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Extended Cohort for E-health, Environment and DNA (EXCEED)
Extended Cohort for E-health, Environment and DNA logo
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Sample details

EXCEED is a longitudinal population-based cohort study investigating the causes of long-term health conditions in a cohort of over 10,000 individuals living in the Midlands of the United Kingdom. Since 2013, participants aged 30 - 69 have been recruited into the cohort via general practices, smoking cessation services, and community-based recruitment within Leicester City, Leicestershire and Rutland. The population of Leicester is diverse and so additional recruitment from Black, Asian and minority ethnic (BAME) communities is ongoing to improve representation of racial and ethnic minority groups. After completing baseline assessments, participants are followed-up for up to 25 years through electronic health records (EHR).

Study design
Cohort

Number of participants at first data collection

9,384 (participants)

Recruitment is ongoing

Age at first data collection

30 - 69 years (participants)

Participant year of birth

Varied (participants)

Participant sex
All

Representative sample at baseline?
No

Sample features

Ex-smokers
Racial and ethnic minorities
Record-linkage
Smokers
Dataset details
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Countries

England, United Kingdom of Great Britain and Northern Ireland

Year of first data collection

2013

Primary Institutions

University of Leicester

Links

exceed.org.uk/

Profile paper DOI

doi.org/10.1093/ije/dyz073

Funders

Medical Research Council (MRC)

NIHR Clinical Research Network (CRN) East Midlands

NIHR Leicester Biomedical Research Centre - Respiratory

National Institute for Health and Care Research (NIHR)

University of Leicester

Ongoing?
Yes

Data types collected

mentalHealthData
dataLinkage
Quantitative data collection
  • Interview – face-to-face
  • Physical or biological assessment (e.g. blood, saliva, gait, grip strength, anthropometry)
  • Self-report questionnaire – online
  • Self-report questionnaire – paper or computer assisted
Qualitative data collection
  • None
Neuroimaging data collection
  • None
Linked or secondary data
  • Healthcare data
Features

Engagement

  • Patients, service users, lived experience involvement
  • Participant or community advisory groups
  • Community engagement
  • Keywords

    Anthropometry
    Biological samples/biospecimens
    COVID-19
    Electronic health records
    Environmental factors
    Genetics
    Healthcare access and use
    Lifestyle factors
    Smoking
    Spirometry
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