[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100589343":3},{"organization":4,"armGroups":7,"interventions":14,"overallOfficials":10,"centralContacts":19,"locations":25,"responsibleParty":43,"collaborators":10,"id":46,"slug":47,"hasResults":48,"nctId":49,"briefTitle":50,"officialTitle":51,"acronym":10,"eligibilityCriteria":52,"healthyVolunteers":53,"sex":54,"minAge":55,"maxAge":56,"enrollmentInfo":57,"targetDuration":10,"studyType":60,"phases":10,"briefSummary":61,"conditions":62,"keywords":68,"overallStatus":27,"whyStopped":10,"lastUpdateSubmitDate":74,"lastUpdatePostDateStruct":75,"startDateStruct":78,"completionDateStruct":80,"leadSponsor":82,"locationsCount":83},{"fullName":5,"class":6},"Asfendiyarov Kazakh National Medical University","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":12},"The study includes 1 cohort divided into 4 age subgroups.",null,"The study follows a multistage cluster sampling design with age and gender stratification. A total of 1 cohorts have been identified, further divided into 4 age subgroups:\n\n1. 18-29 years\n2. 30-44 years\n3. 45-59 years\n4. 60-69 years Each age group is designed to have an equal distribution of men and women, ensuring gender balance across all subgroups.",[13],"Other: Genetic: DNA analysis",[15],{"type":6,"name":16,"description":17,"armGroupLabels":18,"otherNames":10},"Genetic: DNA analysis","Investigation of telomere length (TL) and DNA methylation level analysis",[9],[20],{"name":21,"role":22,"phone":23,"phoneExt":10,"email":24},"Ildar Fakhradiyev, Ph.D","CONTACT","+7 (727) 338 7090","fakhradiyev.i@kaznmu.kz",[26],{"facility":5,"status":27,"city":28,"state":29,"zip":30,"country":29,"countryCode":31,"cosmosGeoPoint":32,"geoPoint":37,"contacts":38},"RECRUITING","Almaty","Kazakhstan","050000","KZ",{"type":33,"coordinates":34},"Point",[35,36],76.9115,43.25249,{"lat":36,"lon":35},[39,41],{"name":40,"role":22,"phone":23,"phoneExt":10,"email":24},"Ildar Fakhradiyev, PhD",{"name":40,"role":42,"phone":10,"phoneExt":10,"email":10},"PRINCIPAL_INVESTIGATOR",{"type":42,"investigatorFullName":44,"investigatorTitle":45,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"Ildar Fakhradiyev","Vice-rector","100589343","epigenetics-and-ncd-prevention-in-kazakhstan-personalized-approaches-and-biological-age-prediction-100589343",false,"NCT06953180","Epigenetics and NCD Prevention in Kazakhstan: Personalized Approaches and Biological Age Prediction","Epigenetics and Prevention of Non-communicable Diseases in Kazakhstan: a Personalized Approach and Biological Age Prediction","Inclusion Criteria:\n\n* Adults aged 18 to 69 years.\n* Residents of 17 regions of Kazakhstan.\n* Willingness to participate and provide informed consent.\n\nExclusion Criteria:\n\n* Age less than 18 years old or over 69 years old.\n* Failure to provide informed consent or incomplete participation in data collection procedures.",true,"ALL","18 Years","69 Years",{"count":58,"type":59},6720,"ESTIMATED","OBSERVATIONAL","This study aims to enhance personalized and preventive care for non-communicable diseases (NCDs) in Kazakhstan by examining epigenetic factors, predicting biological age and reproductive function using machine learning, and developing health improvement recommendations.",[63,64,65,66,67],"Cardiovascular Diseases (CVD)","Type 2 Diabetes","Chronic Respiratory Diseases","Obesity (Disorder)","Chronic Kidney Diseases",[69,70,71,72,73],"DNA methylation","precision medicine","preventive medicine","artificial intelligence","biomedical modeling","2025-07-08",{"date":76,"type":77},"2025-07-11","ACTUAL",{"date":79,"type":77},"2025-03-03",{"date":81,"type":59},"2026-12-31",{"name":5,"class":6},1]