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Food Chain Plus Cohort (FoCus)
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Sample details

To characterise the emerging pathology of metaflammation in a comprehensive manner in a Northern Germany cohort, the Food Chain Plus (FoCus) cohort study was instigated. Data collection included multiple omics modalities, including phenomics, metabolomics, genomics, and metagenomics. In total, 1,795 individuals were analysed at baseline. Baseline data collection took place between 2011 and 2014, including 63% females and 37% males with an age range of 18 to 83 years. The median age of all participants at baseline was 52.0 years.

Study design
Cohort

Number of participants at first data collection

1,795 (participants)

Age at first data collection

18 - 83 years (participants)

Participant year of birth

Varied (participants)

Participant sex
All

Representative sample at baseline?
The population in Kiel, the capital of the federal state Schleswig-Holstein in Northern Germany, and the area within a radius of 15kms.

Sample features

Adults
Older and elderly people
Dataset details

Country

Germany

Year of first data collection

2011

Primary Institutions

Kiel University (Christian-Albrechts-Universität zu Kiel, CAU)

University Medical Center of Schleswig–Holstein in Kiel (Universitätsklinikum Schleswig-Holstein, UKSH)

Links

uksh.de/Diabetologie_Kiel/en/Research/Cohort+studies/FoCus+_+Food+Chain+Plus+Cohort.html

Funders

Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung, BMBF) now known as Federal Ministry of Research, Technology and Space (Bundesministerium für Forschung, Technologie und Raumfahrt, BMFTR)

Ongoing?
Yes

Data types collected

neuroImagingData
Quantitative data collection
  • Physical or biological assessment (e.g. blood, saliva, gait, grip strength, anthropometry)
  • Self-report questionnaire – paper or computer assisted
Qualitative data collection
  • None
Neuroimaging data collection
  • Magnetic Resonance Imaging (MRI)
Linked or secondary data
  • None
Features

Engagement

  • None
  • Keywords

    Anthropometry
    Biomarkers
    Cardiovascular health and disease
    Comorbidity
    Diabetes
    Inflammation
    Lifestyle factors
    Physical health
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