From concept to measurement: Initial validation of the Ultra-Processed Food Consumption Scale

From concept to measurement: Initial validation of the Ultra-Processed Food Consumption Scale | 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 From concept to measurement: Initial validation of the Ultra-Processed Food Consumption Scale Michail Mantzios, Misba Hussain, Kyriaki Giannou This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8473971/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Feb, 2026 Read the published version in Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity → Version 1 posted 7 You are reading this latest preprint version Abstract Purpose High consumption of ultra-processed food (UPF) has been consistently linked to negative health outcomes, but existing tools for assessing UPF consumption are often lengthy, culturally specific, or psychometrically underdeveloped. The present research aimed to develop and validate the Ultra-Processed Food Consumption Scale (UPFCS); that is, a brief, psychometrically sound, and cross-culturally applicable measurement. Methods In Study 1 (n = 325), exploratory factor analysis (EFA) was conducted to examine the factorial structure and internal consistency of the 30-item UPFCS. Study 2 (n = 129) evaluated test–retest reliability across a two-week interval, and Study 3 (n = 144) assessed convergent validity by examining associations to Mediterranean Diet adherence, Body Mass Index (BMI), and food addiction, as well as testing the moderating role of Mediterranean Diet adherence. Results EFA and internal consistency supported a unidimensional structure, while test–retest reliability was moderate to strong. UPFCS scores were positively associated with food addiction symptoms, but not with BMI or Mediterranean Diet adherence. Exploratory moderation analysis indicated that adherence to a Mediterranean Diet attenuated the relationship between UPF consumption and food addiction symptoms, with the effect strongest among those with low Mediterranean dietary adherence. Conclusions The UPFCS demonstrates robust psychometric properties and practical utility for assessing ultra-processed food consumption in behavioral and nutritional research. Ultra-Processed Food Consumption Scale Ultra-Processed Foods NOVA classification food addiction Mediterranean Diet Introduction A growing body of epidemiological and clinical evidence linking high UPF intake to a wide range of adverse health outcomes (Blanco-Rojo et al., 2019 ; Bonaccio et al., 2021 ; Dominguez et al., 2018), making the monitoring and measurement of ultra-processed food consumption significant for years to come. Systematic reviews and meta-analyses have consistently demonstrated that elevated consumption of UPF is associated with increased risks of all-cause mortality, cardiovascular disease, type 2 diabetes, obesity and cancer diagnoses (Lane et al., 2024 ; Martini et al., 2021; Taneri et al., 2022). Moreover, UPFs have been implicated with mental health difficulties (Lane et al., 2022 ; Lopes Cortes et al., 2021 ); findings that collectively highlight the urgent need for scalable, reliable, and universally applicable tools to assess UPF consumption to advance behavioural science research aimed at reducing the burden of diet-related diseases. The exponential growth in research on food processing is closely aligned with the NOVA classification system, which has become the dominant framework for categorising foods from unprocessed to ultra-processed (Monteiro et al., 2019a, b). Despite its widespread adoption, the methods used to evaluate ultra-processed food (UPF) intake remain somewhat unstandardised, lacking the ability to replicate and compare, and often impractical when aiming to use in behavioural science research. Instruments such as the Food Frequency Questionnaire (FFQ), including NOVA-adapted and country-specific adaptations, alongside tools like the NOVA-27 UPF Screener, 24-hour dietary recalls, and 7-day dietary records, have been employed with varying degrees of success (Amorim et al., 2020 ; Dinu et al. 2021 ; Frade et al., 2025 ; Freire et al., 2025 ; Oviedo-Solís et al., 2022 ; Neri et al., 2023 ; Motta et al. 2021 ). However, these methods are frequently criticised for their length, complexity, and resource-intensive nature, as well as the lack of validation studies (Frade et al., 2025 ; Marino et al., 2021 ), limiting their scalability and cross-cultural applicability, despite the recognition of country-specific instruments carrying a unique value and having a place in the research spectrum of ultra-processed food intake. Present research In response, the present research introduces a scale that addresses the pressing need for a psychometrically sound and low-burden instrument that can be easily administered across diverse populations; that is, the Ultra-Processed Food Consumption Scale (UPFCS). To standardise the scale, 3 studies were conducted. Study 1 aimed to establish the factorial structure using Exploratory Factor Analysis (EFA) and internal consistency utilising alpha and omega coefficients. Study 2 aimed to determine the scale’s stability over time through test-retest reliability. Finally, Study 3 aimed to confirm the scale's construct validity by correlating UPFCS scores with measures of food addiction and Mediterranean diet adherence, as food addiction was highlighted in the literature on the association to UPF (e.g., Filgueiras et al., 2019 ; Wiss, 2022), and Mediterranean dieting as being the opposite to highly processed foods. Study 1 Method Participants The sample comprised 325 participants, with a mean age of 40.98 years ( SD = 12.85) and a mean BMI of 27.25 ( SD = 5.51). The gender distribution included 166 males and 158 females. Ethnic background was as follows: White British ( n = 271), Black British ( n = 26), British Asian ( n = 15), Mixed British ( n = 6), and 7 participants selected “other” without sharing any further details. Measures The Ultra-Processed Food Consumption Scale (UPFCS; Mantzios, Hussain & Giannou, 2025 ). Prior to the first validation study, a rigorous multi-phase process was initiated. Initially, an item pool of 35 items was generated based on the NOVA classification system, with considerations of additional literature (e.g., Bleiweiss-Sande et al., 2020 ; Davidou et al., 2021 ; Monteiro et al., 2019) for ultra-processed foods to be included in the final version of the scale, and with a focus on capturing UPF intake across diverse and global populations. Experts in nutrition ( n = 5) and health psychology ( n = 5) reviewed the items to establish initial content validity, ensuring alignment with theoretical and empirical definitions of ultra-processed foods. Following refinement, and removal of 5 items, the scale underwent participant appraisals (n = 60) from varied ethnic backgrounds and good command in English (n = 10 for each of the following countries: UK, USA, France, Mexico, South Korea, and Japan) to ensure presence and relevance within each country and cross-cultural applicability. Participants were given an option for each item “N/A – I never consume those foods”, and participants from all countries consumed, even at minimal doses (i.e., “0”) the foods listed in the final 30 item version. The UPFCS is a 30-item self-report instrument designed to quickly and reliably capture the frequency of consuming various ultra-processed foods (UPFs). Respondents rate their consumption frequency for each item using a five-point Likert scale from 0 (Never or less than once a month) to 4 (Daily or more). Sample items include instant meals and processed meats. The scale is scored by summing the responses to yield a total score between 0 and 120, where higher scores indicate a greater intake of ultra-processed foods. Procedure Participants were recruited through an online platform (i.e., Prolific), which provided the ability for them to be reimbursed for their participation time (£6.00/h). Participants were provided with a link to fill in the survey through an online platform (i.e., QuestionPro), and first viewed the participant information sheet and consent form, and upon consenting, were presented with the demographics page and the UPFCS. After completing the scale, the participants were directed to a debriefing page before their participation ended. Analysis To ensure data fitness, data screening was conducted by evaluating the presence of outliers, multivariate normality, linearity, and homogeneity of variance. Kaiser Meyer Olkin (KMO) for sampling adequacy and Bartlett’s test for sphericity were also assessed before proceeding with any attempts to conduct inferential statistics. Once all assumptions were satisfied, Exploratory Factor Analysis (EFA), with principal axis factor extraction and oblique rotation, was performed. Criteria to evaluate factor extraction were screeplot evaluation, eigenvalues (> 1), and item loading greater than .40 (Kaiser, 1960 ; Tabachnick & Fidell, 2007 ). Results An exploratory factor analysis (EFA) using principal component analysis was conducted on the 30 items assessing frequency of ultra-processed food (UPF) consumption. The suitability of the data for factor analysis was confirmed by the Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy, which was .882, indicating meritorious sampling adequacy. Bartlett’s Test of Sphericity was significant, χ²(435) = 2354.16, p < .001, confirming that correlations among items were sufficiently large for EFA. Although the initial eigenvalues greater than 1 suggested a seven-factor solution, inspection of the scree plot revealed a distinct inflection after the first component, indicating that a single-factor solution provided the only interpretable structure. The first component accounted for 31.65% of the total variance (eigenvalue = 9.50), while the second and subsequent components each explained less than 7% of additional variance. All items loaded positively on the first factor, with loadings ranging from .45 to .75, further suggesting that the items reflected a single underlying construct. Communalities ranged from .42 to .75, indicating that each item contributed meaningfully to the latent factor (see Table 1 ). The single factor represents a coherent dimension reflecting ultra-processed food consumption. Internal consistency for the 30-item scale was excellent, with Cronbach’s α = .91, and McDonald’s ω = .91, further supporting its unidimensionality of the scale. Collectively, these results indicate that the ultra-processed food consumption scale is a psychometrically sound and internally consistent unidimensional measure. Table 1 Item Loadings and Communality Item Loading Communality 1. Sweetened milk teas .55 .55 2. Pre-packaged iced teas .54 .55 3. Flavoured/powdered milk drinks .70 .69 4. Fruit drinks with added sugar .61 .53 5. Potato chips, shrimp crackers .60 .68 6. Packaged cookies, cakes .48 .75 7. Instant or cup noodles .58 .71 8. Sweetened/flavoured drinks .60 .64 9. Packaged cereal or granola .45 .56 10. Packaged sweet buns/pastries .51 .58 11. Pre-packaged croissants .58 .69 12. Frozen waffles or pancakes .75 .64 13. Fish balls, luncheon meats .66 .66 14. Sausages, deli meats .54 .54 15. Canned meat spreads .72 .62 16. Frozen pizzas or lasagna .52 .42 17. Instant rice bowls .66 .68 18. Congee mixes, instant soups .59 .61 19. Flavoured instant oatmeal .69 .55 20. Toaster pastries/pancakes .71 .59 21. Packaged salad dressings .42 .60 22. Instant gravy powders .51 .51 23. Sweetened spreads (e.g., jam, chocolate) .67 .55 24. Bubble tea with toppings .60 .60 25. Artificial whipped cream .61 .53 26. Jelly cups, instant puddings .45 .53 27. Sweetened soy or coconut milk .69 .68 28. Processed cheese slices .51 .46 29. Ready-to-drink protein shakes .53 .62 30. Plant-based burgers/nuggets .48 .58 Study 2 Method Participants The sample comprised 129 participants, with a mean age of 42.09 years ( SD = 10.34) and a mean BMI of 27.03 ( SD = 5.48). The gender distribution included 63 males and 65 females. The ethnic distribution was as follows: White British ( n = 103), White Other (n = 5), Black British ( n = 11), Mixed Race ( n = 3), Chinese British ( n = 3), and Pakistani British ( n = 3). Measures Ultra-Processed Food Consumption Scale ( UPFCS ; Mantzios, Hussain & Giannou, 2025 ). See Study 1 for description. Cronbach’s alpha was .928 for baseline test, and .916 for retest. Procedure As in Study 1, participants were invited through Prolific and the research was administered through Question Pro. Participants were asked to complete a food and perception questionnaire twice, over 2 weeks. In both instances, participants were provided with a link, where they viewed the participant information and consent forms, and once they consented, proceeded to the demographics page and the UPFCS. Once they completed the UPFCS, participants were directed to a debriefing page, which concluded their participation. Analysis Test–retest reliability was assessed to show the reliability over time of the UPFCS. Pearson’s correlation was used with strong correlation coefficients estimated at a value above r = .50 (Cohen, 2013 ). All data were analysed using IBM SPSS 28. Results Test-retest correlations demonstrated a moderate to strong level of stability over time. The original measure correlated significantly with the retest scores, r = .43, p < .001. Study 3 Method Participants The sample comprised 144 participants, with a mean BMI of 26.58 ( SD = 5.46). The gender distribution included 65 males and 75 females. Participants reported a wide range of ethnic backgrounds, with the majority identifying as White British ( n = 84), followed by White Other ( n = 13), Black British ( n = 13), Asian British ( n = 9), Mixed ( n = 5), and Other/Unspecified ( n = 20). Measures Ultra-Processed Food Consumption Scale ( UPFCS ; Mantzios, Hussain & Giannou, 2025 ). See Study 1 for description. Cronbach’s Alpha was .931. Mediterranean Diet Adherence Questionnaire ( MD ; Martınez-Gonzalez et al., 2004). The MD assesses adherence to a Mediterranean diet, and consists of 9-items. Sample items include legumes, fish and meat products. A score of 1 was assigned when the participant responded to the predetermined quantity proposed in the validation research (e.g., greater and equal to 1 serving/day) for fruit and vegetable, while 0 if the threshold was not met. Total scores could range from 0 to 9, with higher scores indicating greater adherence. Cronbach’s Alpha was .908. modified Yale Food Addiction Scale – Version 2.0 ( mYFAS 2.0 ; Schulte & Gearhardt, 2017 ). The mYFAS 2.0 proposes a measurement of addictive eating behaviour. The scale is composed of 13 items, rated on an eight-point Likert scale (from 0 = never to 7 = every day) assessing addictive eating behaviors (e.g., “I had such strong urges to eat certain foods that I could not think of anything else”; “I ate to the point where I felt physically ill”). The mYFAS 2.0. was scored on the basis of a symptom count where scores could range from 0 to 11. Cronbach’s Alpha was .918. Procedure Participants were recruited from Prolific and were reimbursed for their participation time (£6.00/h) as in the previous studies. Participants were provided with a link to fill in the survey through QuestionPro, and first viewed the participant information sheet, the consent form, and, upon consenting, were presented with the demographics page and the scales listed above. After completing the scales, the participants were directed to a debriefing page before their participation ended. Analysis Pearson correlation analyses were conducted to examine the relationships among Ultra-Processed Food Consumption (UPFC), Mediterranean Dieting (MD), Body Mass Index (BMI), and food addiction symptoms as measured by the Yale Food Addiction Scale (YFAS). Results A significant positive correlation was found between UPFC and YFAS scores, r = .27, p = .001, indicating that higher consumption of ultra-processed foods was associated with greater food addiction symptoms. Similarly, BMI was significantly positively correlated with YFAS scores, r = .33, p < .001, suggesting that individuals with higher BMI reported more severe food addiction symptoms. Table 2 Pearsons Correlation between UPFC, MD, BMI and YFAS UPFCS MD BMI UPFCS - MD .018 - BMI − .033 .011 - YFAS .270 ** − .124 .328 ** Note : UPFCS = Ultra-processed Food Consumption Scale; MD = Mediterranean Dieting; BMI = Body Mass Index; YFAS = Yale Food Addiction Scale A moderation analysis was conducted using PROCESS Model 1 (Hayes, 2022 ) to examine whether the relationship between Ultra-Processed Food Consumption (UPFC) and food addiction symptoms (YFAS scores) was moderated by adherence to a Mediterranean Diet (MD). The interaction between UPFC and MD approached significance ( b = − 0.0390, p = .0999), suggesting a potential moderating effect. To probe the interaction, conditional effects of UPFC on YFAS were examined at three levels of MD (16th, 50th, and 84th percentiles). The effect of UPFC on YFAS was significant at low levels of MD ( b = 0.2022, p = .0003), but not at moderate ( b = 0.0853, p = .1526) or high levels ( b = 0.0463, p = .5485). This pattern suggests that the positive association between UPFC and food addiction symptoms is stronger among individuals with lower adherence to the Mediterranean Diet. Table 3 Conditional Effects of UPFCS on YFAS at Values of Mediterranean Dieting (MD) MD (Percentile) Beta SE t p 95% CI (LLCI, ULCI) − 1SD 0.202 0.054 3.74 .0003 [0.0953, 0.3091] Moderate 0.085 0.059 1.44 .1526 [-0.0319, 0.2025] + 1SD 0.046 0.077 0.60 .5485 [-0.1059, 0.1985] Discussion The studies in the present manuscript introduce an initial validation of the Ultra-Processed Food Consumption Scale (UPFCS), a novel measure designed to capture UPF intake. The findings across three studies provide strong preliminary evidence for the scale’s reliability, validity, and applicability across diverse samples. Study 1 demonstrated that the UPFCS is best represented as a unidimensional construct, reflecting the frequency of ultra-processed food consumption. The scale’s high internal consistency, one dimensional loadings and satisfactory communalities indicate that the items coherently represent the intended domain of ultra-processed food consumption. Together, these findings establish the UPFCS as a statistically robust tool for measuring UPF consumption. Study 2 provided evidence of temporal stability, with a significant test–retest correlation over a two-week interval; a finding rather important for both longitudinal and intervention research, as well as assessments of policy impact across time. Study 3 examined the UPFCS in relation to established diet-related constructs. As expected, higher UPF consumption was associated with greater food addiction symptoms, consistent with existing literature linking UPFs to compulsive eating, overconsumption and food addictive markers (Filgueiras et al., 2019 ). This finding supported the convergent validity of the UPFCS, but interestingly, no significant correlations were found between UPF consumption, BMI, and adherence to Mediterranean Dieting. This may reflect the multifactorial nature of BMI and the potential for individuals to consume both healthy and ultra-processed foods simultaneously, observations of processed protein consumption that is on the rise, or potential implications for vegan and vegetarian populations that are consuming ultra-processed foods when they also fulfil a large portion of Mediterranean dieting. Importantly, adherence to a Mediterranean Diet moderated the association between UPF consumption and food addiction symptoms: the relationship was strongest among individuals with low adherence, suggesting that nutrient-dense dietary patterns may buffer against the addictive potential of UPFs. This finding aligns with historical and evolving evidence on the protective effects of Mediterranean Dieting by introducing another dimension on dietary quality and associations to psychological health (e.g., Coletro et al., 2022 ). Despite its strengths, several limitations should be acknowledged. The samples were limited to UK-based participants, recruited online, and potentially restricting in the generalizability to other populations. Self-reported dietary measures are inherently subject to recall and social desirability biases. Future research should aim to replicate these findings with international samples and examine criterion validity by comparing UPFCS scores with objective dietary intake data (e.g., 24-hour recalls or biomarker-based assessments). In conclusion, the Ultra-Processed Food Consumption Scale (UPFCS) represents a significant development in dietary assessment of UPF intake. Preliminary data offers a reliable, valid and efficient tool of quantifying UPF intake. Given the global rise in ultra-processed food consumption and its documented health consequences, the UPFCS holds considerable promise for informing research, policy, and intervention strategies aimed at improving dietary health and reducing the burden of diet-related diseases. Strengths and limits A key strength is the strong internal consistency, temporal stability, and convergent validity of the UPFCS across diverse UK samples. The development with expert review and cross-cultural item appraisal further supports practical utility as a low-burden measurement tool for ultra-processed food consumption. The reliance on self-reported data and UK-based samples limit generalisability, highlighting the need for international replication. What is already known on this subject? High consumption of ultra-processed foods is consistently associated with adverse physical and mental health outcomes. The NOVA classification system has become the dominant framework for defining and studying ultra-processed foods in nutritional research. However, existing methods for assessing UPF intake are often lengthy, resource-intensive, culturally specific, restricting their use in behavioural sciences and large-scale, as well as international studies. What this study adds? This study introduces the Ultra-Processed Food Consumption Scale (UPFCS), a brief, psychometrically robust, and theoretically grounded measure of UPF intake. The findings provide initial evidence that UPF consumption, as measured by the UPFCS, is positively associated with food addiction symptoms and that adherence to a Mediterranean diet may moderate this relationship. Disclaimers Declarations Ethical approval: Ethical approval was obtained by the host University’s Ethical Committee corresponding ethical guidelines. Application approval number: XXXX /#12194 /sub1 /Am /2025 /Feb /BLSS FAEC. Participants were presented with information sheets and consent forms. following specific instructions set in the guidelines of the British Psychological Society (BPS), where a designated consent page used checkboxes to allow participants to indicate that they have read and understood each statement and key aspects of the consent information before proceeding with the study. Consent for publication: Informed consent was obtained from all individual participants to publish the findings of this research. Funding: Internal University Funding supported the research for the reimbursement of participants. Author Contribution Author Contributions: All authors participated in designing the study. The first draft of the manuscript was written by the first author, and all authors edited earlier drafts. All authors reviewed and approved the final manuscript. Data Availability Data will be available on request from the corresponding author. References Amorim, A. C. L., Prado, B. 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Food frequency questionnaire for adults in the Brazilian Northeast region: emphasis on the level of food processing. Revista de saude publica , 55 , 51. https://doi.org/10.11606/ s1518-8787.2021055002473 Neri, D., Gabe, K. T., Costa, C. D. S., Martínez-Steele, E., Rauber, F., Marchioni, D. M., Louzada, M. L. da C., Levy, R. B., & Monteiro, C. A. (2023). A novel web-based 24-h dietary recall tool in line with the NOVA food classification: description and evaluation . Public Health Nutrition, 26(10), 1997–2004. doi: 10.1017/S1368980023001623 Oviedo-Solís, C. I., Monterrubio-Flores, E. A., Rodríguez-Ramírez, S., Cediel, G., Denova-Gutiérrez, E., & Barquera, S. (2022). A semi-quantitative food frequency questionnaire has relative validity to identify groups of NOVA food classification system among Mexican adults . Frontiers in Nutrition, 9, 737432. doi: 10.3389/fnut.2022.737432 Schulte, E. M., & Gearhardt, A. N. (2017). Development of the Modified Yale Food Addiction Scale Version 2.0 . European Eating Disorders Review, 25(4), 302–308. doi: 10.1002/erv.2515 Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). New York: Pearson. Ultra-Processed Food Consumption Scale (UPFCS; Mantzios, Hussain & Giannou, 2025) Instructions: Select how often you consume the following items using the provided response options: 0 = Never or less than once a month 1 = 1–3 times per month 2 = 1–2 times per week 3 = 3–6 times per week 4 = Daily or more Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 20 Feb, 2026 Read the published version in Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity → Version 1 posted Editorial decision: Revision requested 24 Jan, 2026 Reviews received at journal 20 Jan, 2026 Reviewers agreed at journal 07 Jan, 2026 Reviewers invited by journal 05 Jan, 2026 Editor assigned by journal 05 Jan, 2026 Submission checks completed at journal 30 Dec, 2025 First submitted to journal 29 Dec, 2025 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. 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Mantzios","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABD0lEQVRIiWNgGAWjYDACZgY2IGkB5RkwMPBLwKR48GoBK2NsAGmRnEFICwOKFpBFNwho0W1nfvbgR4UEkHH2+MMfBTb2xrebn0kw1NgxGJw5gFWL2WE2c8OeMxIMZmfyEhskDNISt905ZibBcCyZweBsAw4tPGwSvG1ALQdyDBsMDA4nmN3IYZNgYDvAYHAeu8NAWiT//gNqOf/GsCHB4LC98QyQln/4tUjzNgC13ADacsDgMOMGCaAWxrYDeBzGZiYtc0yCx+zGG8OZDUC/zLhzzNgisS+ZRxKX988ffib5psZGzux8jsHHH39s7PlnNz+88eGbnRzfmQTsLoMCtDhIwBeRo2AUjIJRMAoIAgAsc1gb6LArnwAAAABJRU5ErkJggg==","orcid":"","institution":"Birmingham City University","correspondingAuthor":true,"prefix":"","firstName":"Michail","middleName":"","lastName":"Mantzios","suffix":""},{"id":570716537,"identity":"9886171e-70f0-49be-9be5-5518d499c852","order_by":1,"name":"Misba Hussain","email":"","orcid":"","institution":"Birmingham City University","correspondingAuthor":false,"prefix":"","firstName":"Misba","middleName":"","lastName":"Hussain","suffix":""},{"id":570716540,"identity":"08f7128a-394d-49da-8ae5-edfb1a6a6ab0","order_by":2,"name":"Kyriaki Giannou","email":"","orcid":"","institution":"De Montfort University","correspondingAuthor":false,"prefix":"","firstName":"Kyriaki","middleName":"","lastName":"Giannou","suffix":""}],"badges":[],"createdAt":"2025-12-29 14:38:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8473971/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8473971/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s40519-026-01825-9","type":"published","date":"2026-02-20T15:58:27+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":99828521,"identity":"6961bea0-d082-4443-87c6-1421c6ce7c0e","added_by":"auto","created_at":"2026-01-08 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16:42:04","extension":"html","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":108346,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8473971/v1/65ec6ab258f4f4a1a3fb50ad.html"},{"id":103251280,"identity":"4cbca48b-f268-4a15-909b-438a1d73ae49","added_by":"auto","created_at":"2026-02-23 16:07:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":658476,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8473971/v1/890028ee-4e17-4c8f-8629-275c6320646a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"From concept to measurement: Initial validation of the Ultra-Processed Food Consumption Scale","fulltext":[{"header":"Introduction","content":"\u003cp\u003eA growing body of epidemiological and clinical evidence linking high UPF intake to a wide range of adverse health outcomes (Blanco-Rojo et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Bonaccio et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Dominguez et al., 2018), making the monitoring and measurement of ultra-processed food consumption significant for years to come. Systematic reviews and meta-analyses have consistently demonstrated that elevated consumption of UPF is associated with increased risks of all-cause mortality, cardiovascular disease, type 2 diabetes, obesity and cancer diagnoses (Lane et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Martini et al., 2021; Taneri et al., 2022). Moreover, UPFs have been implicated with mental health difficulties (Lane et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Lopes Cortes et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); findings that collectively highlight the urgent need for scalable, reliable, and universally applicable tools to assess UPF consumption to advance behavioural science research aimed at reducing the burden of diet-related diseases.\u003c/p\u003e \u003cp\u003eThe exponential growth in research on food processing is closely aligned with the NOVA classification system, which has become the dominant framework for categorising foods from unprocessed to ultra-processed (Monteiro et al., 2019a, b). Despite its widespread adoption, the methods used to evaluate ultra-processed food (UPF) intake remain somewhat unstandardised, lacking the ability to replicate and compare, and often impractical when aiming to use in behavioural science research. Instruments such as the Food Frequency Questionnaire (FFQ), including NOVA-adapted and country-specific adaptations, alongside tools like the NOVA-27 UPF Screener, 24-hour dietary recalls, and 7-day dietary records, have been employed with varying degrees of success (Amorim et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Dinu et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Frade et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Freire et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Oviedo-Sol\u0026iacute;s et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Neri et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Motta et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, these methods are frequently criticised for their length, complexity, and resource-intensive nature, as well as the lack of validation studies (Frade et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Marino et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), limiting their scalability and cross-cultural applicability, despite the recognition of country-specific instruments carrying a unique value and having a place in the research spectrum of ultra-processed food intake.\u003c/p\u003e\n\u003ch3\u003ePresent research\u003c/h3\u003e\n\u003cp\u003eIn response, the present research introduces a scale that addresses the pressing need for a psychometrically sound and low-burden instrument that can be easily administered across diverse populations; that is, the Ultra-Processed Food Consumption Scale (UPFCS). To standardise the scale, 3 studies were conducted. Study 1 aimed to establish the factorial structure using Exploratory Factor Analysis (EFA) and internal consistency utilising alpha and omega coefficients. Study 2 aimed to determine the scale\u0026rsquo;s stability over time through test-retest reliability. Finally, Study 3 aimed to confirm the scale's construct validity by correlating UPFCS scores with measures of food addiction and Mediterranean diet adherence, as food addiction was highlighted in the literature on the association to UPF (e.g., Filgueiras et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Wiss, 2022), and Mediterranean dieting as being the opposite to highly processed foods.\u003c/p\u003e "},{"header":"Study 1","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003eMethod\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section4\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eThe sample comprised 325 participants, with a mean age of 40.98 years (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;12.85) and a mean BMI of 27.25 (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.51). The gender distribution included 166 males and 158 females. Ethnic background was as follows: White British (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;271), Black British (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;26), British Asian (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;15), Mixed British (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6), and 7 participants selected \u0026ldquo;other\u0026rdquo; without sharing any further details.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cp\u003eThe Ultra-Processed Food Consumption Scale (UPFCS; Mantzios, Hussain \u0026amp; Giannou, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Prior to the first validation study, a rigorous multi-phase process was initiated. Initially, an item pool of 35 items was generated based on the NOVA classification system, with considerations of additional literature (e.g., Bleiweiss-Sande et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Davidou et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Monteiro et al., 2019) for ultra-processed foods to be included in the final version of the scale, and with a focus on capturing UPF intake across diverse and global populations. Experts in nutrition (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5) and health psychology (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5) reviewed the items to establish initial content validity, ensuring alignment with theoretical and empirical definitions of ultra-processed foods. Following refinement, and removal of 5 items, the scale underwent participant appraisals (n\u0026thinsp;=\u0026thinsp;60) from varied ethnic backgrounds and good command in English (n\u0026thinsp;=\u0026thinsp;10 for each of the following countries: UK, USA, France, Mexico, South Korea, and Japan) to ensure presence and relevance within each country and cross-cultural applicability. Participants were given an option for each item \u0026ldquo;N/A \u0026ndash; I never consume those foods\u0026rdquo;, and participants from all countries consumed, even at minimal doses (i.e., \u0026ldquo;0\u0026rdquo;) the foods listed in the final 30 item version.\u003c/p\u003e \u003cp\u003eThe UPFCS is a 30-item self-report instrument designed to quickly and reliably capture the frequency of consuming various ultra-processed foods (UPFs). Respondents rate their consumption frequency for each item using a five-point Likert scale from 0 (Never or less than once a month) to 4 (Daily or more). Sample items include instant meals and processed meats. The scale is scored by summing the responses to yield a total score between 0 and 120, where higher scores indicate a greater intake of ultra-processed foods.\u003c/p\u003e\n\u003ch3\u003eProcedure\u003c/h3\u003e\n\u003cp\u003eParticipants were recruited through an online platform (i.e., Prolific), which provided the ability for them to be reimbursed for their participation time (\u0026pound;6.00/h). Participants were provided with a link to fill in the survey through an online platform (i.e., QuestionPro), and first viewed the participant information sheet and consent form, and upon consenting, were presented with the demographics page and the UPFCS. After completing the scale, the participants were directed to a debriefing page before their participation ended.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis\u003c/h2\u003e \u003cp\u003eTo ensure data fitness, data screening was conducted by evaluating the presence of outliers, multivariate normality, linearity, and homogeneity of variance. Kaiser Meyer Olkin (KMO) for sampling adequacy and Bartlett\u0026rsquo;s test for sphericity were also assessed before proceeding with any attempts to conduct inferential statistics. Once all assumptions were satisfied, Exploratory Factor Analysis (EFA), with principal axis factor extraction and oblique rotation, was performed. Criteria to evaluate factor extraction were screeplot evaluation, eigenvalues (\u0026gt;\u0026thinsp;1), and item loading greater than .40 (Kaiser, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1960\u003c/span\u003e; Tabachnick \u0026amp; Fidell, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eResults\u003c/h3\u003e\n\u003cp\u003eAn exploratory factor analysis (EFA) using principal component analysis was conducted on the 30 items assessing frequency of ultra-processed food (UPF) consumption. The suitability of the data for factor analysis was confirmed by the Kaiser\u0026ndash;Meyer\u0026ndash;Olkin (KMO) measure of sampling adequacy, which was .882, indicating meritorious sampling adequacy. Bartlett\u0026rsquo;s Test of Sphericity was significant, χ\u0026sup2;(435)\u0026thinsp;=\u0026thinsp;2354.16, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, confirming that correlations among items were sufficiently large for EFA.\u003c/p\u003e \u003cp\u003eAlthough the initial eigenvalues greater than 1 suggested a seven-factor solution, inspection of the scree plot revealed a distinct inflection after the first component, indicating that a single-factor solution provided the only interpretable structure. The first component accounted for 31.65% of the total variance (eigenvalue\u0026thinsp;=\u0026thinsp;9.50), while the second and subsequent components each explained less than 7% of additional variance.\u003c/p\u003e \u003cp\u003eAll items loaded positively on the first factor, with loadings ranging from .45 to .75, further suggesting that the items reflected a single underlying construct. Communalities ranged from .42 to .75, indicating that each item contributed meaningfully to the latent factor (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The single factor represents a coherent dimension reflecting ultra-processed food consumption.\u003c/p\u003e \u003cp\u003eInternal consistency for the 30-item scale was excellent, with Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;.91, and McDonald\u0026rsquo;s ω\u0026thinsp;=\u0026thinsp;.91, further supporting its unidimensionality of the scale. Collectively, these results indicate that the ultra-processed food consumption scale is a psychometrically sound and internally consistent unidimensional measure.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eItem Loadings and Communality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLoading\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCommunality\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. Sweetened milk teas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. Pre-packaged iced teas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3. Flavoured/powdered milk drinks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4. Fruit drinks with added sugar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5. Potato chips, shrimp crackers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6. Packaged cookies, cakes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7. Instant or cup noodles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8. Sweetened/flavoured drinks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9. Packaged cereal or granola\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10. Packaged sweet buns/pastries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11. Pre-packaged croissants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12. Frozen waffles or pancakes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13. Fish balls, luncheon meats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14. Sausages, deli meats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15. Canned meat spreads\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16. Frozen pizzas or lasagna\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17. Instant rice bowls\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18. Congee mixes, instant soups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19. Flavoured instant oatmeal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20. Toaster pastries/pancakes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21. Packaged salad dressings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22. Instant gravy powders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23. Sweetened spreads (e.g., jam, chocolate)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24. Bubble tea with toppings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25. Artificial whipped cream\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26. Jelly cups, instant puddings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27. Sweetened soy or coconut milk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28. Processed cheese slices\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29. Ready-to-drink protein shakes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30. Plant-based burgers/nuggets\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Study 2","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMethod\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eThe sample comprised 129 participants, with a mean age of 42.09 years (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;10.34) and a mean BMI of 27.03 (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.48). The gender distribution included 63 males and 65 females. The ethnic distribution was as follows: White British (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;103), White Other \u003cem\u003e(n\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5), Black British (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;11), Mixed Race (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3), Chinese British (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3), and Pakistani British (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eMeasures\u003c/h2\u003e \u003cp\u003e \u003cem\u003eUltra-Processed Food Consumption Scale\u003c/em\u003e (\u003cem\u003eUPFCS\u003c/em\u003e; Mantzios, Hussain \u0026amp; Giannou, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). See Study 1 for description. Cronbach\u0026rsquo;s alpha was .928 for baseline test, and .916 for retest.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eProcedure\u003c/h2\u003e \u003cp\u003eAs in Study 1, participants were invited through Prolific and the research was administered through Question Pro. Participants were asked to complete a food and perception questionnaire twice, over 2 weeks. In both instances, participants were provided with a link, where they viewed the participant information and consent forms, and once they consented, proceeded to the demographics page and the UPFCS. Once they completed the UPFCS, participants were directed to a debriefing page, which concluded their participation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis\u003c/h2\u003e \u003cp\u003eTest\u0026ndash;retest reliability was assessed to show the reliability over time of the UPFCS. Pearson\u0026rsquo;s correlation was used with strong correlation coefficients estimated at a value above \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.50 (Cohen, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). All data were analysed using IBM SPSS 28.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eResults \u003c/h3\u003e\n\u003cp\u003eTest-retest correlations demonstrated a moderate to strong level of stability over time. The original measure correlated significantly with the retest scores, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.43, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001.\u003c/p\u003e"},{"header":"Study 3","content":" \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003eMethod\u003c/h2\u003e \u003cdiv id=\"Sec19\" class=\"Section4\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eThe sample comprised 144 participants, with a mean BMI of 26.58 (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.46). The gender distribution included 65 males and 75 females. Participants reported a wide range of ethnic backgrounds, with the majority identifying as White British (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;84), followed by White Other (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;13), Black British (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;13), Asian British (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;9), Mixed (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5), and Other/Unspecified (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;20).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eMeasures\u003c/h2\u003e \u003cp\u003e \u003cem\u003eUltra-Processed Food Consumption Scale\u003c/em\u003e (\u003cem\u003eUPFCS\u003c/em\u003e; Mantzios, Hussain \u0026amp; Giannou, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). See Study 1 for description. Cronbach\u0026rsquo;s Alpha was .931.\u003c/p\u003e \u003cp\u003e \u003cem\u003eMediterranean Diet Adherence Questionnaire\u003c/em\u003e (\u003cem\u003eMD\u003c/em\u003e; Martınez-Gonzalez et al., 2004). The MD assesses adherence to a Mediterranean diet, and consists of 9-items. Sample items include legumes, fish and meat products. A score of 1 was assigned when the participant responded to the predetermined quantity proposed in the validation research (e.g., greater and equal to 1 serving/day) for fruit and vegetable, while 0 if the threshold was not met. Total scores could range from 0 to 9, with higher scores indicating greater adherence. Cronbach\u0026rsquo;s Alpha was .908.\u003c/p\u003e \u003cp\u003e \u003cem\u003emodified Yale Food Addiction Scale \u0026ndash; Version 2.0\u003c/em\u003e (\u003cem\u003emYFAS 2.0\u003c/em\u003e; Schulte \u0026amp; Gearhardt, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The mYFAS 2.0 proposes a measurement of addictive eating behaviour. The scale is composed of 13 items, rated on an eight-point Likert scale (from 0\u0026thinsp;=\u0026thinsp;never to 7\u0026thinsp;=\u0026thinsp;every day) assessing addictive eating behaviors (e.g., \u0026ldquo;I had such strong urges to eat certain foods that I could not think of anything else\u0026rdquo;; \u0026ldquo;I ate to the point where I felt physically ill\u0026rdquo;). The mYFAS 2.0. was scored on the basis of a symptom count where scores could range from 0 to 11. Cronbach\u0026rsquo;s Alpha was .918.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eProcedure\u003c/h2\u003e \u003cp\u003eParticipants were recruited from Prolific and were reimbursed for their participation time (\u0026pound;6.00/h) as in the previous studies. Participants were provided with a link to fill in the survey through QuestionPro, and first viewed the participant information sheet, the consent form, and, upon consenting, were presented with the demographics page and the scales listed above. After completing the scales, the participants were directed to a debriefing page before their participation ended.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis\u003c/h2\u003e \u003cp\u003ePearson correlation analyses were conducted to examine the relationships among Ultra-Processed Food Consumption (UPFC), Mediterranean Dieting (MD), Body Mass Index (BMI), and food addiction symptoms as measured by the Yale Food Addiction Scale (YFAS).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eResults\u003c/h3\u003e\n\u003cp\u003eA significant positive correlation was found between UPFC and YFAS scores, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.27, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001, indicating that higher consumption of ultra-processed foods was associated with greater food addiction symptoms. Similarly, BMI was significantly positively correlated with YFAS scores, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.33, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, suggesting that individuals with higher BMI reported more severe food addiction symptoms.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePearsons Correlation between UPFC, MD, BMI and YFAS\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUPFCS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUPFCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYFAS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.270\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.328\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eNote\u003c/em\u003e: UPFCS\u0026thinsp;=\u0026thinsp;Ultra-processed Food Consumption Scale; MD\u0026thinsp;=\u0026thinsp;Mediterranean Dieting; BMI\u0026thinsp;=\u0026thinsp;Body Mass Index; YFAS\u0026thinsp;=\u0026thinsp;Yale Food Addiction Scale\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA moderation analysis was conducted using PROCESS Model 1 (Hayes, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) to examine whether the relationship between Ultra-Processed Food Consumption (UPFC) and food addiction symptoms (YFAS scores) was moderated by adherence to a Mediterranean Diet (MD). The interaction between UPFC and MD approached significance (\u003cem\u003eb\u003c/em\u003e = \u0026minus;\u0026thinsp;0.0390, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.0999), suggesting a potential moderating effect.\u003c/p\u003e \u003cp\u003eTo probe the interaction, conditional effects of UPFC on YFAS were examined at three levels of MD (16th, 50th, and 84th percentiles). The effect of UPFC on YFAS was significant at low levels of MD (\u003cem\u003eb\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.2022, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.0003), but not at moderate (\u003cem\u003eb\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0853, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.1526) or high levels (\u003cem\u003eb\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0463, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.5485). This pattern suggests that the positive association between UPFC and food addiction symptoms is stronger among individuals with lower adherence to the Mediterranean Diet.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eConditional Effects of UPFCS on YFAS at Values of Mediterranean Dieting (MD)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMD (Percentile)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% \u003cem\u003eCI\u003c/em\u003e (LLCI, ULCI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;1SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.0003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e[0.0953, 0.3091]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.1526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e[-0.0319, 0.2025]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e+\u0026thinsp;1SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.5485\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e[-0.1059, 0.1985]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe studies in the present manuscript introduce an initial validation of the Ultra-Processed Food Consumption Scale (UPFCS), a novel measure designed to capture UPF intake. The findings across three studies provide strong preliminary evidence for the scale\u0026rsquo;s reliability, validity, and applicability across diverse samples.\u003c/p\u003e \u003cp\u003eStudy 1 demonstrated that the UPFCS is best represented as a unidimensional construct, reflecting the frequency of ultra-processed food consumption. The scale\u0026rsquo;s high internal consistency, one dimensional loadings and satisfactory communalities indicate that the items coherently represent the intended domain of ultra-processed food consumption.\u003c/p\u003e \u003cp\u003eTogether, these findings establish the UPFCS as a statistically robust tool for measuring UPF consumption. Study 2 provided evidence of temporal stability, with a significant test\u0026ndash;retest correlation over a two-week interval; a finding rather important for both longitudinal and intervention research, as well as assessments of policy impact across time. Study 3 examined the UPFCS in relation to established diet-related constructs. As expected, higher UPF consumption was associated with greater food addiction symptoms, consistent with existing literature linking UPFs to compulsive eating, overconsumption and food addictive markers (Filgueiras et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This finding supported the convergent validity of the UPFCS, but interestingly, no significant correlations were found between UPF consumption, BMI, and adherence to Mediterranean Dieting. This may reflect the multifactorial nature of BMI and the potential for individuals to consume both healthy and ultra-processed foods simultaneously, observations of processed protein consumption that is on the rise, or potential implications for vegan and vegetarian populations that are consuming ultra-processed foods when they also fulfil a large portion of Mediterranean dieting. Importantly, adherence to a Mediterranean Diet moderated the association between UPF consumption and food addiction symptoms: the relationship was strongest among individuals with low adherence, suggesting that nutrient-dense dietary patterns may buffer against the addictive potential of UPFs. This finding aligns with historical and evolving evidence on the protective effects of Mediterranean Dieting by introducing another dimension on dietary quality and associations to psychological health (e.g., Coletro et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite its strengths, several limitations should be acknowledged. The samples were limited to UK-based participants, recruited online, and potentially restricting in the generalizability to other populations. Self-reported dietary measures are inherently subject to recall and social desirability biases. Future research should aim to replicate these findings with international samples and examine criterion validity by comparing UPFCS scores with objective dietary intake data (e.g., 24-hour recalls or biomarker-based assessments).\u003c/p\u003e \u003cp\u003eIn conclusion, the Ultra-Processed Food Consumption Scale (UPFCS) represents a significant development in dietary assessment of UPF intake. Preliminary data offers a reliable, valid and efficient tool of quantifying UPF intake. Given the global rise in ultra-processed food consumption and its documented health consequences, the UPFCS holds considerable promise for informing research, policy, and intervention strategies aimed at improving dietary health and reducing the burden of diet-related diseases.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limits\u003c/h2\u003e \u003cp\u003eA key strength is the strong internal consistency, temporal stability, and convergent validity of the UPFCS across diverse UK samples. The development with expert review and cross-cultural item appraisal further supports practical utility as a low-burden measurement tool for ultra-processed food consumption. The reliance on self-reported data and UK-based samples limit generalisability, highlighting the need for international replication.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003eWhat is already known on this subject?\u003c/h2\u003e \u003cp\u003eHigh consumption of ultra-processed foods is consistently associated with adverse physical and mental health outcomes. The NOVA classification system has become the dominant framework for defining and studying ultra-processed foods in nutritional research. However, existing methods for assessing UPF intake are often lengthy, resource-intensive, culturally specific, restricting their use in behavioural sciences and large-scale, as well as international studies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003eWhat this study adds?\u003c/h2\u003e \u003cp\u003eThis study introduces the Ultra-Processed Food Consumption Scale (UPFCS), a brief, psychometrically robust, and theoretically grounded measure of UPF intake. The findings provide initial evidence that UPF consumption, as measured by the UPFCS, is positively associated with food addiction symptoms and that adherence to a Mediterranean diet may moderate this relationship.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eDisclaimers\u003c/h2\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthical approval: Ethical approval was obtained by the host University\u0026rsquo;s Ethical Committee corresponding ethical guidelines. Application approval number: XXXX /#12194 /sub1 /Am /2025 /Feb /BLSS FAEC. Participants were presented with information sheets and consent forms. following specific instructions set in the guidelines of the British Psychological Society (BPS), where a designated consent page used checkboxes to allow participants to indicate that they have read and understood each statement and key aspects of the consent information before proceeding with the study. Consent for publication: Informed consent was obtained from all individual participants to publish the findings of this research.\u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003e Internal University Funding supported the research for the reimbursement of participants.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAuthor Contributions: All authors participated in designing the study. The first draft of the manuscript was written by the first author, and all authors edited earlier drafts. All authors reviewed and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData will be available on request from the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAmorim, A. C. L., Prado, B. G., \u0026amp; Guimar\u0026atilde;es, L. V. (2020). \u003cem\u003eA food frequency questionnaire for schoolchildren from a capital city of midwestern Brazil according to the NOVA classification system: development and reproducibility\u003c/em\u003e. Demetra: Food, Nutrition \u0026amp; Health, 15, 1+. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://link.gale.com/apps/doc/A659022947/IFME?u=anon~268b8c91\u003c/span\u003e\u003cspan address=\"https://link.gale.com/apps/doc/A659022947/IFME?u=anon~268b8c91\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u0026amp;sid=googleScholar\u0026amp;xid=cb86978b\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlanco-Rojo, R., Sandoval-Insausti, H., L\u0026oacute;pez-Garcia, E., Graciani, A., Ordov\u0026aacute;s, J. M., Banegas, J. R., \u0026hellip; Guallar-Castill\u0026oacute;n, P. (2019, November). Consumption of ultra-processed foods and mortality: a national prospective cohort in Spain. In Mayo Clinic Proceedings (94), 11, 2178\u0026ndash;2188. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.mayocp.2019.03.035\u003c/span\u003e\u003cspan address=\"10.1016/j.mayocp.2019.03.035\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBleiweiss-Sande, R., Sacheck, J. M., Chui, K., Goldberg, J. P., Bailey, C., \u0026amp; Evans, E. W. (2020). \u003cem\u003eProcessed food consumption is associated with diet quality, but not weight status, in a sample of low-income and ethnically diverse elementary school children\u003c/em\u003e. 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New York: Pearson.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUltra-Processed Food Consumption Scale (UPFCS; Mantzios, Hussain \u0026amp; Giannou, 2025)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInstructions: Select how often you consume the following items using the provided response options: 0\u0026thinsp;=\u0026thinsp;Never or less than once a month 1\u0026thinsp;=\u0026thinsp;1\u0026ndash;3 times per month 2\u0026thinsp;=\u0026thinsp;1\u0026ndash;2 times per week 3\u0026thinsp;=\u0026thinsp;3\u0026ndash;6 times per week 4\u0026thinsp;=\u0026thinsp;Daily or more\u003c/span\u003e\u003c/li\u003e\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":"eating-and-weight-disorders-studies-on-anorexia-bulimia-and-obesity","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"eawd","sideBox":"Learn more about [Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity](https://www.springer.com/journal/40519)","snPcode":"40519","submissionUrl":"https://submission.nature.com/new-submission/40519/3","title":"Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Ultra-Processed Food Consumption Scale, Ultra-Processed Foods, NOVA classification, food addiction, Mediterranean Diet","lastPublishedDoi":"10.21203/rs.3.rs-8473971/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8473971/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eHigh consumption of ultra-processed food (UPF) has been consistently linked to negative health outcomes, but existing tools for assessing UPF consumption are often lengthy, culturally specific, or psychometrically underdeveloped. The present research aimed to develop and validate the Ultra-Processed Food Consumption Scale (UPFCS); that is, a brief, psychometrically sound, and cross-culturally applicable measurement.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn Study 1 (n\u0026thinsp;=\u0026thinsp;325), exploratory factor analysis (EFA) was conducted to examine the factorial structure and internal consistency of the 30-item UPFCS. Study 2 (n\u0026thinsp;=\u0026thinsp;129) evaluated test\u0026ndash;retest reliability across a two-week interval, and Study 3 (n\u0026thinsp;=\u0026thinsp;144) assessed convergent validity by examining associations to Mediterranean Diet adherence, Body Mass Index (BMI), and food addiction, as well as testing the moderating role of Mediterranean Diet adherence.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eEFA and internal consistency supported a unidimensional structure, while test\u0026ndash;retest reliability was moderate to strong. UPFCS scores were positively associated with food addiction symptoms, but not with BMI or Mediterranean Diet adherence. Exploratory moderation analysis indicated that adherence to a Mediterranean Diet attenuated the relationship between UPF consumption and food addiction symptoms, with the effect strongest among those with low Mediterranean dietary adherence.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe UPFCS demonstrates robust psychometric properties and practical utility for assessing ultra-processed food consumption in behavioral and nutritional research.\u003c/p\u003e","manuscriptTitle":"From concept to measurement: Initial validation of the Ultra-Processed Food Consumption Scale","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-08 16:41:59","doi":"10.21203/rs.3.rs-8473971/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-24T09:50:56+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-20T13:45:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"124391519429375723049678381488841495039","date":"2026-01-07T09:28:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-05T09:23:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-05T09:14:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-30T14:03:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity","date":"2025-12-29T14:24:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"eating-and-weight-disorders-studies-on-anorexia-bulimia-and-obesity","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"eawd","sideBox":"Learn more about [Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity](https://www.springer.com/journal/40519)","snPcode":"40519","submissionUrl":"https://submission.nature.com/new-submission/40519/3","title":"Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"779fb771-6d06-4ddc-97a1-35a5b00fdd94","owner":[],"postedDate":"January 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-23T16:05:09+00:00","versionOfRecord":{"articleIdentity":"rs-8473971","link":"https://doi.org/10.1007/s40519-026-01825-9","journal":{"identity":"eating-and-weight-disorders-studies-on-anorexia-bulimia-and-obesity","isVorOnly":false,"title":"Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity"},"publishedOn":"2026-02-20 15:58:27","publishedOnDateReadable":"February 20th, 2026"},"versionCreatedAt":"2026-01-08 16:41:59","video":"","vorDoi":"10.1007/s40519-026-01825-9","vorDoiUrl":"https://doi.org/10.1007/s40519-026-01825-9","workflowStages":[]},"version":"v1","identity":"rs-8473971","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8473971","identity":"rs-8473971","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}