Understanding Society collects information about participants’ social and economic circumstances, attitudes and beliefs and it also gathers information about their health.
As part of the main survey, from Wave 1 onwards participants are asked multiple questions about their general health, including a number of validated scales.
Health and biomarker data
In Wave 2 and Wave 3 adult participants received a follow-up visit from a research nurse. A range of bio-measures were collected from around 13,500 adults, which included blood pressure, weight, height, waist measurement, body fat, grip strength and lung function.
Blood samples were also taken at these visits and biomarker data is available including:
- Measures of fat in the blood (cholesterol and triglycerides)
- An indicator of diabetes (Glycated haemoglobin HbA1c)
- Measures of inflammation and the immune system– the body’s way of responding to harm (High sensitivity c-reactive protein, fibrinogen and CMV seropositivity)
- Measures of anaemia (Haemoglobin and ferritin)
- Liver and kidney function
- Hormones that build up the body – (testosterone, DHEAs, IFG-1).
Understanding Society also has omics data. Find out more about the data available and how to apply for them in the omics web area.
Proteomic panels
Proteomics is the analysis of a large set of protein molecules. Data from Understanding Society has been used to create two proteomic panels: one for proteins from the cardiometabolic panel and one for proteins in the neurology panel.
The cardiometabolic panel focuses on cardiovascular health (heart and blood vessels) and metabolic health, for example diabetes. The neurological panel focuses on proteins involved in areas such as brain development and neurodegenerative disease. Read more about the proteomic panels in the User Guide.
Epigenetic ageing algorithms (epigenetic clocks)
Epigenetic ageing
Differences between actual age and biological age may be related to life circumstances and environment. For the Understanding Society data, five epigenetic ageing algorithms have been constructed. You can read more about epigenetic ageing algorithms in the User Guide.
Ageing algorithm and proteomic panel data is available from the UK Data Service in the Nurse health assessment dataset, SN: 7251
Polygenic scores
A polygenic score is a continuous variable that reflects an individual’s propensity towards a given trait. These traits can include disease status, behaviours, and blood levels of biomolecules, among many others.
A number of polygenic score variables have been derived from the genomic dataset and are available for the first time in the Special Licence version of the Nurse Assessment dataset (SN 7587). Polygenic scores generated in Understanding Society can be used as explanatory variables in a range of analyses, including investigating the causal effect of the polygenic score trait with health or social outcomes. However, any findings from analyses that use polygenic scores as explanatory variables require careful interpretation. Please consult the User Guide for information on using these data appropriately.
Polygenic scores data are available from the UK Data Service in the Special Licence version of the Nurse Health Assessment dataset, SN: 7587.
Future data
In Wave 16 (currently in the field 2024-2026) we will be collecting further biological data from our participants. This will include blood samples, blood pressure, weight, height and waist measurements. These data will be released towards the end of 2026. To stay updated, please subscribe to our newsletter.