[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"leadSponsorName\":\"Zuyd University of Applied Sciences\",\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:":46},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,1,0,[8],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":15,"eligibilityCriteria":16,"healthyVolunteers":17,"sex":18,"minAge":4,"maxAge":4,"enrollmentInfo":19,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":23,"conditions":24,"keywords":27,"overallStatus":34,"whyStopped":4,"lastUpdateSubmitDate":35,"lastUpdatePostDateStruct":36,"startDateStruct":39,"completionDateStruct":41,"leadSponsor":43,"locationsCount":4},"100589901","mapping-obesity-related-subtypes-and-interconnected-clusters-100589901",false,"NCT06960434","Mapping Obesity-related Subtypes And Interconnected Clusters","Systemic Interpretation of Personal and Environmental Characteristics in Overweight and Obesity: From Data Patterns to Practical Interventions","MOSAIC","Inclusion Criteria:\n\n* researchers or professionals with expertise in obesity, lifestyle, environment, psychosocial or medical factors;\n* experience in data interpretation and\u002For public health;\n* able to communicate in Dutch;\n* willing to participate in the online survey and\u002For expert panel meeting\n\nExclusion Criteria:\n\n* no relevant domain expertise;\n* inability to give informed consent",true,"ALL",{"count":20,"type":21},15,"ESTIMATED","OBSERVATIONAL","In the Netherlands, about half of all adults are currently living with overweight. This number is expected to rise to as much as 64% by the year 2050, especially among younger adults aged 18 to 44. Overweight and obesity increase the risk of chronic conditions such as heart disease, diabetes, and joint problems. However, there is no single cause behind these issues. Instead, they result from a complex combination of factors - including nutrition, physical activity, sleep, stress, income, environment, and even air quality. These factors often influence each other and vary from person to person.\n\nThis study aims to better understand these patterns and connections. By analyzing large sets of data, researchers are identifying different subtypes of people with overweight or obesity. These subtypes reflect groups of individuals who share similar personal, lifestyle, and environmental characteristics. Understanding these differences makes it possible to develop more personalized lifestyle advice and support. That way, care and prevention efforts can be better tailored to what people actually need and what works best for them in practice. Experts from various fields are helping interpret the results, so that scientific insights can be translated into practical solutions for individuals, communities, and healthcare settings.",[25,26],"Obesity","Overweight (BMI > 25)",[28,29,30,31,32,33],"overweight","obesity","prevention","lifestyle","data-driven","clusters","NOT_YET_RECRUITING","2025-04-28",{"date":37,"type":38},"2025-05-07","ACTUAL",{"date":40,"type":21},"2025-05-01",{"date":42,"type":21},"2025-09-01",{"name":44,"class":45},"Zuyd University of Applied Sciences","OTHER",""]