Understanding Society, (UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex and the survey research organisations Verian Group (formerly Kantar Public) and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.

This release combines fourteen waves of Understanding Society data with harmonised data from all eighteen waves of the BHPS. As multi-topic studies, the purpose of Understanding Society and BHPS is to understand short- and long-term effects of social and economic change in the UK at the household and individual levels. The study has a strong emphasis on domains of family and social ties, employment, education, financial resources, and health. Understanding Society is an annual survey of each adult member of a nationally representative sample. The same individuals are re-interviewed in each wave approximately 12 months apart. When individuals move they are followed within the UK and anyone joining their households are also interviewed as long as they are living with them. The study has five sample components: the general population sample; a boost sample of ethnic minority group members; an immigrant and ethnic minority boost sample (from wave 6); participants from the BHPS; and a second general population boost sample added at this wave. In addition, there is the Understanding Society Innovation Panel (which is a separate standalone survey (see SN 6849)). The fieldwork period is for 24 months. Data collection uses computer assisted personal interviewing (CAPI) and web interviews (from wave 7), and includes a telephone mop-up. From March 2020 (the end of wave 10 and the 2nd year of wave 11), due to the coronavirus pandemic, face-to-face interviews were suspended, and the survey was conducted by web and telephone only, but otherwise has continued as before. Face-to-face interviewing was resumed from April 2022. One person completes the household questionnaire. Each person aged 16 is invited to complete the individual adult interview and self-completed questionnaire. Parents are asked questions about their children under 10 years old. Youths aged 10 to 15 are asked to respond to a self-completion questionnaire. For the general and BHPS samples biomarker, genetic and epigenetic data are also available. The biomarker data, and summary genetics and epigenetic scores, are available via UKDS (see SN 7251); detailed genetics and epigenetics data are available by application (see below). In 2020-21 an additional frequent web survey was separately issued to sample members to capture data on the rapid changes in people’s lives due to the COVID-19 pandemic (see SN 8644). Participants are asked consent to link their data to wide-ranging administrative data sets (see below).

Further information may be found on the Understanding Society Main stage webpage and links to publications based on the study can be found on the Understanding Society Latest Research webpage.

Co-funders

In addition to the Economic and Social Research Council, co-funders for the study included the Department of Work and Pensions, the Department for Education, the Department for Transport, the Department of Culture, Media and Sport, the Department for Community and Local Government, the Department of Health, the Scottish Government, the Welsh Assembly Government, the Northern Ireland Executive, the Department of Environment and Rural Affairs, and the Food Standards Agency.

End User Licence, Special Licence and Secure Access versions:

There are three versions of the main Understanding Society data with different access conditions. One is available under the standard End User Licence (EUL) agreement (this study), one is a Special Licence (SL) version (SN 6931) and the third is a Secure Access version (SN 6676). The SL version contains month as well as year of birth variables, more detailed country and occupation coding for a number of variables, various income variables that have not been top-coded, and other potentially sensitive variables (see 6931_eul_vs_sl_variable_differences document available with the SL version for full details of the differences). The Secure Access version, in addition to containing all the variables in the SL version, also contains day of birth as well as Grid Reference geographical variables. Users are advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements. The SL and Secure Access versions of the data have more restrictive access conditions and prospective users of those versions should visit the catalogue entries for SN 6931 and SN 6676 respectively for further information.

Low- and Medium-level geographical identifiers are also available subject to SL access conditions; see SNs 6666, 6668-6675, 7453-4, 7629-30, 7245, 7248-9 and 9169-9170. Schools data are available subject to SL access conditions in SN 7182. Higher Education establishments for Wave 5 are available subject to SL access conditions in SN 8578. Interviewer Characteristics data, also subject to SL access conditions is available in SN 8579. In addition, a fine detail geographic dataset (SN 6676) is available under more restrictive Secure Access conditions that contains National Grid postcode grid references (at 1m resolution) for the unit postcode of each household surveyed, derived from ONS Postcode Directories (ONSPD). For details on how to make an application for Secure Access dataset, please see the SN 6676 catalogue record.

How to access genetic and/or bio-medical sample data from Understanding Society:

Information on how to access genetics and epigenetics data directly from the study team is available on the Understanding Society Accessing data webpage.

Linked administrative data

Linked Understanding Society / administrative data are available on a number of different platforms. See the Understanding Society Data linkage webpage for details of those currently available and how they can be accessed.

Latest edition information

For the 19th edition (November 2024) Wave 14 data has been added. Other minor changes and corrections have also been made to Waves 1-13. Please refer to the revisions document for full details.

m_hhresp and n_hhresp files updated, December 2024

In the previous release (19th edition, November 2024), there was an issue with household income estimates in m_hhresp and n_hhresp where a household resides in a new local authority (approx. 300 households in wave 14). The issue has been corrected and imputation models re-estimated and imputed values updated for the full sample. Imputed values will therefore change compared to the versions in the original release. The variable affected is n_ctband_dv.

Suitable data analysis software

These data are provided by the depositor in Stata format. Users are strongly advised to analyse them in Stata. Transfer to other formats may result in unforeseen issues. Stata SE or MP software is needed to analyse the larger files, which contain over 2,047 variables.

Further information may be found on the FSA's Food and You Survey webpage.

Food and You 2, 2020-2025
The Food and You 2 survey was conducted using a push-to-web methodology and explored participants’ food-related knowledge, behaviours and attitudes. Push-to-web is a quantitative data collection method in which participants are contacted using an offline means of contact and asked to complete an online survey. In this survey, participants were contacted by letter, with those who chose not to complete the online survey, after the initial reminder, subsequently sent a postal version.

Trends data
The second Food and You 2 trends data provides an overview of key trends between Wave 1 (July 2020 to October 2020) and Wave 8 (October 2023 to January 2024).

A set of additional variables for Food and You 2, covering food allergies and related demographics is available under SN 8815, subject to more restrictive Special Licence access conditions.

Latest edition information
For the 11th edition (June 2025), data and documentation for Wave 9 were added to the study and the trends dataset was updated to include Waves 1-8.

This data collections consists of data and documentation produced to examine the spatial and social differences in people’s lack of access to adequate energy and transport services in the United Kingdom (UK). The work responds to the need for developing a differentiated understanding of both the drivers and expressions of this ‘double energy vulnerability’, while seeking to integrate and analyse relevant information from all four UK nations. Using a variety of statistically representative census and survey datasets, the project developed a series of multi-dimensional indices to map transport- and energy-related injustices. This was followed by a cluster analysis to examine broad-level geographical patterns, and a Geographically Weighted Regression model to explore the spatial variation of vulnerabilities related to contingencies such as income, ethnicity and housing. The work corroborates the results of previous qualitative studies, and research within selected UK nations, while revealing a number of unexpected territorial clusters and underpinnings of infrastructural injustice.

The Opinions and Lifestyle Survey, Well-Being Module, April-May 2015: Unrestricted Access Teaching Dataset is based on the Opinions and Lifestyle Survey, Well-Being Module, January, February, April and May, 2015 (available from UK Data Archive under SN 7815) and constitutes real data which are used by government, business and other organisations. The teaching dataset is a subset which has been subjected to certain simplifications and additions for the purpose of learning and teaching.

The main differences are:

• the teaching dataset contains data from April-May 2015 only;
  
• the number of variables has been reduced;
  
• a reduced user guide with codebook is provided;
  
• some variables have been recoded due to concerns about statistical disclosure;

Super Output Areas are a geographic hierarchy designed to improve the reporting of small-area statistics.

The Lower Super Output Areas and Data Zones list contains 42,619 areas of the following constituent geographies:

• 32,844 Lower Super Output Areas in England
• 890 Super Output Areas in Northern Ireland
• 6,976 Data Zones in Scotland
• 1,909 Lower Super Output Areas in Wales

Please visit ONS Beginner's Guide to UK Geography for more info.

The boundaries are available as either extent of the realm (usually this is the Mean Low Water mark but in some cases boundaries extend beyond this to include off shore islands) or

clipped to the coastline (Mean High Water mark).

Understanding Society (UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex, and the survey research organisations Verian Group and NatCen. It builds on and incorporates the British Household Panel Survey (BHPS), which began in 1991.

Secure Access Dataset:
The Understanding Society: Linked Education Administrative Datasets (National Pupil Database), England, 1995-2018: Secure Access study contains nine files extracted from the National Pupil Database (NPD) for England. These can be linked (within the Secure Access service) to Understanding Society participants using the cross-wave personal identifier (variable pidp). The NPD files include information on pupil background, attainment, school absences and exclusions for all individuals with a valid consent to education linkage collected in Waves 1 and 4 of Understanding Society. This includes consents collected from parents of children aged 4-15 and of young adults aged 16+ and born in 1981 or later. The included files cover Pupil Level Annual School Census (PLASC) data on pupil background; pupil attainment data for the Early Years Foundation Stage Profile (EYFSP) (age 5) and Key Stages (KS) 1 (age 7), KS2 (age 11), KS3 (age 14), KS4 (age 16) and KS5 (ages 17-18); and absences and exclusions (ages 4-18). See documentation for further details.

Related UK Data Archive studies:
The equivalent study to this one that covers Scotland is in preparation.

This study is frequently linked through the pidp variable to one of the main Understanding Society datasets: SN 6614 (End User Licence), SN 6931 (Special Licence) or SN 6676 (Secure Access). A Special Licence dataset containing School Codes for the main Understanding Society study (SN 7182) is also available. Further details can be found on the "http://discover.ukdataservice.ac.uk/series/?sn=2000053" title="Understanding Society series"> Understanding Society series Key data webpage.

The Archive also holds separate (i.e. not linked to Understanding Society) data from the National Pupil Database, available under Secure Access and Safe Room Access conditions. See SNs 7626, 7627 and 7628 (Secure Access) and SNs 7590, 7625, 7600, 7595, 7612 and 7606 (Safe Room Access) for details.

Latest edition information

The third edition (November 2020) includes Understanding Society participants who gave consent at Wave 4 and could be linked to the National Pupil Database (NPD). It includes NPD data up to academic year 2017/18. It also contains Understanding Society participants who gave consent and could be linked at Wave 1 and did not re-consent at Wave 4. NPD data up to academic year 2012/13 is included for these participants.

Background:
The Millennium Cohort Study (MCS) is a large-scale, multi-purpose longitudinal dataset providing information about babies born at the beginning of the 21st century, their progress through life, and the families who are bringing them up, for the four countries of the United Kingdom. The original objectives of the first MCS survey, as laid down in the proposal to the Economic and Social Research Council (ESRC) in March 2000, were:

• to chart the initial conditions of social, economic and health advantages and disadvantages facing children born at the start of the 21st century, capturing information that the research community of the future will require
• to provide a basis for comparing patterns of development with the preceding cohorts (the National Child Development Study, held at the UK Data Archive under GN 33004, and the 1970 Birth Cohort Study, held under GN 33229)
• to collect information on previously neglected topics, such as fathers' involvement in children's care and development
• to focus on parents as the most immediate elements of the children's 'background', charting their experience as mothers and fathers of newborn babies in the year 2000, recording how they (and any other children in the family) adapted to the newcomer, and what their aspirations for her/his future may be
• to emphasise intergenerational links including those back to the parents' own childhood
• to investigate the wider social ecology of the family, including social networks, civic engagement and community facilities and services, splicing in geo-coded data when available

• to provide control cases for the national evaluation of Sure Start (a government programme intended to alleviate child poverty and social exclusion)
• to provide samples of adequate size to analyse and compare the smaller countries of the United Kingdom, and include disadvantaged areas of England

Further information about the MCS can be found on the Centre for Longitudinal Studies web pages.

The content of MCS studies, including questions, topics and variables can be explored via the CLOSER Discovery website.

The first sweep (MCS1) interviewed both mothers and (where resident) fathers (or father-figures) of infants included in the sample when the babies were nine months old, and the second sweep (MCS2) was carried out with the same respondents when the children were three years of age. The third sweep (MCS3) was conducted in 2006, when the children were aged five years old, the fourth sweep (MCS4) in 2008, when they were seven years old, the fifth sweep (MCS5) in 2012-2013, when they were eleven years old, the sixth sweep (MCS6) in 2015, when they were fourteen years old, and the seventh sweep (MCS7) in 2018, when they were seventeen years old.

End User Licence versions of MCS studies:
The End User Licence (EUL) versions of MCS1, MCS2, MCS3, MCS4, MCS5, MCS6 and MCS7 are held under UK Data Archive SNs 4683, 5350, 5795, 6411, 7464, 8156 and 8682 respectively. The longitudinal family file is held under SN 8172.

Sub-sample studies:
Some studies based on sub-samples of MCS have also been conducted, including a study of MCS respondent mothers who had received assisted fertility treatment, conducted in 2003 (see EUL SN 5559). Also, birth registration and maternity hospital episodes for the MCS respondents are held as a separate dataset (see EUL SN 5614).

Release of Sweeps 1 to 4 to Long Format (Summer 2020)
To support longitudinal research and make it easier to compare data from different time points, all data from across all sweeps is now in a consistent format. The update affects the data from sweeps 1 to 4 (from 9 months to 7 years), which are updated from the old/wide to a new/long format to match the format of data of sweeps 5 and 6 (age 11 and 14 sweeps). The old/wide formatted datasets contained one row per family with multiple variables for different respondents. The new/long formatted datasets contain one row per respondent (per parent or per cohort member) for each MCS family. Additional updates have been made to all sweeps to harmonise variable labels and enhance anonymisation.

How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from MCS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.

Secure Access datasets:
Secure Access versions of the MCS have more restrictive access conditions than versions available under the standard End User Licence or Special Licence (see 'Access data' tab above).

Secure Access versions of the MCS include:

• detailed sensitive variables not available under EUL. These have been grouped thematically and are held under SN 8753 (socio-economic, accommodation and occupational data), SN 8754 (self-reported health, behaviour and fertility), SN 8755 (demographics, language and religion) and SN 8756 (exact participation dates). These files replace previously available studies held under SNs 8456 and 8622-8627
  
• detailed geographical identifier files which are grouped by sweep held under SN 7758 (MCS1), SN 7759 (MCS2), SN 7760 (MCS3), SN 7761 (MCS4), SN 7762 (MCS5 2001 Census Boundaries), SN 7763 (MCS5 2011 Census Boundaries), SN 8231 (MCS6 2001 Census Boundaries), SN 8232 (MCS6 2011 Census Boundaries), SN 8757 (MCS7), SN 8758 (MCS7 2001 Census Boundaries) and SN 8759 (MCS7 2011 Census Boundaries). These files replace previously available files grouped by geography SN 7049 (Ward level), SN 7050 (Lower Super Output Area level), and SN 7051 (Output Area level)
• linked education administrative datasets for Key Stages 1, 2, 4 and 5 held under SN 8481 (England). This replaces previously available datasets for Key Stage 1 (SN 6862) and Key Stage 2 (SN 7712)
  
• linked education administrative datasets for Key Stage 1 held under SN 7414 (Scotland)
• linked education administrative dataset for Key Stages 1, 2, 3 and 4 under SN 9085 (Wales)
  
• linked NHS Patient Episode Database for Wales (PEDW) for MCS1 – MCS5 held under SN 8302
• linked Scottish Medical Records data held under SNs 8709, 8710, 8711, 8712, 8713 and 8714;
• Banded Distances to English Grammar Schools for MCS5 held under SN 8394
• linked Health Administrative Datasets (Hospital Episode Statistics) for England for years 2000-2019 held under SN 9030
• linked Hospital of Birth data held under SN 5724.

The linked education administrative datasets held under SNs 8481,7414 and 9085 may be ordered alongside the MCS detailed geographical identifier files only if sufficient justification is provided in the application.

Researchers applying for access to the Secure Access MCS datasets should indicate on their ESRC Accredited Researcher application form the EUL dataset(s) that they also wish to access (selected from the MCS Series Access web page).

This dataset was collected as part of the SILCI project (‘Social influence and disruptive low carbon innovations’). The SILCI project ran from 2016 - 2021 at the Tyndall Centre for Climate Change Research, University of East Anglia and was funded by the European Research Council (ERC) through the Starting Grant #678799. Further details on the SILCI project and related publications can be found at: http://www.silci.org. The SILCI project explored disruptive low carbon innovations and how they spread through processes of social influence. As part of the SILCI project, a national online survey was conducted in the UK in 2019 to understand consumers' perceptions, communication behaviour, and adoption propensity towards a wide range of low-carbon innovations in four different consumer domains: transport, food, homes and energy. These datasets are published on ReShare at URL = https://reshare.ukdataservice.ac.uk/854723/ A repeat survey was conducted with respondents from the previous 2019 UK sample. The survey was implemented by an international market research company between 23rd November and 20th December 2020. A total of n=1175 responses were collected. The survey responses were coded and cleaned by the project team. Both the repeat survey instrument and cleaned response data are made available here.

The Wealth and Assets Survey (WAS) is a longitudinal survey, which aims to address gaps identified in data about the economic well-being of households by gathering information on level of assets, savings and debt; saving for retirement; how wealth is distributed among households or individuals; and factors that affect financial planning. Private households in Great Britain were sampled for the survey (meaning that people in residential institutions, such as retirement homes, nursing homes, prisons, barracks or university halls of residence, and also homeless people were not included).

The WAS commenced in July 2006, with a first wave of interviews carried out over two years, to June 2008. Interviews were achieved with 30,595 households at Wave 1. Those households were approached again for a Wave 2 interview between July 2008 and June 2010, and 20,170 households took part. Wave 3 covered July 2010 - June 2012, Wave 4 covered July 2012 - June 2014 and Wave 5 covered July 2014 - June 2016. Revisions to previous waves' data mean that small differences may occur between originally published estimates and estimates from the datasets held by the UK Data Service. Data are revised on a wave by wave basis, as a result of backwards imputation from the current wave's data. These revisions are due to improvements in the imputation methodology.

Note from the WAS team - November 2023:

“The Office for National Statistics has identified a very small number of outlier cases present in the seventh round of the Wealth and Assets Survey covering the period April 2018 to March 2020. Our current approach is to treat cases where we have reasonable evidence to suggest the values provided for specific variables are outliers. This approach did not occur for two individuals for several variables involved in the estimation of their pension wealth. While we estimate any impacts are very small overall and median pension wealth and median total wealth estimates are unaffected, this will affect the accuracy of the breakdowns of the pension wealth within the wealthiest decile, and data derived from them. We are urging caution in the interpretation of more detailed estimates.”

Survey Periodicity - "Waves" to "Rounds"
Due to the survey periodicity moving from “Waves” (July, ending in June two years later) to “Rounds” (April, ending in March two years later), interviews using the ‘Wave 6’ questionnaire started in July 2016 and were conducted for 21 months, finishing in March 2018. Data for round 6 covers the period April 2016 to March 2018. This comprises of the last three months of Wave 5 (April to June 2016) and 21 months of Wave 6 (July 2016 to March 2018). Round 5 and Round 6 datasets are based on a mixture of original wave-based datasets. Each wave of the survey has a unique questionnaire and therefore each of these round-based datasets are based on two questionnaires. While there may be some changes in the questionnaires, the derived variables for the key wealth estimates have not changed over this period. The aim is to collect the same data, though in some cases the exact questions asked may differ slightly. Detailed information on Moving the Wealth and Assets Survey onto a financial years’ basis was published on the ONS website in July 2019.

A Secure Access version of the WAS, subject to more stringent access conditions, is available under SN 6709; it contains more detailed geographic variables than the EUL version. Users are advised to download the EUL version first (SN 7215) to see if it is suitable for their needs, before considering making an application for the Secure Access version.

Further information and documentation may be found on the ONS "https://www.ons.gov.uk/economy/nationalaccounts/uksectoraccounts/methodologies/wealthandassetssurveywas" title="Wealth and Assets Survey"> Wealth and Assets Survey webpage. Users are advised to the check the page for updates before commencing analysis.

Occupation data for 2021 and 2022 data files

The ONS have identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. For further information on this issue, please see: https://www.ons.gov.uk/news/statementsandletters/occupationaldatainonssurveys.

The data dictionary for round 8 person file is not available.

Latest edition information

For the 20th edition (May 2025), the Round 8 data files were updated to include variables personr7, nounitsr8 and porage1tar8, and derived binary versions of multi-choice questions, their collected equivalents and imputed binary versions of these variables. Also, variables that were only collected for part of the round have been removed. Additional documentation for Round 8 was also added to the study, including an updated variable list and derived variable specifications.

Datasets and interview transcripts from a Q-methodology study with 54 individuals with a range of different experiences of, and expertise in relation to, the COVID-19 pandemic. Participants included, for example, seldom-heard and low-income individuals, health practitioners, health and social policy academics and relevant policy makers, key workers, furloughed staff, and individuals directed to shield by the NHS. Participants from England and Scotland rank ordered 60 statements onto a quasi-normal shaped grid according to their point of view in 2021. The dataset includes data from the Q sorts (n=54), socio-demographic survey (n=54) and post-sort qualitative interviews (n=53).

The Business Structure Database (BSD) contains a small number of variables for almost all business organisations in the UK. The BSD is derived primarily from the Inter-Departmental Business Register (IDBR), which is a live register of data collected by HM Revenue and Customs via VAT and Pay As You Earn (PAYE) records. The IDBR data are complimented with data from ONS business surveys. If a business is liable for VAT (turnover exceeds the VAT threshold) and/or has at least one member of staff registered for the PAYE tax collection system, then the business will appear on the IDBR (and hence in the BSD). In 2004 it was estimated that the businesses listed on the IDBR accounted for almost 99 per cent of economic activity in the UK. Only very small businesses, such as the self-employed were not found on the IDBR.

The IDBR is frequently updated, and contains confidential information that cannot be accessed by non-civil servants without special permission. However, the ONS Virtual Micro-data Laboratory (VML) created and developed the BSD, which is a 'snapshot' in time of the IDBR, in order to provide a version of the IDBR for research use, taking full account of changes in ownership and restructuring of businesses. The 'snapshot' is taken around April, and the captured point-in-time data are supplied to the VML by the following September. The reporting period is generally the financial year. For example, the 2000 BSD file is produced in September 2000, using data captured from the IDBR in April 2000. The data will reflect the financial year of April 1999 to March 2000. However, the ONS may, during this time, update the IDBR with data on companies from its own business surveys, such as the Annual Business Survey (SN 7451).

The data are divided into 'enterprises' and 'local units'. An enterprise is the overall business organisation. A local unit is a 'plant', such as a factory, shop, branch, etc. In some cases, an enterprise will only have one local unit, and in other cases (such as a bank or supermarket), an enterprise will own many local units.

For each company, data are available on employment, turnover, foreign ownership, and industrial activity based on Standard Industrial Classification (SIC)92, SIC 2003 or SIC 2007. Year of 'birth' (company start-up date) and 'death' (termination date) are also included, as well as postcodes for both enterprises and their local units. Previously only pseudo-anonymised postcodes were available but now all postcodes are real.

The ONS is continually developing the BSD, and so researchers are strongly recommended to read all documentation pertaining to this dataset before using the data.

Linking to Other Business Studies
These data contain IDBR reference numbers. These are anonymous but unique reference numbers assigned to business organisations. Their inclusion allows researchers to combine different business survey sources together. Researchers may consider applying for other business data to assist their research.

Latest Edition Information
For the sixteenth edition (March 2024), data files and a variable catalogue document for 2023 have been added.

Output Area is the lowest geographical level at which census estimates are provided. Output Areas were introduced in Scotland at the 1981 Census and in all the countries of the UK at the 2001 Census.

The Output Areas and Small Areas list contains 232,296 areas of the following constituent geographies:

• 171,372 Output Areas in England
• 46,351 Output Areas in Scotland
• 4,537 Small Areas in Northern Ireland
• 10,036 Output Areas in Wales

Please visit ONS Beginner's Guide to UK Geography for more info.

The boundaries are available as either extent of the realm (usually this is the Mean Low Water mark but in some cases boundaries extend beyond this to include off shore islands) or

clipped to the coastline (Mean High Water mark).

The Health Survey for England 2011: Teaching Dataset is based on the Health Survey for England, 2011 (available from the UK Data Archive under SN 7260) and constitutes real data which are used by the government and are behind many headlines. The teaching dataset contains fewer variables and has been subjected to certain simplifications and additions for the purpose of learning and teaching.

The main differences are:

• the number of variables has been reduced
• weighting has been simplified
• a reduced codebook is provided

The Workplace Employment Relations Study, 2011 (also known as WERS6) is the sixth in a series of national surveys of employment relations at the workplace level. Earlier surveys were conducted in 1980, 1984, 1990, 1998 and 2004 (the series was originally known as the Workplace Industrial Relations Survey, or WIRS). The aim of each survey in the WERS series has been to provide large-scale, statistically reliable evidence about a broad range of employment relations and practices across almost every sector of the economy in Great Britain. The data were collected to serve three purposes: to map British employment relations over time; to inform policy and practice, and stimulate debate; and to provide a comprehensive and statistically robust dataset on British workplace employment relations for public use.

The 1990, 1998 and 2004 WERS comprised a freshly selected cross-section sample and a separate, more limited panel sample consisting of workplaces who participated in the previous cross-section survey. The key design innovation of the 2011 WERS was the integration of the two elements so that workplaces in the panel sample were eligible for all four components of WERS 2011. Weights were devised to enable the panel sample to be combined with the fresh sample to form a combined cross-sectionally representative sample. The WERS 2011 has four components: a Survey of Managers comprising the Employee Profile Questionnaire (EPQ) and the Management Questionnaire (MQ); a Survey of Worker Representatives (WRQ); a Survey of Employees (SEQ); and a Financial Performance Questionnaire (FPQ) which detailed the financial performance of trading sector establishments in the 12 months before the survey. The FPQ data, alongside region identifiers, detailed industry codes for the MQ and other anonymised but potentially disclosive data will be available through the UK Data Archive's Secure Data Service (see below).

The WERS sponsors have established the 2011 Workplace Employment Relations Study: Information and Advice user support website for users of the WERS 2011 data. The site includes provision for users to contact the WERS research team with queries about the data. Further BIS information about WERS 2011, including the First Findings report and key tables are also provided on the gov.uk 2011 WERS webpage.

Confidentiality and anonymisation edits:
The following data items have been removed from the general-use (standard access or End User Licence (EUL)) version of WERS 2011: names of respondents, the workplace at which they worked, region identifiers, detailed industry classification below Section level, the Inter-departmental Business Register (IDBR) reference numbers, verbatim answers, and all data from the Financial Performance Questionnaire (FPQ). The restricted-access version of the data that will be available through the Secure Data Service (SDS) contains region identifiers, detailed industry classification, and the IDBR reference numbers of the workplaces that have consented to the linking of their WERS data to other sources and data from the FPQ. (Users should note that the SDS also holds a variety of data from WERS 2004 (WERS5).)

Latest edition:
For the sixth edition (September 2014), a new version of the management questionnaire (MQ) file was deposited, with additional variables included. Amendments have also been made to the mqsetup Stata ‘do’ file to take account of the additional variables. Finally, access restrictions have now been lifted on the Financial Performance Questionnaire (FPQ), so the data have been added to the study. For full details, see the updated Introductory Note in the documentation.

Understanding Society (the UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex, and the survey research organisations Verian Group (formerly Kantar Public) and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.

The Understanding Society: UKMOD Input Data, 2010-2019: Special Licence Access dataset provides input data for the longitudinal version of the UKMOD microsimulation model. The longitudinal version of UKMOD runs on Understanding Society data and covers the period 2010-2019 (Waves 1-11). The UKHLS is a large panel survey with a sample of approximately 40,000 households in its first wave. It contains detailed income data and a wide range of demographic and labour market information. As such it is the primary survey of interest in the UK for those interested in longitudinal analysis.

UKMOD is a tax-benefit microsimulation model (MSM) for the UK and its constituent nations (England, Wales, Scotland, and Northern Ireland) that originated from EUROMOD. Since 2020 UK MOD has replaced, as a stand-alone model, the UK component of EUROMOD. UKMOD is freely accessible, released open-source, and thoroughly documented and validated using external data. The standard cross-sectional version of UKMOD uses the Family Resources Survey (FRS) as its input dataset.

A tax-benefit microsimulation model is a computer code that calculates disposable income for each micro-unit (such as individual or household) in a representative sample of the population, under a specific policy scenario. Based on micro-level information about the individual and household characteristics and on legislative rules, UKMOD simulates the amount of fiscal liabilities and benefit entitlements at the tax-benefit unit level.

Tax-benefit microsimulation models are used to answer "what if" questions about the effects of tax and benefit reforms on household incomes and the income distribution. Such analysis is regularly performed for Budget and other Government policy announcements, and is also highly relevant for the design of alternative reforms and new policy instruments taking account of the diverse economic circumstances of the UK population. The longitudinal version of the data allows researchers to address additional questions, for example about the evolution of outcomes of interest over time. It also allows UKMOD outputs to be linked with additional information not used by the tax and benefit model but present in the UKHLS data for example, about labour market activity, retirement, health and wellbeing and others.

SN 9147 can be used on its own with UKMOD and is sufficient to conduct typical UKMOD analysis. For applicants seeking to add additional Understanding Society variables not included in the UKMOD dataset SN 9147, accessing SN 6614 (Safeguarded / EUL) and linking it to dataset SN 9147 normally provides a sufficient level of detail. However, in some instances, the desired variables may only be available in the safeguarded / Special Licence equivalent, SN 6931. Full details of how to link the datasets are provided in the User Guide.

The COVID-19 pandemic has caused major disruptions to families' lives in many ways, including through lockdowns, social distancing, home learning requirements, and restrictions. This resulted in a rapidly changing situation where different pressures have arisen for children, young people and their families over time. Understanding the psychological effects of the COVID-19 pandemic on children and young people, through the collection of high quality data and in a way that could directly inform policy, was set out as an immediate research priority in a Lancet position paper (Holmes et al., 2020) at the start of the pandemic. The Co-SPACE study was launched on 30th March 2020, a week after the first national lockdown was implemented in the UK, with the purpose of using the findings to inform resources and support for families. It was then extended in 2022 under the project on 'Learning from the trajectories of mental health challenges for children, young people and parents over the course of the Covid-19 pandemic' in collaboration with the CORONA x CODOMO project in Japan (run by Dr Naho Morisaki at the National Center for Child Health and Development).

The Co-SPACE project aimed to:

track participating children and young people’s mental health throughout the COVID-19 crisis,

identify what protects children and young people from deteriorating mental health (over time, and at particular stress points),

determine how this varies according to child, family and environmental characteristics.

The Co-SPACE study, overall, involved an online longitudinal survey completed monthly from March 2020 to July 2021 by (i) UK-based parents/carers of children and young people (aged 4-16 years, at the start of the study), and (ii) their children (if aged 11-16 years, at the start of the study). Additional, longer-term follow-ups were then completed 6-monthly in March/April 2022, October 2022, and March/April 2023 by parents who took part in the original Co-SPACE survey. To develop a richer understanding of people’s experiences, qualitative interviews were also conducted with parents/carers, young people, and people who work with them. The current data available includes parent/carer reported survey data only.

The study was designed and conducted with rapid and meaningful stakeholder involvement, including through in-depth discussion with advisory groups of experts, young people, and parents/carers. Parent/carer and young people's involvement was facilitated through the UKRI Emerging Minds Research Network Plus.

In addition to the Principal Investigators (PW, CC, & SS), contributors to the study were as follows: Praveetha Patalay, UCL; Helen Dodd, University of Exeter; Pete Lawrence, University of Southampton; Simona Skripkauskaite, University of Oxford; Samantha Pearcey, University of Oxford; Adrienne Shum, University of Oxford; Amy McCall, University of Oxford; Olly Robertson, University of Oxford; Bettina Moltrecht, UCL; Eoin McElroy, Ulster University; Lowrie Hilladakis (nee Burgess), University of Oxford; Ning Ding, University of Oxford; Martha Oakes, University of Oxford; Naho Morisaki, National Center for Child Health and Development .

Further information, including research reports, are available from the Co-SPACE project website.

Latest edition information

For the second edition (January 2025), the study has been updated to include three new waves of data collection conducted between March 2022 and March 2023. The data and documentation files have been replaced with new versions.

The inequities of the COVID-19 pandemic were clear by April 2020 when data showed that despite being just 3.5% of the population in England, Black people comprised 5.8% of those who died from the virus; whereas White people, comprising 85.3% of the population, were 73.6% of those who died. The disproportionate impact continued with, for example, over-policing: 32% of stop and search in the year ending March 2021 were of Black, Asian and Minority Ethnic (BAME) males aged 15-34, despite them being just 2.6% of the population. The emergency measures introduced to govern the pandemic worked together to create a damaging cycle affecting Black, Asian and Minority Ethnic families and communities of all ages. Key-workers – often stopped by police on their way to provide essential services – could not furlough or work from home to avoid infection, nor support their children in home-schooling. Children in high-occupancy homes lacked adequate space and/ or equipment to learn; such homes also lacked leisure space for key workers to restore themselves after extended hours at work. Over-policing instilled fear across the generations and deterred BAME people – including the mobile elderly - from leaving crowded homes for legitimate exercise, and those that did faced the risk of receiving a Fixed Penalty Notice and a criminal record. These insights arose from research by Co-POWeR into the synergistic effects of emergency measures on policing, child welfare, caring, physical activity and nutrition. Using community engagement, a survey with 1000 participants and interviews, focus groups, participatory workshops and community testimony days with over 400 people in total, we explored the combined impact of COVID-19 and discrimination on wellbeing and resilience across BAME FC in the UK. This policy note crystallises our findings into a framework of recommendations relating to arts and media communications, systems and structures, community and individual well-being and resilience. We promote long term actions rather than short term reactions. In brief, we conclude that ignoring race, gender and class when tackling a pandemic can undermine not only wellbeing across Black, Asian and Minority Ethnic families and communities (BAME FC) but also their levels of trust in government. A framework to protect wellbeing and resilience in BAME FC during public health emergencies was developed by Co-POWeR to ensure that laws and guidance adopted are culturally competent.

The Centre for Time Use Research (CTUR) Time Use Survey conducted in March 2023 is a UK representative survey of UK adults aged 18+ (N=2179) collected using a multi-field digital time-use diary design that corresponds to the information collected in best practice pen-and-paper designs such as the Harmonised European Time Use Survey (HETUS). A general-purpose time use survey design, incorporating multiple continuous independent diary fields, is important because it offers both continuity with historically collected time use diary data and versatility, providing data for a wide-ranging and still growing corpus of substantive research and policy applications.

The online diary design developed at the CTUR (the Extended Light Diary Digital Instrument - ELiDDI) mimics the ‘light diary’ visually intuitive interface, and including all the fields and activities of the HETUS diary. It builds on and is compatible with the previous CaDDI online diary design used for the Centre for Time Use Research (CTUR) UK Time Use Survey 6-Wave Sequence across the COVID-19 Pandemic 2016-2021(UKDS Study ID 8741). Methodological work to date suggests that this visually intuitive design does not lead to an erosion of data quality or increased respondent burden.

The nationally representative survey was conducted in March 2023 in a 3-way collaboration between CTUR, Dynata (a leading international market research agency conforming to the Market Research Society's ethical code who designed the digital diary interface) and the National Centre for Social Research (NatCen), who provided the UK representative sample and ran the logistics of the data collection exercise.

Respondents were invited to complete 2 diaries, one on a randomly sampled weekday, one on a weekend day, recording activities, location, co-presence, device use, and enjoyment across continuous 10-minute episodes throughout the diary day. The accompanying background questionnaire collected information on the standard socio-demographic variables, and a diary day questionnaire included additional information about each diary day.