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GCAT Genomes for Life
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Sample details

GCAT aims to integrate and assess the role of genomic, epigenomic, environmental and lifestyle factors in the development of major chronic diseases in Catalonia, a north-east region of Spain. Questionnaires, blood samples, anthropometry measurements, and clinical history are collected from participants. Between 2014 to 2017, around 20,000 adults aged 40 to 65 years were recruited and completed baseline assessments. Participants are passively followed up via Electronic Health Records (EHR), with data available since 2012. Participants completed a follow-up assessment between 2018 and 2020. Additionally, sub-samples have participated in sub-studies, such as GCAT_Lifestyle, GCAT_Family Health, and GCAT_Environment and Health. The study plans to follow participants for 20 years after recruitment.

Study design
Cohort

Number of participants at first data collection

19,209 (participants)

Age at first data collection

40 - 65 years (participants)

Participant year of birth

Varied (participants)

Participant sex
All

Representative sample at baseline?
No

Sample features

Adults
Middle-aged people
Dataset details

Country

Spain

Year of first data collection

2012 (EHR linkage)

2014

Primary Institutions

Blood and Tissue Bank of Catalonia (BST)

Germans Trias i Pujol Research Institute (IGTP)

Government of Catalonia (Generalitat de Catalunya)

Links

gcatbiobank.org/en_index/

maelstrom-research.org/study/gcat

Funders

Government of Catalonia (Generalitat de Catalunya)

Ongoing?
Yes

Data types collected

mentalHealthData
dataLinkage
Quantitative data collection
  • Physical or biological assessment (e.g. blood, saliva, gait, grip strength, anthropometry)
  • Secondary data
  • Self-report questionnaire – online
Qualitative data collection
  • None
Neuroimaging data collection
  • None
Linked or secondary data
  • Geographic, spatial & environmental data
  • Healthcare data
  • Mortality data
Features

Engagement

  • Community engagement
  • Keywords

    Alcohol use
    Anthropometry
    Biological samples/biospecimens
    COVID-19
    Diet and nutrition
    Electronic health records
    Environmental exposures
    Lifestyle
    Physical activity and exercise
    Smoking
    Sociodemographics
    Work and employment
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