The general population cohort of Lifelines consists of 167.729 participants, identified with a Lifelines-ID.

Lifelines participants were initially recruited through general practitioners in the three provinces in the northern part of the Netherlands: Groningen, Friesland and Drenthe¹⁾.
General practitioners (GP's) invited all their patients between 25 and 50 years old (on Terschelling 18+), resulting in ~81.500 participants at baseline.
These individuals were then asked to invite their family members (parents, partner, children, parents-in-law), resulting in an additional ~64.500 participants at baseline.
~21.500 interested individuals registered directly for baseline participation via the Lifelines website.

There were no specific inclusion criteria for Lifelines.
GP's were asked to decide which of their patients should be excluded from Lifelines, based on the following list of exclusion criteria provided by Lifelines:

• terminal illness (life expectancy < 5 years)
• severe mental illness (i.e. not fully capable to make rational decisions)
• not being able to visit the GP
• not being able to fill in the questionnaires
• not being able to understand the Dutch language

Lifelines has participants of all ages.
Children follow a special child protocol until they turn 18. Elderly participants follow the adult protocol plus some additional questions (in assessments 1A, 1B and 1C) and additional measurements (MMSE).
Since baseline, the original distribution of the three age groups (children, adults and elderly) has shifted as follows:

Lifelines has ~97,000 female participants (58%) and ~71,000 male participants (42%).
Most questionnaires and measurements are performed in both sexes.
Notable exceptions:

• ROAQ, an additional assessment on reproductive health in women
• VESP, an additional assessment on semen quality in men
• NEXT, our birth cohort with an emphasis on pregnant women (but fathers are also included)

Thus far, the *binary* gender of participants was assessed via self-report and via BRP linkage.
More recently, attention is given to *non-binary* gender within the cohort.

The vast majority of Lifelines participants is born in the Netherlands (97%) and has a Caucasian ethnicity (98%). See also the subsection on Nationality & ethnicity.

Click here to learn more about the Lifelines death rate and causes of death.

Lifelines includes many participants with a family connection to one another, including 355 twins and 5 triplets. Current and past family connections between participants are identified using:

• The Dutch citizen registration
• Self-reported information
• Genotyping (see GWAS and UGLI)

Based on BRP and self-report, the following Lifelines nuclear families can be identified:

Other family connections (e.g. grandparent-grandchild, siblings) are present in the cohort as well.

At baseline, the adult Lifelines cohort was generally representative of the adult population of the north of the Netherlands²⁾. An updated report on the representativity of the current cohort is currently in preparation.

Comprehensive factsheets were developed on a number of health-related topics covered by Lifelines:

• Asthma & COPD
• Cancer
• Diabetes
• Cardiovascular diseases
• Mental health
• Frequency of disease
• Omics data
• Geolocation linkage

In addition, some informative cohort statistics can be found here:

• Cancer statistics (prevalence, incidence, relation to smoking)
• Diabetes statistics

Subsets of participants have been selected for additional assessments according to assessment-specific criteria. This results in subcohorts that are defined by the availability of certain additional variables.
Some notable examples are:

• GWAS subcohort (15,000 genotyped participants)
• UGLI subcohort (38,000 genotyped participants)
• DEEP subcohort (1,500 participants with extensive metabolomics/microbiomics)
• DAG3 subcohort (9,500 participants with extensive metabolomics/microbiomics)

• Basic information (address, date of birth, sex, birth of children, marriage/divorce, date of death) about our participants is provided by the Dutch citizen registration
• Information about living environment (or exposome), such as air pollution or LISA-data, can be linked to individual participants via postal codes or x-y coordinates (see also: http://www.gecco.nl)
• Individual data from governmental registries (i.e. causes of death, socio-economic data) can be linked to Lifelines health-related data via Statistics Netherlands
• Individual results from pathological tests (i.e. biopsies) can be linked to Lifelines health-related data (including self-reported cancer) via PALGA and ZorgTTP
• Individual longitudinal prescription medication data from Dutch pharmacies can be linked to Lifelines health-related data (including self-reported medication) via IADB (the Pharmlines initiative)