110/3","title":"Nutrire","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"obesity, weight loss, anxiety, diet, food intake, ultra-processed foods","lastPublishedDoi":"10.21203/rs.3.rs-6227414/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6227414/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThe association between symptoms of generalized anxiety disorder (GAD) and the consumption of ultra-processed foods (UPF) needs to be better characterized in obese adults seeking weight loss. This study aimed to evaluate the relationship between GAD symptoms and UPF consumption in this Population.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional study was conducted with 148 adults (19\u0026ndash;59 years old) with obesity recruited from a Brazilian university. Food consumption was assessed using three 24-hour dietary recalls, which were classified according to the NOVA classification. GAD was measured using the Generalized Anxiety Disorder Scale (GAD-7). Linear regression models adjusted for confounding factors, such as sex, age, economic status, and physical activity, were used to analyze the association between anxiety symptoms and UPF consumption.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eHigher GAD-7 scores were associated with greater UPF consumption (β\u0026thinsp;=\u0026thinsp;0.445%; 95% CI: 0.042% \u0026ndash; 0.849%; p\u0026thinsp;=\u0026thinsp;0.031). There was no significant association between GAD and the intake of sodium (β = -18.464mg; 95% CI: -55.618mg \u0026ndash; 18.689mg; p\u0026thinsp;=\u0026thinsp;0.328), sugar (β = -0.127g; 95% CI: -0.342g \u0026ndash; 0.087g; p\u0026thinsp;=\u0026thinsp;0.243), or saturated fat (β\u0026thinsp;=\u0026thinsp;0.290g; 95% CI: -0.024g \u0026ndash; 0.604g; p\u0026thinsp;=\u0026thinsp;0.070). The average UPF consumption was 22.8% of total energy intake.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eObese adults seeking weight loss who had higher anxiety symptoms consumed more UPF, suggesting a relationship between anxiety and dietary patterns. Longitudinal studies are needed to explore causality and underlying mechanisms.\u003c/p\u003e","manuscriptTitle":"Association between the consumption of ultra-processed foods and generalized anxiety disorder in adults with obesity seeking weight loss","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-26 09:46:26","doi":"10.21203/rs.3.rs-6227414/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-03-21T22:44:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"19747083907342994166001557441633211048","date":"2025-03-19T06:53:06+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-18T11:33:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-18T11:32:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-17T07:46:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"Nutrire","date":"2025-03-14T14:40:07+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nutrire","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Nutrire](https://www.springer.com/journal/41110)","snPcode":"41110","submissionUrl":"https://submission.nature.com/new-submission/41110/3","title":"Nutrire","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b77d3b08-0d68-4336-a2fc-a1ed6c1a7a8c","owner":[],"postedDate":"March 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-07-11T18:08:26+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-26 09:46:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6227414","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6227414","identity":"rs-6227414","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}