Mapping Obesity-related Subtypes And Interconnected Clusters

NCT ID: NCT06960434

Last Updated: 2025-05-07

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Total Enrollment: 15 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2025-05-01
• Study Completion Date: 2025-09-01

Brief Summary

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.

This 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.

Detailed Description

Overweight and obesity are increasingly prevalent in the Netherlands. Obesity-related health issues are complex and influenced by multiple interacting variables, including personal behaviors, socioeconomic status, environmental characteristics, and health conditions. This study seeks to validate and enrich the results of an ongoing exploratory data analysis by involving experts in the interpretation of identified factor clusters related to BMI categories.

This mixed methods study includes a quantitative component (an online survey) and a qualitative component (expert panel group discussions). Experts are recruited through purposive and snowball sampling and participate in interpreting variable clusters, assessing associations, and drawing conclusions on implications for further research and practical application.

Conditions

Obesity; Overweight (BMI > 25)

Study Design

• Observational Model Type: OTHER
• Study Time Perspective: CROSS_SECTIONAL

Eligibility Criteria

Inclusion Criteria

• researchers or professionals with expertise in obesity, lifestyle, environment, psychosocial or medical factors;
• experience in data interpretation and/or public health;
• able to communicate in Dutch;
• willing to participate in the online survey and/or expert panel meeting

Exclusion Criteria

• no relevant domain expertise;
• inability to give informed consent

• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Statistics Netherlands (CBS)

UNKNOWN

Sponsor Role: collaborator

LIME Limburg Measures

UNKNOWN

Sponsor Role: collaborator

Zuyd University of Applied Sciences

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Central Contacts

Iris M Kanera, PhD

Role: CONTACT

iris.kanera@zuyd.nl

+642476766

Other Identifiers

Overweight_SHICLIME_2025

Identifier Type: -

Identifier Source: org_study_id