[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100609335":3},{"organization":4,"outcomesModule":7,"designInfo":89,"detailedDescription":94,"studyPopulation":94,"armGroups":99,"interventions":117,"overallOfficials":126,"centralContacts":131,"locations":139,"responsibleParty":155,"collaborators":94,"id":157,"slug":158,"hasResults":159,"nctId":160,"briefTitle":161,"officialTitle":162,"acronym":94,"eligibilityCriteria":163,"healthyVolunteers":164,"sex":165,"minAge":166,"maxAge":167,"enrollmentInfo":168,"targetDuration":94,"studyType":171,"phases":172,"briefSummary":174,"conditions":175,"keywords":94,"overallStatus":142,"whyStopped":94,"lastUpdateSubmitDate":178,"lastUpdatePostDateStruct":179,"startDateStruct":182,"completionDateStruct":184,"leadSponsor":186,"locationsCount":187},{"fullName":5,"class":6},"Göteborg University","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":30,"otherOutcomes":66},[9,13,17,21,24,27],{"measure":10,"description":11,"timeFrame":12},"Self-reported appetite","Appetite ratings (hunger, fullness, and desire to eat) will be assessed using separate 100-mm Visual Analogue Scales (VAS), anchored with \"not at all\" (0 mm) and \"extremely\" (100 mm). Higher scores indicate greater perceived intensity.","Baseline to 8 hours after test meal",{"measure":14,"description":15,"timeFrame":16},"Energy intake","Energy intake estimated by nutrient calculation of leftover food at the ad libitum lunch meal","4 hours after test meal",{"measure":18,"description":19,"timeFrame":20},"Gastrointestinal hormones - incretins","Difference between groups in incretins GIP and GLP-1 in response to meal","Baseline to 4 hours after test meal",{"measure":22,"description":23,"timeFrame":20},"Gastrointestinal hormones - cholecystokinin","Difference between groups in cholecystokinin in response to meal",{"measure":25,"description":26,"timeFrame":20},"Gastrointestinal hormones - peptide YY","Difference between groups in peptide YY (PYY) in response to meal",{"measure":28,"description":29,"timeFrame":20},"Gastrointestinal hormones - ghrelin","Difference between groups in ghrelin in response to meal",[31,35,38,41,44,47,50,54,57,60,63],{"measure":32,"description":33,"timeFrame":34},"Eating rate","Time it takes to eat the study meal until satisfied","Baseline til end of study meal",{"measure":36,"description":37,"timeFrame":20},"Glucose postprandial","Difference between groups in postprandial glucose in response to meal.",{"measure":39,"description":40,"timeFrame":20},"Insulin postprandial","Difference between groups in postprandial insulin in response to meal.",{"measure":42,"description":43,"timeFrame":20},"Lipid metabolism","Difference between groups in postprandial lipid metabolism in response to meal.",{"measure":45,"description":46,"timeFrame":20},"Metabolome","Differences between groups in metabolome (plasma) measured using metabolomics in response to meals.",{"measure":48,"description":49,"timeFrame":20},"Proteome","Differences between groups in proteome (plasma) measured using proteomics in response to meals.",{"measure":51,"description":52,"timeFrame":53},"Self-reported prospective energy intake","Self-reported prospective energy intake during the remainder of the day","From 30 min until midnight or bedtime (which ever comes first)",{"measure":55,"description":56,"timeFrame":20},"Inflammatory markers in blood - cytokines","Differences between groups in immunological responses (cytokines) in response to meal.",{"measure":58,"description":59,"timeFrame":20},"Inflammatory markers in blood - lipopolysaccharides","Differences between groups in immunological responses (lipopolysaccharides) in response to meal.",{"measure":61,"description":62,"timeFrame":20},"Inflammatory markers in blood - GlycA","Differences between groups in immunological responses (GlycA) in response to meal.",{"measure":64,"description":65,"timeFrame":20},"Lipid profile","Differences between groups in lipid profile (plasma) measured using lipidomics in response to meals.",[67,71,74,77,80,83,86],{"measure":68,"description":69,"timeFrame":70},"Determinants of energy intake - proteome","Correlation between baseline proteome measured using proteomics and the primary outcome energy intake","Baseline",{"measure":72,"description":73,"timeFrame":70},"Determinants of energy intake - metabolome","Correlation between baseline metabolome measured using metabolomics and primary outcome energy intake",{"measure":75,"description":76,"timeFrame":70},"Determinants of energy intake - body composition","Correlation between baseline body composition (fat percentage and fat free mass percentage) measured using Bioelectrical impedance analysis (BIA) and primary outcome energy intake",{"measure":78,"description":79,"timeFrame":70},"Determinants of energy intake - metabolic markers","Correlation between baseline metabolic markers, fasting plasma glucose, insulin, and triglycerides measured via standard clinical chemistry methods, and primary outcome energy intake",{"measure":81,"description":82,"timeFrame":70},"Determinants of energy intake - physical activity","Correlation between baseline self-reported physical activity and primary outcome energy intake",{"measure":84,"description":85,"timeFrame":70},"Determinants of energy intake - diet","Correlation between baseline diet (macro- and micronutrient intake, dietary patterns, food group intake) estimated from a 4-day dietary record and primary outcome energy intake",{"measure":87,"description":88,"timeFrame":70},"Determinants of energy intake - microbiome","Correlation between baseline gut microbiome composition-assessed using metagenomic shotgun sequencing and 16S rRNA analysis-and the primary outcome of energy intake.",{"allocation":90,"interventionModel":91,"interventionModelDescription":92,"primaryPurpose":93,"observationalModel":94,"timePerspective":94,"maskingInfo":95},"RANDOMIZED","CROSSOVER","Factorial assignment 2X2 factorial","PREVENTION",null,{"masking":96,"maskingDescription":94,"whoMasked":97},"SINGLE",[98],"PARTICIPANT",[100,105,109,113],{"label":101,"type":102,"description":101,"interventionNames":103},"Meal high in energy density, high in ultra-processed food","EXPERIMENTAL",[104],"Other: Meal high in energy density, high in ultra-processed food",{"label":106,"type":102,"description":106,"interventionNames":107},"Meal high in energy density, low in ultra-processed food",[108],"Other: Meal high in energy density, low in ultra-processed food",{"label":110,"type":102,"description":110,"interventionNames":111},"Meal low in energy density, high in ultra-processed food",[112],"Other: Meal low in energy density, high in ultra-processed food",{"label":114,"type":102,"description":114,"interventionNames":115},"Meal low in energy density, low in ultra-processed food",[116],"Other: Meal low in energy density, low in ultra-processed food",[118,120,122,124],{"type":6,"name":101,"description":101,"armGroupLabels":119,"otherNames":94},[101],{"type":6,"name":106,"description":106,"armGroupLabels":121,"otherNames":94},[106],{"type":6,"name":110,"description":110,"armGroupLabels":123,"otherNames":94},[110],{"type":6,"name":114,"description":114,"armGroupLabels":125,"otherNames":94},[114],[127],{"name":128,"affiliation":129,"role":130},"Therese Karlsson, PhD","University of Gothenburg, Institute of medicine","PRINCIPAL_INVESTIGATOR",[132,136],{"name":128,"role":133,"phone":134,"phoneExt":94,"email":135},"CONTACT","+46704089150","therese.karlsson@gu.se",{"name":137,"role":133,"phone":94,"phoneExt":94,"email":138},"Linnea Bärebring, PhD","linnea.barebring@gu.se",[140],{"facility":141,"status":142,"city":143,"state":94,"zip":144,"country":145,"countryCode":146,"cosmosGeoPoint":147,"geoPoint":152,"contacts":153},"Department of internal medicine and clinical nutrition, University olf Gothenburg","RECRUITING","Gothenburg","40530","Sweden","SE",{"type":148,"coordinates":149},"Point",[150,151],11.96679,57.70716,{"lat":151,"lon":150},[154],{"name":128,"role":133,"phone":134,"phoneExt":94,"email":94},{"type":156,"investigatorFullName":94,"investigatorTitle":94,"investigatorAffiliation":94,"oldNameTitle":94,"oldOrganization":94},"SPONSOR","100609335","metabolic-effects-of-short-term-ultra-processed-food-intake-mest-upf-100609335",false,"NCT07213245","Metabolic Effects of Short-term Ultra-processed Food Intake (MEST-UPF)","Metabolic Effects of Short-term Ultra-processed Food Intake (MEST-UPF): a Randomized Controlled Trial","Inclusion Criteria:\n\n* Body mass index (BMI) 18.5-30 kg\u002Fm2\n* Fasting glucose \\\u003C 6.1 mmol\u002Fl\n* Hb \\>110 g\u002FL\n* Weight stability the last 3 months +\u002F-5%\n\nExclusion Criteria:\n\n* Food allergies, intolerances or preferences preventing consumption of any products included in the study.\n* Unable to sufficiently understand written and spoken Swedish or English to provide written consent and understand information and instructions from the study personal.\n* Pregnant, lactating or planning a pregnancy during the study period.\n* Blood donation or participation in a clinical study with blood sampling within 30 days prior to screening visit and throughout the study.\n* History of gastrointestinal conditions or major gastrointestinal surgery (Inflammatory bowel disease, Crohn's disease, malabsorption, colostomy, bowel resection, gastric bypass surgery etc.).\n* Type 1 diabetes or type 2 diabetes.\n* Thyroid disorder.\n* Current smoking, vaping.\n* Following any weight reduction program or having followed one during the last 6 months prior to screening.\n* Not habitually eating breakfast (\\\u003C5 times\u002Fweek).\n* Restrained eating based on the three-factor eating questionnaire.",true,"ALL","18 Years","50 Years",{"count":169,"type":170},24,"ESTIMATED","INTERVENTIONAL",[173],"NA","The overall aim of this project is to study the effects of short-term high ultra-processed food intake, compared to nutrient- and energy density matched low ultra-processed food (UPF) intake, on energy intake and appetite.\n\nA total of 24 men and women who meet all inclusion criteria and none of the exclusion criteria will be invited to participate. A randomized 2\\*2 factorial four-way crossover study will be conducted at the Department of Internal medicine and Clinical Nutrition at the University of Gothenburg, comparing a high-UPF meal to a low-UPF meal also with high and\u002For low energy density. A supervised breakfast meal will be served, and postprandial blood samples and appetite measures will be collected continuously up to 4 hours after the breakfast meal. Subsequently, an ad libitum lunch meal will be served, and energy intake will be recorded.",[176,177],"Appetite","Obesity and Obesity-related Medical Conditions","2026-09-08",{"date":180,"type":181},"2026-09-09","ACTUAL",{"date":183,"type":181},"2025-12-01",{"date":185,"type":170},"2026-12-31",{"name":5,"class":6},1]