Ignite Creation Date:
2025-12-24 @ 9:24 PM
Ignite Modification Date:
2025-12-28 @ 4:33 AM
Study NCT ID:
NCT06775132
Status:
RECRUITING
Last Update Posted:
2025-05-21
First Post:
2025-01-01
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Associations Between Dietary Intake and Cardiometabolic and Gut Microbiota Outcomes
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D012871', 'term': 'Skin Diseases'}, {'id': 'D007319', 'term': 'Sleep Initiation and Maintenance Disorders'}], 'ancestors': [{'id': 'D017437', 'term': 'Skin and Connective Tissue Diseases'}, {'id': 'D020919', 'term': 'Sleep Disorders, Intrinsic'}, {'id': 'D020920', 'term': 'Dyssomnias'}, {'id': 'D012893', 'term': 'Sleep Wake Disorders'}, {'id': 'D009422', 'term': 'Nervous System Diseases'}, {'id': 'D001523', 'term': 'Mental Disorders'}]}}, 'protocolSection': {'designModule': {'bioSpec': {'retention': 'SAMPLES_WITH_DNA', 'description': 'plasma, serum, stool'}, 'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'CROSS_SECTIONAL', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 240}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2025-02-03', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-05', 'completionDateStruct': {'date': '2025-12-30', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-05-19', 'studyFirstSubmitDate': '2025-01-01', 'studyFirstSubmitQcDate': '2025-01-09', 'lastUpdatePostDateStruct': {'date': '2025-05-21', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2025-01-14', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2025-09-30', 'type': 'ESTIMATED'}}, 'outcomesModule': {'otherOutcomes': [{'measure': 'Anthopometric measurements', 'timeFrame': 'Day 1', 'description': 'Height, weight, and waist circumference will be measured for each subject'}], 'primaryOutcomes': [{'measure': 'Dietary intake', 'timeFrame': 'Day 7', 'description': 'Use a 3-day food record to document dietary intake'}, {'measure': 'Blood pressure', 'timeFrame': 'Day 1', 'description': 'Systolic and diastolic blood pressure (in mmHg) will be measured by a blood pressure monitor.'}, {'measure': 'Blood lipid lipoprotein profile', 'timeFrame': 'Day 1', 'description': 'Total cholesterol, LDL, HDL, and triglyceride concentration in the blood will be measured'}, {'measure': 'Fasting blood glucose', 'timeFrame': 'Day 1', 'description': 'Glucose concentration in the blood will be measured'}, {'measure': 'Endothelial Progenitor Cell Count', 'timeFrame': 'Day 1', 'description': 'Endothelial functions are determined by the percentage of endothelial progenitor cells (CD34+/KDR+) expression in peripheral blood mononuclear cells'}, {'measure': 'Fecal short chain fatty acid (SCFA) concentration', 'timeFrame': 'Day 1', 'description': 'SCFA concentration in the blood will be measured'}, {'measure': 'Trimethylamine N-oxide (TMAO)', 'timeFrame': 'Day 1', 'description': 'Trimethylamine N-oxide (TMAO) concentration in the blood will be measured'}, {'measure': 'Fecal bile acids', 'timeFrame': 'Day 1', 'description': 'Bile acids concentration will be determined from fecal samples of the subjects'}, {'measure': 'Fecal zonulin', 'timeFrame': 'Day 1', 'description': 'Zonulin concentration will be determined from fecal samples of the subjects'}, {'measure': 'Fecal calprotectin', 'timeFrame': 'Day 1', 'description': 'Calprotectin concentration will be determined from fecal samples of the subjects'}, {'measure': 'Estimated Glomerular Filtration Rate (eGFR)', 'timeFrame': 'Day 1', 'description': 'The estimated Glomerular Filtration Rate (eGFR) of the subjects will be measured from the blood'}], 'secondaryOutcomes': [{'measure': 'Sleep quality-Pittsburgh Sleep Quality Index Questionnaire', 'timeFrame': 'Day 1', 'description': 'Pittsburgh Sleep Quality Index Questionnaire (PSQI) will be used to assess the sleep quality. Overall score ranging from 0 to 21 points, where lower scores denote a healthier sleep quality.'}, {'measure': 'Cognitive function', 'timeFrame': 'Day 1', 'description': 'Use Montreal Cognitive Assessment (MoCA) questionnaires to assess cognitive function. A score of 26 or above (out of 30) is generally considered normal, though adjustments may be made for educational level.'}, {'measure': 'Skin carotenoid concentration', 'timeFrame': 'Day 1', 'description': 'Skin carotenoid concentration: This can be measured by Resonance Raman Spectroscopy, the unit is skin carotenoid score, a higher score means optimal, lower score means poor condition of skin carotenoids.'}, {'measure': 'Macular Pigment Optical Density (MPOD)', 'timeFrame': 'Day 1', 'description': 'Macular Pigment Optical Density (MPOD): A measurement of macular pigment of the eye using a heterochromatic flicker photometry device. The measurements are in arbitrary units.'}, {'measure': 'The Global Physical Activity Questionnaire (GPAQ)', 'timeFrame': 'Day 1', 'description': 'The Global Physical Activity Questionnaire (GPAQ) will be used to assess physical activity levels in three areas: work, transport, and leisure. It measures activity in terms of frequency, duration, and intensity, generating a score in metabolic equivalents (METs). Higher MET values indicate higher levels of physical activity.'}, {'measure': 'The Perceived Stress Scale (PSS-10)', 'timeFrame': 'Day 1', 'description': 'The Perceived Stress Scale (PSS-10) will be used to assess the level of perceived stress over the past month. The scale consists of 10 items scored on a 5-point Likert scale (0 = never to 4 = very often), with a total score ranging from 0 to 40. Higher scores indicate greater perceived stress.'}, {'measure': 'The Beck Anxiety Inventory (BAI)', 'timeFrame': 'Day 1', 'description': 'The Beck Anxiety Inventory (BAI) will be used to measure the severity of anxiety symptoms. It consists of 21 questions scored on a 4-point Likert scale (0 = not at all to 3 = severely). The total score ranges from 0 to 63, with higher scores reflecting more severe anxiety symptoms.'}, {'measure': 'The Beck Depression Inventory-II (BDI-II)', 'timeFrame': 'Day 1', 'description': 'The Beck Depression Inventory-II (BDI-II) will be used to assess the severity of depressive symptoms over the past two weeks. It contains 21 questions scored on a 4-point scale (0 = no symptoms to 3 = severe symptoms). Total scores range from 0 to 63, with higher scores indicating more severe depression.'}, {'measure': 'Visual acuity', 'timeFrame': 'Day 1', 'description': 'Participants will read out letters on a ETDRS LogMAR chart at a fixed distance where letters becomes smaller as it goes down the chart. Tests results will be recorded in number of letters read, where the more letters the better the outcome.'}, {'measure': 'Visual function questionnaire 25', 'timeFrame': 'Day 1', 'description': 'A questionnaire to for participants to self-evaluate their perception of their current eye health based on general vision, ocular pain, near activities, distance activities, vision specific functions, driving, color vision and peripheral vision. The best possible score is 100 and worst possible score is 0.'}, {'measure': 'Skin advanced glycation end products (AGE) levels', 'timeFrame': 'Day 1', 'description': 'Skin advanced glycation end products (AGE) levels: Measurement of skin advanced glycation end products level using a skin autofluorescence device, where participants wlll be instructed to place their forearm over the device and a light will be shone and a reading can be captured by detecting fluorescence. The results will be presented as arbitrary units.'}]}, 'oversightModule': {'isUsExport': False, 'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Endothelial progenitor cells', 'Gut microbiota', 'Cardiovascular diseases risk factors', 'MoCA', 'Advanced glycation end products'], 'conditions': ['Cardiometabolic Risk Factors', 'Gut -Microbiota', 'Skin Condition', 'Cognitive Ability, General', 'Sleep Quality']}, 'descriptionModule': {'briefSummary': 'This cross-sectional study aims to investigate the associations between dietary intake, cardiometabolic health markers, and gut microbiota composition in Singapore adults.', 'detailedDescription': 'Diet plays a crucial role in maintaining overall health, and changes in dietary patterns are increasingly recognized as major contributors to chronic disease development. Inadequate dietary intake and poor diet quality have been linked to increased risks of cardiometabolic diseases and disruptions in gut microbiota composition. However, most studies investigating these associations have been conducted on Western populations, and there is a lack of research focusing on Asian populations. Given the genetic, metabolic, and dietary differences between Western and Asian populations, examining these associations in an Asian population is essential for a deeper understanding of population-specific risk factors and health outcomes. Therefore, there is an urgent need to assess the associations between dietary intake, cardiometabolic health, and gut microbiota composition in Asian population.\n\nThis cross-sectional study aims to investigate the associations between dietary intake, cardiometabolic health markers, and gut microbiota composition in Singapore adults.\n\nFindings from this study will offer valuable insights into the relationship between diet, cardiometabolic health, and the gut microbiota in this population. In addition, this research may identify specific dietary patterns or nutrients that offer greater benefit for cardiometabolic and gut health. In turn, these findings can contribute to the improvement of current dietary guidelines aimed at promoting better cardiometabolic and gut microbiota outcomes for the broader Singaporean population.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '80 Years', 'minimumAge': '21 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Singapore adults', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n1. Able to give informed consent\n2. Adults 21-80 years old\n3. English-literate\n4. Have venous access sufficient to allow for blood sampling as per the protocol\n5. No drastic change of diet for the past 1 year\n6. If taking medication, has been consistently taking antihypertensive/cholesterol-lowering/type-2 diabetic medication for more than 5 years prior to starting the study.\n\nExclusion Criteria:\n\n1. Taking dietary supplements and fermented foods, which may impact the gut microbiota (e.g. antibiotics, prebiotics, probiotics, yogurt, kimchi) 2 months before starting the 1st study visit only.\n2. Taking dietary supplements or medications, which may impact sleep outcomes (e.g. Nutritional Shakes (e.g. Ensure), tryptophan, 5-hydroxytryptophan or melatonin supplementations) 1 month before starting the study.\n3. Taking dietary supplements which may impact the eye outcomes (e.g. Vitamin A, vitamin A-containing multivitamin) 2 months before starting the study.'}, 'identificationModule': {'nctId': 'NCT06775132', 'briefTitle': 'Associations Between Dietary Intake and Cardiometabolic and Gut Microbiota Outcomes', 'organization': {'class': 'OTHER', 'fullName': 'National University of Singapore'}, 'officialTitle': 'Associations Between Dietary Intake and Cardiometabolic and Gut Microbiota Outcomes in Singapore Adults', 'orgStudyIdInfo': {'id': 'S27'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Younger population', 'description': 'Age 21-64'}, {'label': 'Middle-aged and older population', 'description': 'Age 65-80'}]}, 'contactsLocationsModule': {'locations': [{'zip': '117546', 'city': 'Singapore', 'state': 'Singapore', 'status': 'RECRUITING', 'country': 'Singapore', 'contacts': [{'name': 'Yueying YAO', 'role': 'CONTACT', 'email': 'yueying.yao@u.nus.edu', 'phone': '+65 83136733'}], 'facility': 'National University of Singapore', 'geoPoint': {'lat': 1.28967, 'lon': 103.85007}}], 'centralContacts': [{'name': 'Yao Yueying', 'role': 'CONTACT', 'email': 'yueying.yao@u.nus.edu', 'phone': '+65 83136733'}, {'name': 'Jung Eun Kim, PhD, RD', 'role': 'CONTACT', 'email': 'fstkje@nus.edu.sg'}], 'overallOfficials': [{'name': 'Jung Eun Kim', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Department of Food Science and Technology, National University of Singapore'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'National University of Singapore', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Assistant Professor', 'investigatorFullName': 'Jung Eun Kim', 'investigatorAffiliation': 'National University of Singapore'}}}}